WO2024055250A1

WO2024055250A1 - Base station, user equipment and methods in a wireless communications network

Info

Publication number: WO2024055250A1
Application number: PCT/CN2022/119086
Authority: WO
Inventors: Hao Zhang; Ang FENG; Christian Braun; Ming Li; Georgy LEVIN
Original assignee: Telefonaktiebolaget LM Ericsson AB
Current assignee: Telefonaktiebolaget LM Ericsson AB
Priority date: 2022-09-15
Filing date: 2022-09-15
Publication date: 2024-03-21
Anticipated expiration: 2025-03-15

Abstract

A method performed by a Base Station (BS) is provided. The method is for handling Precoding Matrix Indicator (PMI) reporting from a User Equipment (UE) in a wireless communications network. The PMI reporting relates to reporting Channel State Information (CSI) estimations of a Downlink (DL) channel. The BS sends (202) a request to the UE, requesting PMI reporting to be provided by one or more PMI reporting iterations. The one or more PMI reporting iterations are requested to comprise iterative reports of CSI estimations of the DL channel based on an algorithm. The algorithm is represented by a residual PMI selection algorithm. The BS sends (203) a CSI Reference Signal (RS) in the DL channel to be used by the UE as a basis for the PMI reporting iterations. The BS then receives (204) PMI reporting iterations from the UE. The PMI reporting iterations are according to the request and based on the sent CSI RS. Publ.

Description

BASE STATION, USER EQUIPMENT AND METHODS IN A WIRELESS COMMUNICATIONS NETWORK

TECHNICAL FIELD

Embodiments herein relate to a Base Station (BS) , a User Equipment (UE) and methods therein. In some aspects, they relate to handling Precoding Matrix Indicator (PMI) reporting from the UE to the BS in the wireless communications network. The PMI reporting relates to reporting Channel State Information (CSI) estimations of a Downlink (DL) channel.

BACKGROUND

In a typical wireless communication network, wireless devices, also known as wireless communication devices, mobile stations, stations (STA) and/or User Equipment (UE) , communicate via a Wide Area Network or a Local Area Network such as a Wi-Fi network or a cellular network comprising a Radio Access Network (RAN) part and a Core Network (CN) part. The RAN covers a geographical area which is divided into service areas or cell areas, which may also be referred to as a beam or a beam group, with each service area or cell area being served by a radio network node such as a radio access node e.g., a Wi-Fi access point, a Base Station (BS) or a radio base station (RBS) , which in some networks may also be denoted, for example, a Base Station (BS) , a NodeB, eNodeB (eNB) , or gNodeB (gNB) as denoted in Fifth Generation (5G) telecommunications. A service area or cell area is a geographical area where radio coverage is provided by the radio network node. The radio network node communicates over an air interface operating on a radio frequency with the wireless devices within the range of the radio network node.

3rd Generation Partnership Project (3GPP) is the standardization body for specifying the standards for the cellular system evolution, e.g., including 3G, 4G, 5G and the future evolutions. Specifications for Evolved Universal Terrestrial Radio Access (E-UTRA) and Evolved Packet System (EPS) have been completed within the 3GPP. In 4G also called a Fourth Generation (4G) network, EPS is core network and E-UTRA is radio access network. In 5G, 5GC is core network, NR is radio access network. As a continued network evolution, the new release of 3GPP specifies a 5G network also referred to as 5G New Radio (NR) and 5G Core (5GC) .

Frequency bands for 5G NR are being separated into two different frequency ranges, Frequency Range 1 (FR1) and Frequency Range 2 (FR2) . FR1 comprises sub-6 GHz frequency bands. Some of these bands are bands traditionally used by legacy standards but have been extended to cover potential new spectrum offerings from 410 MHz to 7125 MHz. FR2 comprises frequency bands from 24.25 GHz to 52.6 GHz. Bands in this millimeter wave range have shorter range but higher available bandwidth than bands in the FR1.

Multi-antenna techniques may significantly increase the data rates and reliability of a wireless communication system. For a wireless connection between a single user, such as UE, and a base station (BS) , the performance is in particular improved if both the transmitter and the receiver are equipped with multiple antennas, which results in a Multiple-Input Multiple-Output (MIMO) communication channel. This may be referred to as Single-User (SU) -MIMO. In the scenario where MIMO techniques is used for the wireless connection between multiple users and the base station, MIMO enables the users to communicate with the base station simultaneously using the same time-frequency resources by spatially separating the users, which increases further the cell capacity. This may be referred to as Multi-User (MU) -MIMO. Note that MU-MIMO may benefit when each UE only has one antenna. The cell capacity can be increased linearly with respect to the number of antennas at the BS side. Due to that, more and more antennas are employed in BS. Such systems and/or related techniques are commonly referred to as massive MIMO.

In current 5G and 4G wireless communications networks, CSI plays a crucial role in many areas such as e.g., radio link adaptation, multi-user scheduling, and beamforming, etc. In general, CSI is much more difficult to be acquired at a transmitter (TX) side than a receiver (RX) side. From viewpoint of a (BS) , CSI corresponds to Downlink (DL) CSI and Uplink (UL) CSI. Typically, aforementioned areas are highly depended on the DL CSI, rather than the UL CSI.

In Time Division Duplex (TDD) systems, thanks to the reciprocity of a wireless channel, DL CSI may be derived by UL CSI directly, as long as the channel does not vary too fast.

However, in Frequency Division Duplex (FDD) systems, since the wireless channel is not reciprocal, a UE has to feed the DL CSI back to BS. The true CSI is not easy to be fed back to the TX side because of the high overhead needed in the feedback resources, e.g. an UL channel. Instead, the true CSI has to be compressed to reduce the overhead in the feedback channel. For example, codebook-based schemes are proposed to use Precoding Matrix Indicator (PMI) to represent the CSI. 3GPP defines a set of codebooks that are known to both a BS and a UE. Once a UE estimates the CSI, it selects the precoding matrix that is closest to the estimated CSI, and then sends back the index of that matrix. This is a method to acquire the CSI with a kind of compression of information, whereas less resources are needed. However, the accuracy of CSI is deteriorated since current PMI solutions cannot provide high angular resolution in the spatial domain.

SUMMARY

As a part of developing embodiments herein a problem was identified by the inventors and will first be discussed.

Basically, current PMI reporting is based on one-time calculation. At each loop, also referred to as iteration, a Type I codebook only allows one PMI, while a Type II codebook extents the value to more than one. Although the Type II codebook significantly increases the accuracy of a feedback CSI, it is constrained by the number of available resources in the feedback channel. This limitation has recognized as a main blocking issue for many promising features, such as e.g., in-field Antenna Calibration (AC) , UE assisted obstacle detection, etc.

A method of novel CSI feedback to improve the CSI accuracy for DL AC has been discussed. This method is based on an Orthogonal Matching Pursuit (OMP) algorithm. The OMP algorithm selects an optimal precoding matrix in a candidate matrix set in each iteration. A key step of OMP is that the precoding matrix is selected according to a residual channel in which the contribution from previous selected precoding matrices has been removed. A residual channel when used herein may mean the difference between the true CSI and the compressed CSI produced by previous selected precoding matrices.

Besides the OMP algorithm, the well-known Singular Value Decomposition (SVD) algorithm may also be employed to generate the residual channel. But it needs more computational complexity, therefore it is not recommended here.

By analyzing the OMP, it has been seen that it is not necessarily to be one-time calculation. The residual channel may be stored and continued for a next loop of PMI reporting. That means, the compressed CSI may be arbitrarily close to the true CSI, without restraining by the limited resource in the feedback channel. Unfortunately, such mechanism is not supported by current 3GPP standard.

An object of embodiments herein is to improve CSI acquisition for a DL channel from a UE in a wireless communications network.

According to an aspect of embodiments herein, the object is achieved by a method performed by a Base Station, BS. The method is for handling Precoding Matrix Indicator, PMI, reporting from a User Equipment, UE, in a wireless communications network. The PMI reporting relates to reporting Channel State Information, CSI, estimations of a Downlink, DL, channel. The BS sends a request to the UE, requesting PMI reporting to be provided by one or more PMI reporting iterations. The one or more PMI reporting iterations are requested to comprise iterative reports of CSI estimations of the DL channel based on an algorithm. The algorithm is represented by a residual PMI selection algorithm. The BS sends a CSI Reference Signal, RS, in the DL channel to be used by the UE as a basis for the PMI reporting iterations. The BS then receives (204 AB) PMI reporting iterations from the UE. The PMI reporting iterations are according to the request and based on the sent CSI RS.

According to an aspect of embodiments herein, the object is achieved by a method performed by a User Equipment, UE. The method is for handling Precoding Matrix Indicator, PMI, reporting to a Base Station, BS, in a wireless communications network. The PMI reporting relates to reporting Channel State Information, CSI, estimations of a Downlink, DL, channel. The UE receives a request from the BS, requesting PMI reporting to be provided by one or more PMI reporting iterations.

The one or more PMI reporting iterations are requested to comprise iterative reports of CSI estimations of the DL channel based on an algorithm. The algorithm is represented by a residual PMI selection algorithm. The UE receiving a CSI Reference Signal, RS, in the DL channel from the BS. The RS is to be used by the UE as a basis for the PMI reporting iterations. The UE estimates the CSI in the DL channel for the PMI reporting iterations, based on the CSI RS according to the request. The UE then sends the PMI reporting iterations to the BS. The PMI reporting iterations are according to the estimated CSI in the DL channel.

According to another aspect of embodiments herein, the object is achieved by a Base Station, BS, configured to handling Precoding Matrix Indicator, PMI, reporting from a User Equipment, UE, in a wireless communications network. The PMI reporting is adapted to relate to reporting Channel State Information, CSI, estimations of a Downlink, DL, channel. The BS is further configured to:

-send a request to the UE, requesting PMI reporting to be provided by one or more PMI reporting iterations, where the one or more PMI reporting iterations are to be requested to comprise iterative reports of CSI estimations of the DL channel, based on an algorithm, which algorithm is adapted to be represented by a residual PMI selection algorithm,

-send a CSI Reference Signal, RS, in the DL channel, to be used by the UE as a basis for the PMI reporting iterations, and

-receive from the UE, PMI reporting iterations according to the request and based on the sent CSI RS.

According to another aspect of embodiments herein, the object is achieved by a User Equipment, UE, configured to handle Precoding Matrix Indicator, PMI, reporting to a Base Station, BS, in a wireless communications network. The PMI reporting is adapted to relate to reporting Channel State Information, CSI, estimations of a Downlink, DL, channel. The UE is further configured to:

-receive a request from the BS, requesting PMI reporting to be provided by one or more PMI reporting iterations, where the one or more PMI reporting iterations are adapted to be requested to comprise iterative reports of CSI estimations of the DL channel, based on an algorithm, which algorithm is adapted to be represented by a residual PMI selection algorithm,

-receive from the BS, a CSI Reference Signal, RS, in the DL channel, to be used by the UE as a basis for the PMI reporting iterations,

-estimate the CSI in the DL channel for the PMI reporting iterations based on the CSI RS according to the request, and

-send to the BS, the PMI reporting iterations according to the estimated CSI in the DL channel.

Thanks to the feature that the PMI reporting is provided by the UE by multiple PMI report iterations, comprising iterative reports of CSI estimations of the DL channel, based on the residual PMI selection algorithm, the PMI reporting of the CSI estimations can be highly accurate. A residual PMI selection algorithm when used herein is an iterative algorithm that can select a best PMI from the candidate precoding matrix set according to the residual CSI in which the contribution of previously selected precoding matrices has been subtracted from the true CSI. Thus, the CSI acquisition of the DL channel from the UE in the wireless communications network is improved by this enhanced PMI reporting.

Embodiments herein providing the highly accurate CSI estimations e.g., provide the following advantages:

- An improved performance of in-field AC by highly accurate CSI feedback from the UE 120.

- A lowered computational load in the UE 120 for CSI acquisition.

- A lowered overhead in feedback resources, i.e. UL channel.

- They are applicable in both TDD and FDD systems.

- They enable UE assisted obstacle detection.

BRIEF DESCRIPTION OF THE DRAWINGS

Examples of embodiments herein are described in more detail with reference to attached drawings in which:

Figure 1 is a schematic block diagram illustrating embodiments of a wireless communications network.

Figure 2 is a flowchart depicting an embodiment of a method in a base station.

Figure 3 is a flowchart depicting an embodiment of a method in a UE.

Figure 4 is a sequence diagram illustrating an embodiment herein.

Figure 5 is a sequence diagram illustrating another embodiment herein.

Figures 6 a-b are schematic block diagrams illustrating embodiments of a base station.

Figures 7 a-b are schematic block diagrams illustrating embodiments of a UE.

Figure 8 schematically illustrates a telecommunication network connected via an intermediate network to a host computer.

Figure 9 is a generalized block diagram of a host computer communicating via a base station with a user equipment over a partially wireless connection.

Figures 10-13 are flowcharts illustrating methods implemented in a communication system including a host computer, a base station, and a user equipment.

DETAILED DESCRIPTION

Exemplary embodiments herein relate to iterative PMI reporting for highly accurate CSI feedback.

Figure 1 is a schematic overview depicting a wireless communications network 100 wherein embodiments herein may be implemented. The wireless communications network 100 comprises one or more RANs and one or more CNs. The wireless communications network 100 may use 5G NR but may further use a number of other different technologies, such as, 6G, Wi-Fi, (LTE) , LTE-Advanced, Wideband Code Division Multiple Access (WCDMA) , Global System for Mobile communications/enhanced Data rate for GSM Evolution (GSM/EDGE) , or Ultra Mobile Broadband (UMB) , just to mention a few possible implementations.

Network nodes, such as a BS 110, operate in the wireless communications network 100. The BS 110 e.g. provides a number of cells and may use these cells for communicating with UEs such as e.g. a UE 120. The BS 110 may be a transmission and reception point e.g. a network node, a radio access network node such as a base station, a radio base station, a NodeB, an evolved Node B (eNB, eNodeB, eNode B) , an NR/g Node B (gNB) , a base transceiver station, a radio remote unit, an Access Point Base Station, a base station router, a transmission arrangement of a radio base station, a stand-alone access point, a Wireless Local Area Network (WLAN) access point, an Access Point Station (AP STA) , an access controller, a UE acting as an access point or a peer in a Device to Device (D2D) communication, or any other network unit capable of communicating with a UE served by the BS 110 depending e.g. on the radio access technology and terminology used.

UEs operate in the wireless communications network 100, such as e.g. the UE 120. The UE 120 may e.g. be an NR device, a mobile station, a wireless terminal, an NB-IoT device, an enhanced Machine Type Communication (eMTC) device, an NR RedCap device, a CAT-M device, a Vehicle-to-everything (V2X) device, Vehicle-to-Vehicle (V2V) device, a Vehicle-to-Pedestrian (V2P) device, a Vehicle-to-Infrastructure (V2I) device, and a Vehicle-to-Network (V2N) device, a Wi-Fi device, an LTE device and a non-access point (non-AP) STA, a STA, that communicates via a base station such as e.g. the network node 110, one or more Access Networks (AN) , e.g. RAN, to one or more core networks (CN) . It should be understood by the skilled in the art that the UE relates to a non-limiting term which means any UE, terminal, wireless communication terminal, user equipment, (D2D) terminal, or node e.g. smart phone, laptop, mobile phone, sensor, relay, mobile tablets or even a small base station communicating within a cell.

Methods herein may in one aspect be performed by the BS 110, in another aspect by the UE 120. As an alternative, a Distributed Node (DN) and functionality, e.g. comprised in a cloud 135 as shown in Figure 1, may be used for performing or partly performing the methods of embodiments herein.

Examples of embodiments herein e.g. provides two variants of embodiments for iterative PMI reporting based on an algorithm, referred to as A embodiments and B embodiments. Features applicable to both embodiments are referred to as AB. The algorithm is a residual PMI selection algorithm. E.g., in each iteration, the best PMI is select based on a residual CSI left from previous iterations. The algorithm may as one example be an OMP algorithm. A complete PMI reporting is composed of multiple PMI report iterations, also referred to as PMI reporting iterations, and PMI reporting loops. It is noted that the wordings iteration and loop should be seen as equal and may be used interchangeably herein. E.g., the PMI reports are requested iteratively in which a residual channel is kept and reused for each new iteration. Such embodiments are particularly helpful for the use cases which requires high CSI accuracy and angular resolution but not so strict requirement on latency. These use cases include but not limited to such as e.g., in-field AC and, UE assisted obstacle detection e.g. according to US20200249339A1.

A embodiments

The first variant of the embodiments is referred to as A embodiments. In some of the A embodiments, the UE 120 performs iterative OMP calculations and PMI reporting according to a BS 110 request. Subsequently the BS 110 receives a Mean Squared Error (MSE) of the CSI from the UE 120, to decide and inform the UE 120 about the further number of iterations left. The A embodiments abbreviates the computational load on the UE 120 side due to the iterative PMI calculation and reporting but requires more assistance information exchanging between the UE 120 and the BS 110 than the B embodiments.

B embodiments

The second variant of the embodiments is referred to as B embodiments. In some of the B embodiments, the UE 120 decides the number of iterations of OMP calculations which is needed according to the BS request. Meanwhile, the UE 120 may exit calculations earlier according to the BS 110 configuration. This e.g. means that the UE 120 performs a number of iterative PMI calculations according to the BS 110 requirement, and a small number of iterations is expected for a lower requirement. The UE 120 then reports the PMI iteratively according to a BS 110 UL resource scheduling. The B embodiments require less assistance information exchanging between the UE 120 and the BS 110 than the A embodiments and allows more flexibility on PMI reporting by the UE 120, but increases the computational load on the UE 120 side.

As mentioned above, the above embodiments provide highly accurate CSI feedback which e.g. comprises the following advantages:

- Improved performance of in-field AC by highly accurate CSI feedback from the UE 120.

- Lowered computational load in the UE 120 for CSI acquisition.

- Lowered overhead in feedback resources, i.e. UL channel.

- Applicable in both TDD and FDD systems.

- Enable UE 120 assisted obstacle detection.

A number of embodiments will now be described, some of which may be seen as alternatives, while some may be used in combination.

Figure 2 shows exemplary embodiments of a method performed by the BS 110. The method is for handling PMI reporting from the UE 120 in the wireless communications network 100. The PMI reporting relates to reporting CSI estimations of a DL channel.

The method comprises the following actions, which actions may be taken in any suitable order. Optional actions are referred to as dashed boxes in Figure 2.

Action 201

The BS 110 may obtain capability data from the UE 120. The capability data indicates that the UE 120 is capable of performing the PMI reporting and supporting the algorithm. In some embodiments, the capability data further indicates a number of iterations that is supported by the UE 120. This relates to both Embodiments A and B.

Action 202

The BS 110 sends a request to the UE 120. This is to request PMI reporting to be provided by one or more PMI reporting iterations. The one or more PMI reporting iterations are requested to comprise iterative reports of CSI estimations of the DL channel based on an algorithm. The algorithm is represented by a residual PMI selection algorithm, e.g. an OMP or SVD algorithm. The algorithm e.g., relates to selecting a PMI in a candidate PMI set, in each iteration out of a set of iterations based on residual CSI estimations left from previous iterations. This relates to both Embodiments A and B.

In some of the B Embodiments, the request for PMI reporting further comprises a required MSE level.

Action 203

The BS 110 sends a CSI Reference Signal (RS) in the DL channel. The RS is to be used by the UE 120 as a basis for the PMI reporting iterations. E.g., for CSI estimations of the DL channel based on an algorithm to provide the PMI reporting iterations according to the request. This relates to both Embodiments A and B.

Action 204

The BS 110 receives PMI reporting iterations from the UE 120. The sent PMI reporting iterations are according to the request and based on the sent CSI RS. This relates to both Embodiments A and B. However, the steps within this action may be performed in different ways for the A and B embodiments.

A Embodiments:

In the A Embodiments, this action of receiving the PMI reporting iterations according to the request and based on the sent CSI RS from the UE 120, may be performed according to the following:

The BS 110 receives 204 A-1 a first PMI report from the UE 120. The first PMI report relates to a first iteration and indicates an associated MSE of the CSI estimations.

The BS 110 decides 204 A-2 the number of further PMI reporting iterations that is left based on the first PMI report.

The BS 110 sends 204 A-3 a subsequent PMI reporting request to the UE 120. The subsequent PMI reporting request indicates the decided number of further PMI reporting iterations that is left.

The BS 110 receives 204 A-4 from the UE 120, one or more subsequent PMI reporting iterations relating to the decided number of further iterations that is left. The subsequent PMI reporting may also indicate MSE.

An example scenario of an A Embodiment related to the BS side may comprises the following: The BS 110 may receive the capability data from one or multiple UEs, e.g. the UE 120. The BS 110 may select those UEs which are capable to support the required algorithm e.g. OMP algorithm and iterative PMI reporting, e.g. the UE 120. The BS 110 then sends out the PMI request and CSI RS to the UE 120. When the BS 110 receives PMI and MSE feedback from the UE 120, it estimates the CSI accuracy. If the CSI accuracy is not OK, the BS 110 may trigger another loop of PMI feedback. If the CSI accuracy is OK, the BS 110 stops the iteration and uses the received information to reconstruct the DL CSI. An optional step is also provided, to send an indicator to the UE 120 to stop the process.

B Embodiments:

As mentioned above, the request for PMI reporting further comprises a required MSE level, in the B Embodiments. Further, in the B Embodiments this action of receiving the PMI reporting iterations according to the request and based on the sent CSI reference signals from the UE 120, may be performed according to the following:

The BS 110 receives 204 B-1 an indication from the UE 120. The indication indicates a number of iterations that will be used for the PMI reporting. The number of iterations that will be used for the PMI reporting is calculated based on the required MSE level.

The BS 110 sends 204 B-2 to the UE 120, a grant to send the PMI reporting. The grant to send the PMI reporting comprises the indicated number of iterations and scheduling information for the indicated number of iterations, and

The BS 110 receiving 204 B-3 the PMI reporting from the UE 120. The PMI reporting is according to the indicated number of iterations. The PMI reporting iterations are received according to any one out of: at the same time or iteratively.

An example scenario of a B Embodiment related to the BS side may comprise the following. In this procedure, the BS 110 sends the requested MSE level to the UE 120 directly. After receiving the number of iterations from the UE 120, the BS 110 schedules the UL resource for a single or multiple loops of PMI reporting.

Action 205

The BS 110 reconstructs DL CSI related to the DL channel. The reconstruction is based on the received PMI reporting iterations. To reconstruct DL CSI related to the DL channel is e.g., performed by linear combination of precoding matrices and corresponding coefficients, in which the precoding matrices are selected according to the PMI, and the coefficients include amplitudes and phases. This relates to both Embodiments A and B.

Figure 3 shows exemplary embodiments of method performed by the UE 120. The method is for handling PMI reporting to the BS 110 in the wireless communications network 100. The PMI reporting relates to reporting CSI estimations of a DL channel.

The method comprises the following actions, which actions may be taken in any suitable order. Optional actions are referred to as dashed boxes in Figure 3.

Action 301

The UE 120 may send capability data to the BS 110. The capability data indicates that the UE 120 is capable of PMI reporting and supporting the algorithm.

The capability data may further indicate a number of iterations that is supported by the UE 120. This relates to both Embodiments A and B.

Action 302

The UE 120 receives a request from the BS 110. The request is requesting PMI reporting to be provided by one or more PMI reporting iterations. The one or more PMI reporting iterations are requested to comprise iterative reports of CSI estimations of the DL channel, based on an algorithm. The algorithm is represented by a residual PMI selection algorithm. The algorithm e.g., relates to selecting a PMI in a candidate PMI set, in each iteration out of a set of iterations based on residual CSI estimations left from previous iterations. This relates to both Embodiments A and B.

In some embodiments the request for PMI reporting further indicates a required MSE level. This relates to some Embodiments B.

Action 303

The UE 120 receives a CSI RS from the BS 110. The CSI RS is received in the DL channel, to be used by the UE 120 as a basis for the PMI reporting iterations. The estimating of the CSI in the DL channel for the PMI reporting iterations may in some embodiments further comprise to store the residual CSI estimations and reuse the residual CSI estimations for each new iteration during the one or more PMI reporting iterations. This relates to both Embodiments A and B.

Action 304

The UE 120 estimates the CSI in the DL channel for the PMI reporting iterations, based on the CSI RS according to the request. This relates to both Embodiments A and B.

Action 305

The UE 120 sends the PMI reporting iterations to the BS 110. The PMI reporting iterations are according to the CSI estimations in the DL channel. This relates to both Embodiments A and B.

A Embodiments: In examples of the A Embodiments the estimating of the CSI in the DL channel for the PMI reporting iterations, based on the CSI RS according to the request in Action 304 comprises Actions 304 A-1, 304 A-3 and 304 A-4 below. Further, the sending of the PMI reporting iterations according to the estimated CSI in the DL channel to the BS 110, in Action 305 comprises Actions 305 A-2 and 305 A-5 below. The

Actions

304 and 305 may comprise one or more of the following actions:

The UE 120 estimates 304 A-1 the CSI in the DL channel for a first PMI report relating to a first iteration. The UE 120 further obtains an associated MSE of the estimated CSI. The UE 120 then sends 305 A-2 to the BS 110, the first PMI report relating to the first iteration. The first PMI report comprises the obtained MSE of the estimated CSI. The UE 120 receives 304 A-3 a subsequent PMI reporting request from the BS 110. The subsequent PMI reporting request indicates a number of further PMI reporting iterations that is left, based on the first PMI report. The UE 120 estimates 304 A-4 the CSI in the DL channel for one or more subsequent PMI reporting iterations relating to the indicated number of further iterations that is left. The UE 120 then sends 305 A-5 to the BS 110, the one or more subsequent PMI reporting iterations relating to the decided number of further iterations that is left. The subsequent PMI reporting may also comprise MSE. The A Embodiments will be further described below.

An example scenario of A Embodiments related to the UE side may comprise the following: When the UE 120 accesses to the RAN, it may report its capability to the BS 110 so that the BS 110 is able to send out the request to it accordingly. When the UE 120 receives the PMI and CSI RS signals, it starts the 1st loop of algorithm calculation, e.g. OMP calculation. The UE 120 will perform the iterations according to the number of iterations M ₁ in PMI request. When the UE 120 finishes the number of iterations, it reports the PMI and MSE level to the BS 110 and waits for the further request.

If the UE 120 receives a request for another loop, it should continue the iterations with the new number of M _j (j=2, 3, …) , and report the PMI and MSE for the new loop.

If the UE 120 receives a stop indicator or it doesn’ t receive request in a certain time, it may exit the whole process.

B Embodiments: In examples of the B Embodiments the request for PMI reporting further indicates the required MSE level. Further in the B Embodiments, the estimating of the CSI in the DL channel for the PMI reporting iterations, based on the CSI RS according to the request in Action 304 comprises Actions 304 B-1, 304 B-2, and 304 B-3 below. Further, the sending of the PMI reporting iterations according to the estimated CSI in the DL channel to the BS 110, in Action 305 comprises Action 305 B-4 below. The

Actions

304 and 305 may comprise one or more of the following actions:

The UE 120 calculates 304 B-1 a number of iterations that will be used for the PMI reporting. The number of iterations is calculated based on the indicated required MSE level. The UE 120 sends 304 B-2 an indication to the BS 110, indicating the calculated number of iterations that will be used for the PMI reporting. The UE 120 receives 304 B-3 a grant to send the PMI reporting from the BS 110. The grant is for sending the PMI reporting comprising the indicated number of iterations and scheduling information for the indicated number of iterations. The UE 120 then sends 305 B-4 the PMI reporting according to the indicated number of iterations to the BS 110. The PMI reporting iterations are sent according to any one out of: at the same time or iteratively. The B Embodiments will be further described below.

An example scenario of a B Embodiment related to the UE side may comprise the following: The UE 120 finishes all the iterations of CSI calculation according to required MSE level. Then it reports the number of iterations M to the BS 110. It reports single or multiple sets of PMI according to the BS 110 scheduling.

Embodiments herein such as the embodiments mentioned above will now be further described and exemplified. The text below is applicable to and may be combined with any suitable embodiment described above.

Embodiments of the methods herein overcome the issue that restrains the highly accurate PMI report in current standardization. Exemplary embodiments of the methods e.g. comprise:

An iterative PMI reporting based on the algorithm such as e.g. the OMP algorithm.

A customized number of iterations, e.g. OMP iterations according to the BS 110 requirements.

A customized number of PMI reporting loops according to the BS 110 requirements.

A method for the UE 120 to perform the algorithm such as e.g. the OMP algorithm calculation for different iterations.

A method for the BS 110 to perform CSI reconstruction according to different iterations and loops.

A method for the BS 110 to estimate CSI accuracy based on MSE from the UE 120.

Signaling of UE capability for supporting the algorithm such as e.g. the OMP algorithm.

Signaling of algorithm enabler such as e.g. the OMP algorithm enabler.

Signaling for iterative algorithm calculation such as e.g. the OMP algorithm calculation and PMI reporting.

Brief description of the A Embodiments

Step 1. The BS 110 receives the capability data from the UE 120.

Step 2. The BS 110 sends the PMI report request.

Step 3. The BS 110 sends the CSI RS signals.

Step 4. The UE 120 performs calculations by such as the OMP algorithm and sends PMI reporting iterations

Step 5. BS 110 estimates the CSI accuracy

Step 6. The BS 110 reconstructs DL CSI

These steps will be described more in detail below.

Figure 4 illustrates an example of the overall procedures of the A embodiments comprising the following actions:

401. The BS 110 receives the capability data from UE 120. This relates to and may be combined with Step 1 and

Actions

201 and 301.

402. In some embodiments, the BS 110 triggers DL CSI acquisition.

403. The BS 110 sends the PMI report request. This relates to and may be combined with Step 2 and

Actions

202 and 302.

404. The BS 110 sends the CSI RS signals. This relates to and may be combined with Step 3 and Actions 203 and 303.

405, 406. The UE 120 performs calculations according to the algorithm and sends PMI reporting for the first iteration. This relates to and may be combined with Step 4 and Actions 204 A-1, A-2, and A-3 and 304 A-1, 305 A-2.

407. The BS 110 estimates CSI accuracy. This relates to and may be combined with Step 5 and Action 204 A-2.

408. The BS 110 sends a second request to the UE 120 for the remaining iterations. This relates to and may be combined with Step 2 and Actions 204 A-3 and 304 A-3.

409, 410. The UE 120 performs calculations by the algorithm such as the OMP algorithm and sends PMI reporting for the remaining iterations. This relates to and may be combined with Step 4 and Action 304 A-4 and 305 A-5.

411. The BS 110 reconstructs DL CSI. This relates to and may be combined with Step 6 and Action 205.

Detailed Procedures of examples of the A Embodiments:

Step 1. UE 120 capability data.

The BS 110 receives the capability data, also referred to as capability data, from the UE 120.

The capability data indicates whether or not the UE 120 supports the algorithm, e.g. the OMP algorithm. It may also include the number of iterations that are supported by the UE 120.

Step 2. The BS 110 sends the PMI report request to the UE 120.

There are three new fields in the csi-ReportConfig message according to embodiments herein that may be sent to the UE 120:

- A field to enable CSI estimations with the algorithm such as e.g. the OMP algorithm, e.g. 1 or 0.

- A field for an index of the iteration, also referred to as the loop, referred to as j.

- A field for the number of iterations of the algorithm, such as e.g. the OMP algorithm, referred to as M _j.

Step 3. The BS 110 sends the CSI RS signals to the UE 120.

Step 4. The UE iteratively calculates the DL CSI feedback for loop j, starts from 1.

If j=1.

The UE 120 performs the algorithm calculation such as e.g. the OMP algorithm calculation based on the subset number of iterations M _j. It should be noted that the number of iterations corresponds to the number of PMIs to be reported.

For iteration i, i starts from 1

if i≤M _j, the UE 120 calculates the PMI p _i and amplitude &phase coefficients a _i and φ _i, where p _i is the index of the beam.

if i>M _j, the UE 120 stops the algorithm calculation such as e.g. the OMP algorithm calculation and feeds back the P ₁, A ₁, Φ ₁ to the BS 110. P ₁, A ₁, Φ ₁ are vectors as below. Together with PMI, the UE 120 also may send the MSE MSE _j back to the BS 110. An example of using MSE is provided below as defined in Table 1Table 1.

wherein j=1

Bits	00	01	10	11
MSE	＞-20dB	-20 to -30 dB	-30 to -40 dB	＜-40dB

Table 1 Residual Error Example

This is applied to all iterations. The MSE may be calculated as below. H is the actual CSI estimations.

is the CSI estimations up to a certain number of iterations. ‖·‖ ₂ denotes the l ₂-norm of a vector.

If j>1

The UE 120 continues the algorithm such as e.g. the OMP algorithm based on the subset number of iterations M _j.

For iteration i, i starts from

if

the UE 120 calculates the PMI p _i and amplitude &phase coefficients a _i and φ _i.

if

the UE 120 stops the algorithm calculation, such as e.g. the OMP algorithm calculation, and feeds back the P _j, A _j, φ _j to BS. P _j, A _j, φ _j are vectors as below. The UE 120 may also send the residual CSI error MSE _j back to the BS 110.

Step 5 The BS 110 receives the subset of PMIs and estimate of the CSI accuracy.

There may be different requirements on CSI accuracy for different purpose. For e.g. antenna calibration, the BS 110 may need the MSE level to be in -30 to -40 dB.

If MSE _j is within the required MSE level, the BS 110 may send an indicator to the UE 120 for stop. Another option is that the UE 120 may stop if no indicator is received.

If MSE _j doesn’t achieve the required level, the BS 110 sends an indicator to the UE 120 to start a continuous loop j+1. Please note that M _j+1 may be different from M _j. In this case, Step 4-6 would be repeated. As a typical example, an AC error may be relatively large if this is the initial calibration. In this case, the BS 110 and the UE 120 may need more loops to achieve the required MSE level. Otherwise, the number of loops and iterations can be much fewer.

In this way, the BS 110 may control the UE 120 computation load and overhead according to its requirement.

Step 6 BS reconstructs the DL CSI

The DL CSI H may be calculated as below. P ^BS, A ^BS, φ ^BS are the PMI, amplitude &phase coefficients received in the BS 110 for single or multiple loops. c _i is a complex number which is constructed by amplitude &phase coefficients. W _pi is the codebook precoding matrix defined in 3GPP TS38.214.

M ₁+...+M _j

c _i=a _i*φ _i

Where P is codebook index.

Brief description of B Embodiments

The provided B Embodiments provide a further reduction of overhead. Comparing with the A Embodiments, there are differences in Step 2, 4, 5 (underlined below) for the B Embodiments.

Step 1. The BS 110 receives the capability data from the UE 120.

Step 2. The BS 110 sends the PMI report request and the required MSE level to the UE 120.

Step 3. The BS 110 sends the CSI RS signals.

Step 4. UE 120 performs the algorithm calculations, such as OMP calculations.

Step 5. UE 120 performs iterative PMI reporting.

Step 6. The BS 110 performs DL CSI reconstruction.

Figure 5 illustrates an example of the overall procedures of the B Embodiments comprising the following actions:

501. The UE 120 sends its capability data to the BS 110. This relates to and may be combined with Step 1 and

Actions

201 and 301.

502. The BS 110 triggers DL CSI acquisition.

503. The BS 110 sends the PMI report request and the required MSE level to the UE 120. This relates to and may be combined with Step 2 and

Actions

202 and 302.

504. The BS 110 sends the CSI RS signals. This relates to and may be combined with Step 3 and Actions 203 and 303.

505. The UE 120 performs PMI calculations based on requested MSE level. This relates to and may be combined with Step 4 and Action 304 B-1.

506. The UE 120 reports the number of iterations M. This relates to and may be combined with Step 5 and Actions 204 B-1 and 304 B-2.

507. The BS 110 schedules UL resources according to the reported the number of iterations M. This relates to and may be combined with Step 5 and Action 304 B-2.

508. The BS 110 sends an UL grant for single and/or multiple PMI reporting. This relates to and may be combined with Step 5 and Actions 204 B-2 and 304 B-3.

509. The UE 120 sends iteratively PMI reporting. This relates to and may be combined with Step 5 and Actions 204 B-3 and 305 B-4.

510. PMI report for 1st set. This relates to and may be combined with Step 5 and Actions 204 B-3 and 305 B-4.

511. PMI report for 2nd set. This relates to and may be combined with Step 5 and Actions 204 B-3 and 305 B-4.

512. The BS 110 performs DL CSI reconstruction. This relates to and may be combined with Step 6 and Action 205.

Detailed Procedures of examples of the B Embodiments:

Only the updated steps 3, 5 and 6 are described in this section.

Step 2. The BS 110 sends apart from the PMI report request, also the required MSE level to the UE 120.

Some new fields in the csi-ReportConfig message may e.g. be provided according to some embodiments herein to be sent to the UE 120.

A field to enable CSI Estimations with the algorithm, such as e.g. the OMP algorithm, 1 or 0.

A field to indicate the required MSE levels. An example is shown in Table 1 above.

Step 4 The UE 120 calculates the DL CSI according to the required MSE level.

In this step the UE 120 calculates all the PMIs with the algorithm, e.g. the OMP, with M iterations. Here M is determined by the UE 120 to achieve the required MSE level. P ^UE, A ^UE, Φ ^UE are the PMI, amplitude &phase coefficients calculated by the UE 120 as below.

P ^UE= [p ₁, …, p _M]

A ^UE= [a ₁, …, a _M]

Step 5. UE iterative PMI reporting

Then the UE 120 reports the M to the BS 110 for a grant on UL resource to transmit the P ^UE, A ^UE, Φ ^UE. These PMIs may be fed back by single time or iteratively, depending on the BS UL resource and scheduling. The BS 110 will perform an evaluation according to M.

As an example mentioned above, M may be larger during initial calibration so more UL overhead is needed. Otherwise the less UL overhead is needed.

To perform the method actions above, the BS 110 is configured to handle PMI reporting from the UE 120 in the wireless communications network 100. The PMI reporting is adapted to relate to reporting CSI estimations of a DL channel.

The BS 110 may comprise an arrangement depicted in Figures 6a and 6b. The BS 110 may comprise an input and output interface 600 configured to communicate in the wireless communications network 100, e.g., with the UE 120. The input and output interface 600 may comprise a wireless receiver (not shown) and a wireless transmitter (not shown) .

The BS 110 is further configured to, e.g. by means of a sending unit 601 in the BS 110, send a request to the UE 120, requesting PMI reporting to be provided by one or more PMI reporting iterations. The one or more PMI reporting iterations are to be requested to comprise iterative reports of CSI estimations of the DL channel, based on an algorithm. The algorithm is adapted to be represented by a residual PMI selection algorithm. The algorithm may be adapted to be related to selecting a PMI in a candidate PMI set, in each iteration out of a set of iterations based on residual CSI estimations left from previous iterations.

The BS 110 is further configured to, e.g. by means of the sending unit 601 in the BS 110, send a CSI RS, in the DL channel, to be used by the UE 120 as a basis for the PMI reporting iterations.

The BS 110 is further configured to, e.g. by means of a receiving unit 602 in the BS 110, receive from the UE 120, PMI reporting iterations according to the request and based on the sent CSI RS.

In some of the A embodiments, the BS 110 may further be configured to, e.g. by means of the receiving unit 602 in the BS 110, receive from the UE 120, PMI reporting iterations according to the request and based on the sent CSI reference signals by:

- receiving from the UE 120, a first PMI report relating to a first iteration, indicating an associated Mean Squared Error, MSE, of the CSI estimations,

- deciding a number of further PMI reporting iterations that is left based on the first PMI report,

- sending to the UE 120, a subsequent PMI reporting request indicating the decided number of further PMI reporting iterations that is left, and

- receiving from the UE 120, one or more subsequent PMI reporting iterations relating to the decided number of further iterations that is left.

In some of the B embodiments, the request for PMI reporting is further adapted to comprise a required Mean Squared Error, MSE, level, and the BS 110 may further be configured to, e.g. by means of the receiving unit 602 in the BS 110, receive from the UE 120, the PMI reporting iterations according to the request and based on the sent CSI reference signals by:

- receiving an indication from the UE 120, indicating a number of iterations that will be used for the PMI reporting, calculated based on the required MSE level,

- sending to the UE 120, a grant to send the PMI reporting comprising the indicated number of iterations and scheduling information for the indicated number of iterations, and

- receiving from the UE 120, the PMI reporting according to the indicated number of iterations, wherein the PMI reporting iterations are adapted to be received according to any one out of: at the same time or iteratively.

The BS 110 may further be configured to, e.g. by means of an obtaining unit 603 in the BS 110, obtain capability data from the UE 120. The capability data is adapted to indicate that the UE 120 is capable of performing the PMI reporting and supporting the algorithm. The capability data may further be adapted to indicate a number of iterations that is supported by the UE 120.

The BS 110 may further be configured to, e.g. by means of a triggering unit 604 in the BS 110, trigger DL CSI estimations related to the DL channel.

The BS 110 may further be configured to, e.g. by means of a reconstructing unit 605 in the BS 110, reconstruct DL CSI related to the DL channel, based on the received PMI reporting iterations.

To perform the method actions above, the UE 120 is configured to handle PMI reporting to the BS 110 in the wireless communications network 100. The PMI reporting is adapted to relate to reporting CSI estimations of a DL channel.

The UE 120 may comprise an arrangement depicted in Figures 7a and 7b. The UE 120 may comprise an input and output interface 700 configured to communicate in the wireless communications network 100, e.g., with the BS 110. The input and output interface 700 may comprise a wireless receiver not shown and a wireless transmitter not shown.

The UE 120 is further configured to, e.g. by means of a receiving unit 701 in the network node 110, receive a request from the BS 110, requesting PMI reporting to be provided by one or more PMI reporting iterations. The one or more PMI reporting iterations are adapted to be requested to comprise iterative reports of CSI estimations of the DL channel, based on an algorithm. The algorithm is adapted to be represented by a residual PMI selection algorithm. The algorithm may be adapted to relate to selecting a PMI in a candidate PMI set, in each iteration out of a set of iterations based on residual CSI estimations left from previous iterations.

The UE 120 is further configured to, e.g. by means of the receiving unit 701 in the network node 110, receive from the BS 110, a CSI RS in the DL channel, to be used by the UE 120 as a basis for the PMI reporting iterations.

The UE 120 is further configured to, e.g. by means of an estimating unit 702 in the network node 110, estimate the CSI in the DL channel for the PMI reporting iterations based on the CSI RS according to the request.

The UE 120 may further be configured to, e.g., by means of the estimating unit 702 in the network node 110, estimate the CSI in the DL channel for the PMI reporting iterations by further store the residual CSI estimations and reuse the residual CSI estimations for each new iteration during the one or more PMI reporting iterations.

The UE 120 is further configured to, e.g. by means of the sending unit 703 in the network node 110, send to the BS 110, the PMI reporting iterations according to the estimated CSI in the DL channel.

In some of the A embodiments, the UE 120 may further be configured to, e.g. by means of the estimating unit 702 in the BS 110, estimate the CSI in the DL channel for the PMI reporting iterations, based on the CSI RS according to the request, and e.g. by means of the sending unit 703 in the network node 110, send to the BS 110, the PMI reporting iterations according to the estimated CSI in the DL channel, by:

- estimating the CSI in the DL channel for a first PMI report relating to a first iteration and obtaining an associated Mean Squared Error, MSE, of the estimated CSI,

- sending to the BS 110, the first PMI report relating to the first iteration, comprising the obtained MSE of the estimated CSI,

- receiving from the BS 110, a subsequent PMI reporting request indicating a number of further PMI reporting iterations that is left, based on the first PMI report,

- estimating the CSI in the DL channel for one or more subsequent PMI reporting iterations relating to the indicated number of further iterations that is left, and

- sending to the BS 110, the one or more subsequent PMI reporting iterations relating to the decided number of further iterations that is left.

In some of the B embodiments, the request for PMI reporting is further adapted to indicate a required MSE level, and the UE 120 may further be configured to, e.g. by means of the estimating unit 702 in the BS 110, estimate the CSI in the DL channel for the PMI reporting iterations, based on the CSI RS according to the request, and e.g. by means of the sending unit 703 in the network node 110, send to the BS 110, the PMI reporting iterations according to the estimated CSI in the DL channel, by:

- calculating a number of iterations that will be used for the PMI reporting, calculated based on the indicated required MSE level,

- sending an indication to the BS 110, indicating the calculated number of iterations that will be used for the PMI reporting,

- receiving from the BS 110, a grant to send the PMI reporting comprising the indicated number of iterations and scheduling information for the indicated number of iterations, and

- sending to the BS 110, the PMI reporting according to the indicated number of iterations, wherein the PMI reporting iterations are sent according to any one out of: at the same time or iteratively.

The UE 120 may further be configured to, e.g. by means of the sending unit 703 in the network node 110, send capability data To the BS 110, which capability data is adapted to indicate that the UE 120 is capable of the PMI reporting and supporting the algorithm. 30 The capability data may further be adapted to indicate a number of iterations that is supported by the UE 120.

The embodiments herein may be implemented through a respective processor or one or more processors, such as the respective processor 660 of a processing circuitry in the BS 110 depicted in Figure 6a, and processor 760 of a processing circuitry in the UE 120 depicted in Figure 7a together with respective computer program code for performing the functions and actions of the embodiments herein. The program code mentioned above may also be provided as a computer program product, for instance in the form of a data carrier carrying computer program code for performing the embodiments herein when being loaded into the respective BS 110 and UE 120. One such carrier may be in the form of a CD ROM disc. It is however feasible with other data carriers such as a memory stick. The computer program code may furthermore be provided as pure program code on a server and downloaded to the respective BS 110 and UE 120.

The BS 110 and UE 120 may further comprise a respective memory 670 and memory 770 comprising one or more memory units. The respective memory 670 and memory 770 comprises instructions executable by the processor in network node 110. The memory 670 is arranged to be used to store e.g., information, indications, data, configurations, iterations, communication data, and applications to perform the methods herein when being executed in the respective BS 110 and UE 120.

In some embodiments, a respective computer program 680 and computer program 780 comprises instructions, which when executed by the respective at least one processor 660 and processor 670, cause the at least one processor of respective BS 110 and UE 120 to perform the actions above.

In some embodiments, a respective carrier 690 and carrier 790 comprises the respective computer program 680 and computer program 780, wherein the respective carrier 690 and carrier 790 is one of an electronic signal, an optical signal, an electromagnetic signal, a magnetic signal, an electric signal, a radio signal, a microwave signal, or a computer-readable storage medium.

Those skilled in the art will appreciate that the units in the respective BS 110 and UE 120 described above may refer to a combination of analog and digital circuits, and/or one or more processors configured with software and/or firmware, e.g. stored in the respective BS 110 and UE 120, that when executed by the respective one or more processors such as the processors described above. One or more of these processors, as well as the other digital hardware, may be included in a single Application-Specific Integrated Circuitry ASIC, or several processors and various digital hardware may be distributed among several separate components, whether individually packaged or assembled into a System-on-a-Chip (SoC) .

With reference to Figure 8, in accordance with an embodiment, a communication system includes a telecommunication network 3210, such as a 3GPP-type cellular network, e.g. wireless communications network 100, which comprises an access network 3211, such as a radio access network, and a core network 3214. The access network 3211 comprises a plurality of

base stations

3212a, 3212b, 3212c, e.g., the BS 110, such as AP STAs NBs, eNBs, gNBs or other types of wireless access points, each defining a

corresponding coverage area

3213a, 3213b, 3213c. Each

base station

3212a, 3212b, 3212c, e.g. radio network nodes 141, 142, is connectable to the core network 3214 over a wired or wireless connection 3215. A first user equipment (UE) , e.g. the UE 120, such as a Non-AP STA 3291 located in coverage area 3213c is configured to wirelessly connect to, or be paged by, the corresponding base station 3212c, e.g., the network node 110. A second UE 3292, e.g., any of the one or more second UEs 122, such as a Non-AP STA in coverage area 3213a is wirelessly connectable to the corresponding base station 3212a, e.g., the network node 110. While a plurality of

UEs

3291, 3292 are illustrated in this example, the disclosed embodiments are equally applicable to a situation where a sole UE is in the coverage area or where a sole UE is connecting to the corresponding base station 3212.

The telecommunication network 3210 is itself connected to a host computer 3230, which may be embodied in the hardware and/or software of a standalone server, a cloud-implemented server, a distributed server or as processing resources in a server farm. The host computer 3230 may be under the ownership or control of a service provider, or may be operated by the service provider or on behalf of the service provider. The

connections

3221, 3222 between the telecommunication network 3210 and the host computer 3230 may extend directly from the core network 3214 to the host computer 3230 or may go via an optional intermediate network 3220. The intermediate network 3220 may be one of, or a combination of more than one of, a public, private or hosted network; the intermediate network 3220, if any, may be a backbone network or the Internet; in particular, the intermediate network 3220 may comprise two or more sub-networks (not shown) .

The communication system of Figure 8 as a whole enables connectivity between one of the connected

UEs

3291, 3292 and the host computer 3230. The connectivity may be described as an over-the-top (OTT) connection 3250. The host computer 3230 and the connected

UEs

3291, 3292 are configured to communicate data and/or signaling via the OTT connection 3250, using the access network 3211, the core network 3214, any intermediate network 3220 and possible further infrastructure (not shown) as intermediaries. The OTT connection 3250 may be transparent in the sense that the participating communication devices through which the OTT connection 3250 passes are unaware of routing of uplink and downlink communications. For example, a base station 3212 may not or need not be informed about the past routing of an incoming downlink communication with data originating from a host computer 3230 to be forwarded (e.g., handed over) to a connected UE 3291. Similarly, the base station 3212 need not be aware of the future routing of an outgoing uplink communication originating from the UE 3291 towards the host computer 3230.

Example implementations, in accordance with an embodiment, of the UE, base station and host computer discussed in the preceding paragraphs will now be described with reference to Figure 9. In a communication system 3300, a host computer 3310 comprises hardware 3315 including a communication interface 3316 configured to set up and maintain a wired or wireless connection with an interface of a different communication device of the communication system 3300. The host computer 3310 further comprises processing circuitry 3318, which may have storage and/or processing capabilities. In particular, the processing circuitry 3318 may comprise one or more programmable processors, application-specific integrated circuits, field programmable gate arrays or combinations of these (not shown) adapted to execute instructions. The host computer 3310 further comprises software 3311, which is stored in or accessible by the host computer 3310 and executable by the processing circuitry 3318. The software 3311 includes a host application 3312. The host application 3312 may be operable to provide a service to a remote user, such as a UE 3330 connecting via an OTT connection 3350 terminating at the UE 3330 and the host computer 3310. In providing the service to the remote user, the host application 3312 may provide user data which is transmitted using the OTT connection 3350.

The communication system 3300 further includes a base station 3320 provided in a telecommunication system and comprising hardware 3325 enabling it to communicate with the host computer 3310 and with the UE 3330. The hardware 3325 may include a communication interface 3326 for setting up and maintaining a wired or wireless connection with an interface of a different communication device of the communication system 3300, as well as a radio interface 3327 for setting up and maintaining at least a wireless connection 3370 with a UE 3330 located in a coverage area (not shown in Figure 9) served by the base station 3320. The communication interface 3326 may be configured to facilitate a connection 3360 to the host computer 3310. The connection 3360 may be direct or it may pass through a core network (not shown in Figure 9) of the telecommunication system and/or through one or more intermediate networks outside the telecommunication system. In the embodiment shown, the hardware 3325 of the base station 3320 further includes processing circuitry 3328, which may comprise one or more programmable processors, application-specific integrated circuits, field programmable gate arrays or combinations of these (not shown) adapted to execute instructions. The base station 3320 further has software 3321 stored internally or accessible via an external connection.

The communication system 3300 further includes the UE 3330 already referred to. Its hardware 3335 may include a radio interface 3337 configured to set up and maintain a wireless connection 3370 with a base station serving a coverage area in which the UE 3330 is currently located. The hardware 3335 of the UE 3330 further includes processing circuitry 3338, which may comprise one or more programmable processors, application-specific integrated circuits, field programmable gate arrays or combinations of these (not shown) adapted to execute instructions. The UE 3330 further comprises software 3331, which is stored in or accessible by the UE 3330 and executable by the processing circuitry 3338. The software 3331 includes a client application 3332. The client application 3332 may be operable to provide a service to a human or non-human user via the UE 3330, with the support of the host computer 3310. In the host computer 3310, an executing host application 3312 may communicate with the executing client application 3332 via the OTT connection 3350 terminating at the UE 3330 and the host computer 3310. In providing the service to the user, the client application 3332 may receive request data from the host application 3312 and provide user data in response to the request data. The OTT connection 3350 may transfer both the request data and the user data. The client application 3332 may interact with the user to generate the user data that it provides.

It is noted that the host computer 3310, base station 3320 and UE 3330 illustrated in Figure 8 may be identical to the host computer 3230, one of the

base stations

3212a, 3212b, 3212c and one of the

UEs

3291, 3292 of Figure 8, respectively. This is to say, the inner workings of these entities may be as shown in Figure 9 and independently, the surrounding network topology may be that of Figure 8.

In Figure 9, the OTT connection 3350 has been drawn abstractly to illustrate the communication between the host computer 3310 and the use equipment 3330 via the base station 3320, without explicit reference to any intermediary devices and the precise routing of messages via these devices. Network infrastructure may determine the routing, which it may be configured to hide from the UE 3330 or from the service provider operating the host computer 3310, or both. While the OTT connection 3350 is active, the network infrastructure may further take decisions by which it dynamically changes the routing (e.g., on the basis of load balancing consideration or reconfiguration of the network) .

The wireless connection 3370 between the UE 3330 and the base station 3320 is in accordance with the teachings of the embodiments described throughout this disclosure. One or more of the various embodiments improve the performance of OTT services provided to the UE 3330 using the OTT connection 3350, in which the wireless connection 3370 forms the last segment. More precisely, the teachings of these embodiments may improve the RAN effect: data rate, latency, power consumption and thereby provide benefits such as e.g. the applicable corresponding effect on the OTT service: reduced user waiting time, relaxed restriction on file size, better responsiveness, extended battery lifetime.

A measurement procedure may be provided for the purpose of monitoring data rate, latency and other factors on which the one or more embodiments improve. There may further be an optional network functionality for reconfiguring the OTT connection 3350 between the host computer 3310 and UE 3330, in response to variations in the measurement results. The measurement procedure and/or the network functionality for reconfiguring the OTT connection 3350 may be implemented in the software 3311 of the host computer 3310 or in the software 3331 of the UE 3330, or both. In embodiments, sensors (not shown) may be deployed in or in association with communication devices through which the OTT connection 3350 passes; the sensors may participate in the measurement procedure by supplying values of the monitored quantities exemplified above, or supplying values of other physical quantities from which

software

3311, 3331 may compute or estimate the monitored quantities. The reconfiguring of the OTT connection 3350 may include message format, retransmission settings, preferred routing etc. ; the reconfiguring need not affect the base station 3320, and it may be unknown or imperceptible to the base station 3320. Such procedures and functionalities may be known and practiced in the art. In certain embodiments, measurements may involve proprietary UE signaling facilitating the host computer’s 3310 measurements of throughput, propagation times, latency and the like. The measurements may be implemented in that the

software

3311, 3331 causes messages to be transmitted, in particular empty or ‘dummy’ messages, using the OTT connection 3350 while it monitors propagation times, errors etc.

Figure 10 is a flowchart illustrating a method implemented in a communication system, in accordance with one embodiment. The communication system includes a host computer, a base station such as an AP STA, and a UE such as a Non-AP STA which may be those described with reference to Figure 8 and Figure 9. For simplicity of the present disclosure, only drawing references to Figure 10 will be included in this section. In a first Step 2410 of the method, the host computer provides user data. In an optional sub Step 2411 of the first Step 2410, the host computer provides the user data by executing a host application. In a second Step 2420, the host computer initiates a transmission carrying the user data to the UE. In an optional third Step 2430, the base station transmits to the UE the user data which was carried in the transmission that the host computer initiated, in accordance with the teachings of the embodiments described throughout this disclosure. In an optional fourth Step 2440, the UE executes a client application associated with the host application executed by the host computer.

Figure 11 is a flowchart illustrating a method implemented in a communication system, in accordance with one embodiment. The communication system includes a host computer, a base station such as an AP STA, and a UE such as a Non-AP STA which may be those described with reference to Figure 8 and Figure 9. For simplicity of the present disclosure, only drawing references to Figure 11 will be included in this section. In a first Step 2510 of the method, the host computer provides user data. In an optional sub step (not shown) the host computer provides the user data by executing a host application. In a second Step 2520, the host computer initiates a transmission carrying the user data to the UE. The transmission may pass via the base station, in accordance with the teachings of the embodiments described throughout this disclosure. In an optional third Step 2530, the UE receives the user data carried in the transmission.

Figure 12 is a flowchart illustrating a method implemented in a communication system, in accordance with one embodiment. The communication system includes a host computer, a base station such as an AP STA, and a UE such as a Non-AP STA which may be those described with reference to Figure 8 and Figure 9. For simplicity of the present disclosure, only drawing references to Figure 12 will be included in this section. In an optional first Step 2610 of the method, the UE receives input data provided by the host computer. Additionally or alternatively, in an optional second Step 2620, the UE provides user data. In an optional sub Step 2621 of the second Step 2620, the UE provides the user data by executing a client application. In a further optional sub Step 2611 of the first Step 2610, the UE executes a client application which provides the user data in reaction to the received input data provided by the host computer. In providing the user data, the executed client application may further consider user input received from the user. Regardless of the specific manner in which the user data was provided, the UE initiates, in an optional third sub Step 2630, transmission of the user data to the host computer. In a fourth Step 2640 of the method, the host computer receives the user data transmitted from the UE, in accordance with the teachings of the embodiments described throughout this disclosure.

Figure 13 is a flowchart illustrating a method implemented in a communication system, in accordance with one embodiment. The communication system includes a host computer, a base station such as an AP STA, and a UE such as a Non-AP STA which may be those described with reference to Figure 8 and Figure 9. For simplicity of the present disclosure, only drawing references to Figure 13 will be included in this section. In an optional first Step 2710 of the method, in accordance with the teachings of the embodiments described throughout this disclosure, the base station receives user data from the UE. In an optional second Step 2720, the base station initiates transmission of the received user data to the host computer. In a third Step 2730, the host computer receives the user data carried in the transmission initiated by the base station.

When using the word "comprise" or “comprising” it shall be interpreted as non-limiting, i.e. meaning "consist at least of" .

The embodiments herein are not limited to the preferred embodiments described above. Various alternatives, modifications and equivalents may be used.

Abbreviation Explanation

OMP Orthogonal Matching Pursuit

CSI Channel State Information

PMI Precoding Matrix Indicator

AAS Active Antenna System

FDD Frequency Division Duplex

TDD Time Division Duplex

AC Antenna Calibration

DL Downlink

UL Uplink

OTA Over-the-air

LOS Line-of-sight

NLOS None-line-of-sight

BS Base Station

UE User Equipment

TX Transmitter

RX Receiver

RS Reference Signal

MLE Maximum Likelihood Estimator

AoD Azimuth of Departure

ZoD Zenith of Departure

NMSE Normalized Mean Squared Error

WB Wideband

SB Subband

Claims

A method performed by a Base Station, BS, (110) for handling Precoding Matrix Indicator, PMI, reporting from a User Equipment, UE, (120) in a wireless communications network (100) , which PMI reporting relates to reporting Channel State Information, CSI, estimations of a Downlink, DL, channel, the method comprising:

sending (202 AB) a request to the UE (120) , requesting PMI reporting to be provided by one or more PMI reporting iterations,

where the one or more PMI reporting iterations are requested to comprise iterative reports of CSI estimations of the DL channel, based on an algorithm, which algorithm is represented by a residual PMI selection algorithm,

sending (203 AB) a CSI Reference Signal, RS, in the DL channel, to be used by the UE (120) as a basis for the PMI reporting iterations,

receiving (204 AB) from the UE (120) , PMI reporting iterations according to the request and based on the sent CSI RS.
The method according to claim 1, wherein the algorithm relates to selecting a PMI in a candidate PMI set, in each iteration out of a set of iterations based on residual CSI estimations left from previous iterations.
The method according to any of the claims 1-2, wherein the receiving (204 AB) from the UE (120) , PMI reporting iterations according to the request and based on the sent CSI reference signals is performed by:

receiving (204 A-1) from the UE (120) , a first PMI report relating to a first iteration, indicating an associated Mean Squared Error, MSE, of the CSI estimations,

deciding (204 A-2) a number of further PMI reporting iterations that is left based on the first PMI report,

sending (204 A-3) to the UE (120) , a subsequent PMI reporting request indicating the decided number of further PMI reporting iterations that is left,

receiving (204 A-4) from the UE (120) , one or more subsequent PMI reporting iterations relating to the decided number of further iterations that is left.
The method according to any of the claims 1-2, wherein the request for PMI reporting further comprises a required Mean Squared Error, MSE, level, and wherein the receiving (204 AB) from the UE (120) , of the PMI reporting iterations according to the request and based on the sent CSI reference signals is performed by:

receiving (204 B-1) an indication from the UE (120) , indicating a number of iterations that will be used for the PMI reporting, calculated based on the required MSE level,

sending (204 B-2) to the UE (120) , a grant to send the PMI reporting comprising the indicated number of iterations and scheduling information for the indicated number of iterations, and

receiving (204 B-3) from the UE (120) , the PMI reporting according to the indicated number of iterations, wherein the PMI reporting iterations are received according to any one out of: at the same time or iteratively.
The method according to any of the claims 1-4, further comprising any one or more out of:

obtaining (201 AB) capability data from the UE (120) , which capability data indicates that the UE (120) is capable of performing the PMI reporting and supporting the algorithm, and

reconstructing (205 AB) DL CSI related to the DL channel, based on the received PMI reporting iterations.
The method according to claim 5, wherein the capability data further indicates a number of iterations that is supported by the UE (120) .
A computer program (680) comprising instructions, which when executed by a processor (660) , causes the processor (660) to perform actions according to any of the claims 1-6.
A carrier (690) comprising the computer program (680) of claim 7, wherein the carrier (690) is one of an electronic signal, an optical signal, an electromagnetic signal, a magnetic signal, an electric signal, a radio signal, a microwave signal, or a computer-readable storage medium.
A method performed by a User Equipment, UE, (120) for handling Precoding Matrix Indicator, PMI, reporting to a Base Station, BS, (110) in a wireless communications network (100) , which PMI reporting relates to reporting Channel State Information, CSI, estimations of a Downlink, DL, channel, the method comprising:

receiving (302 AB) a request from the BS (110) , requesting PMI reporting to be provided by one or more PMI reporting iterations,

where the one or more PMI reporting iterations are requested to comprise iterative reports of CSI estimations of the DL channel, based on an algorithm, which algorithm is represented by a residual PMI selection algorithm,

receiving (303 AB) from the BS (110) , a CSI Reference Signal, RS, in the DL channel, to be used by the UE (120) as a basis for the PMI reporting iterations,

estimating (304 AB) the CSI in the DL channel for the PMI reporting iterations, based on the CSI RS according to the request, and

sending (305 AB) to the BS (110) , the PMI reporting iterations according to the estimated CSI in the DL channel.
The method according to claim 9, wherein the algorithm relates to selecting a PMI in a candidate PMI set, in each iteration out of a set of iterations based on residual CSI estimations left from previous iterations.
The method according to any of the claims 9-10, wherein estimating (303 AB) the CSI in the DL channel for the PMI reporting iterations further comprises:

storing the residual CSI estimations and reusing the residual CSI estimations for each new iteration during the one or more PMI reporting iterations.
The method according to any of the claims 9-11, wherein the estimating (304 AB) the CSI in the DL channel for the PMI reporting iterations, based on the CSI RS according to the request, and the sending (305 AB) to the BS (110) , the PMI reporting iterations according to the estimated CSI in the DL channel, are performed by:

estimating (304 A-1) the CSI in the DL channel for a first PMI report relating to a first iteration and obtaining an associated Mean Squared Error, MSE, of the estimated CSI,

sending (305 A-2) to the BS (110) , the first PMI report relating to the first iteration, comprising the obtained MSE of the estimated CSI,

receiving (304 A-3) from the BS (110) , a subsequent PMI reporting request indicating a number of further PMI reporting iterations that is left, based on the first PMI report,

estimating (304 A-4) the CSI in the DL channel for one or more subsequent PMI reporting iterations relating to the indicated number of further iterations that is left, and

sending (305 A-5) to the BS (110) , the one or more subsequent PMI reporting iterations relating to the decided number of further iterations that is left.
The method according to any of the claims 9-11, wherein the request for PMI reporting further indicates a required Mean Squared Error, MSE, level, and wherein the estimating (304 AB) the CSI in the DL channel for the PMI reporting iterations, based on the CSI RS according to the request, and the sending (305 AB) to the BS (110) , the PMI reporting iterations according to the estimated CSI in the DL channel, are performed by:

calculating (304 B-1) a number of iterations that will be used for the PMI reporting, based on the indicated required MSE level,

sending (304 B-2) an indication to the BS (110) , indicating the calculated number of iterations that will be used for the PMI reporting,

receiving (304 B-3) from the BS (110) , a grant to send the PMI reporting comprising the indicated number of iterations and scheduling information for the indicated number of iterations, and

sending (305 B-4) to the BS (110) , the PMI reporting according to the indicated number of iterations, wherein the PMI reporting iterations are sent according to any one out of: at the same time or iteratively.
The method according to any of the claims 9-13, further comprising:

sending (301 AB) capability data to the BS (110) , which capability data indicates that the UE (120) is capable of the PMI reporting and supporting the algorithm.
The method according to claim 14, wherein the capability data further indicates a number of iterations that is supported by the UE (120) .
A computer program (780) comprising instructions, which when executed by a processor (760) , causes the processor (760) to perform actions according to any of the claims 9-15.
A carrier (790) comprising the computer program (780) of claim 16, wherein the carrier (790) is one of an electronic signal, an optical signal, an electromagnetic signal, a magnetic signal, an electric signal, a radio signal, a microwave signal, or a computer-readable storage medium.
A Base Station, BS, (110) configured to handling Precoding Matrix Indicator, PMI, reporting from a User Equipment, UE, (120) in a wireless communications network (100) , which PMI reporting is adapted to relate to reporting Channel State Information, CSI, estimations of a Downlink, DL, channel, the BS (110) further being configured to:

send a request to the UE (120) , requesting PMI reporting to be provided by one or more PMI reporting iterations,

where the one or more PMI reporting iterations are to be requested to comprise iterative reports of CSI estimations of the DL channel, based on an algorithm, which algorithm is adapted to be represented by a residual PMI selection algorithm,

send a CSI Reference Signal, RS, in the DL channel, to be used by the UE (120) as a basis for the PMI reporting iterations,

receive from the UE (120) , PMI reporting iterations according to the request and based on the sent CSI RS.
The BS (110) according to claim 18, wherein the algorithm is adapted to be related to selecting a PMI in a candidate PMI set, in each iteration out of a set of iterations based on residual CSI estimations left from previous iterations.
The BS (110) according to any of the claims 18-19, further being configured to receive from the UE (120) , PMI reporting iterations according to the request and based on the sent CSI reference signals by:

receiving from the UE (120) , a first PMI report relating to a first iteration, indicating an associated Mean Squared Error, MSE, of the CSI estimations,

deciding a number of further PMI reporting iterations that is left based on the first PMI report,

sending to the UE (120) , a subsequent PMI reporting request indicating the decided number of further PMI reporting iterations that is left,

receiving from the UE (120) , one or more subsequent PMI reporting iterations relating to the decided number of further iterations that is left.
The BS (110) according to any of the claims 18-19, wherein the request for PMI reporting further is adapted to comprise a required Mean Squared Error, MSE, level, and wherein the BS (110) further is configured to receive from the UE (120) , the PMI reporting iterations according to the request and based on the sent CSI reference signals by:

receiving an indication from the UE (120) , indicating a number of iterations that will be used for the PMI reporting, calculated based on the required MSE level,

sending to the UE (120) , a grant to send the PMI reporting comprising the indicated number of iterations and scheduling information for the indicated number of iterations, and

receiving from the UE (120) , the PMI reporting according to the indicated number of iterations, wherein the PMI reporting iterations are adapted to be received according to any one out of: at the same time or iteratively.
The BS (110) according to any of the claims 18-21, further being configured to any one or more out of:

obtain capability data from the UE (120) , which capability data is adapted to indicate that the UE (120) is capable of performing the PMI reporting and supporting the algorithm, and

reconstruct DL CSI related to the DL channel, based on the received PMI reporting iterations.
The BS (110) according to claim 22, wherein the capability data further is adapted to indicate a number of iterations that is supported by the UE (120) .
A User Equipment, UE, (120) configured to handle Precoding Matrix Indicator, PMI, reporting to a Base Station, BS, (110) in a wireless communications network (100) , which PMI reporting is adapted to relate to reporting Channel State Information, CSI, estimations of a Downlink, DL, channel, the UE (120) further being configured to:

receive a request from the BS (110) , requesting PMI reporting to be provided by one or more PMI reporting iterations,

where the one or more PMI reporting iterations are adapted to be requested to comprise iterative reports of CSI estimations of the DL channel, based on an algorithm, which algorithm is adapted to be represented by a residual PMI selection algorithm,

receive from the BS (110) , a CSI Reference Signal, RS, in the DL channel, to be used by the UE (120) as a basis for the PMI reporting iterations,

estimate the CSI in the DL channel for the PMI reporting iterations based on the CSI RS according to the request, and

send to the BS (110) , the PMI reporting iterations according to the estimated CSI in the DL channel.
The UE (120) according to claim 24, wherein the algorithm is adapted to relate to selecting a PMI in a candidate PMI set, in each iteration out of a set of iterations based on residual CSI estimations left from previous iterations.
The UE (120) according to any of the claims 24-25, further being configured to perform the estimating the CSI in the DL channel for the PMI reporting iterations by further store the residual CSI estimations and reuse the residual CSI estimations for each new iteration during the one or more PMI reporting iterations.
The UE (120) according to any of the claims 24-26, further being configured to estimate the CSI in the DL channel for the PMI reporting iterations, based on the CSI RS according to the request, and the send to the BS (110) , the PMI reporting iterations according to the estimated CSI in the DL channel, by:

estimating the CSI in the DL channel for a first PMI report relating to a first iteration and obtaining an associated Mean Squared Error, MSE, of the estimated CSI,

sending to the BS (110) , the first PMI report relating to the first iteration, comprising the obtained MSE of the estimated CSI,

receiving from the BS (110) , a subsequent PMI reporting request indicating a number of further PMI reporting iterations that is left, based on the first PMI report,

estimating the CSI in the DL channel for one or more subsequent PMI reporting iterations relating to the indicated number of further iterations that is left, and

sending to the BS (110) , the one or more subsequent PMI reporting iterations relating to the decided number of further iterations that is left.
The UE (120) according to any of the claims 24-26, wherein the request for PMI reporting further is adapted to indicate a required Mean Squared Error, MSE, level, and wherein the UE (120) further is configured to estimate the CSI in the DL channel for the PMI reporting iterations, based on the CSI RS according to the request, and the send to the BS (110) , the PMI reporting iterations according to the estimated CSI in the DL channel, by:

calculating a number of iterations that will be used for the PMI reporting, based on the indicated required MSE level,

sending an indication to the BS (110) , indicating the calculated number of iterations that will be used for the PMI reporting,

receiving from the BS (110) , a grant to send the PMI reporting comprising the indicated number of iterations and scheduling information for the indicated number of iterations, and

sending to the BS (110) , the PMI reporting according to the indicated number of iterations, wherein the PMI reporting iterations are sent according to any one out of: at the same time or iteratively.
The UE (120) according to any of the claims 24-28, further being configured to:

send capability data To the BS (110) , which capability data is adapted to indicate that the UE (120) is capable of the PMI reporting and supporting the algorithm.
The UE (120) according to claim 29, wherein the capability data further is adapted to indicate a number of iterations that is supported by the UE (120) .