CN111201828A

CN111201828A - System and method for identifying communication nodes

Info

Publication number: CN111201828A
Application number: CN201780095780.4A
Authority: CN
Inventors: 袁志锋; 杨勋; 李卫敏; 胡宇洲; 唐红
Original assignee: ZTE Corp
Current assignee: ZTE Corp
Priority date: 2017-10-12
Filing date: 2017-10-12
Publication date: 2020-05-26
Anticipated expiration: 2037-10-12
Also published as: CN111201828B; WO2019071503A1

Abstract

A system and method for allocating network resources is disclosed herein. In one embodiment, a method performed by a first wireless communication node comprises: receiving a signal comprising a plurality of first spreading symbols; and selecting the first subset from the plurality of preconfigured spreading sequences by: calculating a metric for each of a plurality of preconfigured spreading sequences of the first subset using the signal; processing the signal to identify at least one second wireless communication node based on the first subset of the plurality of preconfigured spreading sequences.

Description

System and method for identifying communication nodes

Technical Field

The present disclosure relates generally to wireless communications, and more particularly to systems and methods for identifying one or more wireless communication nodes.

Background

Generally, in a wireless communication network, a User Equipment (UE) transmits at least one corresponding preamble to a Base Station (BS) to initiate a random access procedure. Such a preamble is used as a temporary identification of the BS by the UE to estimate various information, such as a timing advance command, scheduling of uplink resources used by the UE in a subsequent step, so that the UE can complete a random access procedure using the above information. And after the random access procedure is finished, the UE is allowed to transmit/receive data to/from the BS.

In some scenarios, although there are multiple UEs in a wireless communication network, each UE may wish to perform a respective random access procedure, each UE may randomly select a respective preamble to initiate the random access procedure. As the number of UEs per UE wanting to perform a random access procedure (simultaneously) increases, such random selection of the preamble signal may result in collisions, which may adversely affect the random access procedure. To reduce collisions, a technique of increasing the number of different preambles has been proposed.

However, the increase in the number of preamble signals may in turn cause various problems, such as additional waste in time/frequency resources, an increase in complexity of a reception node (e.g., BS) in processing the preamble signals, and the like. Furthermore, it should be appreciated that the above may occur more frequently in various applications of 5G New Radio (NR) communication networks (hereinafter "5G networks"), such as large-scale machine type communication (M-MTC), ultra-reliable and low latency communication (URLLC), enhanced mobile broadband (eMBB), etc. While existing systems and methods do not provide a fully satisfactory solution, there is a need for a method and system to provide a technique that meets this anticipated need in a 5G network.

Disclosure of Invention

The exemplary embodiments disclosed herein are directed to solving the problems associated with one or more of the problems presented in the prior art, as well as providing additional features that will become apparent upon reference to the following detailed description when taken in conjunction with the accompanying drawings. In accordance with various embodiments, exemplary systems, methods, devices, and computer process products are disclosed herein. It is to be understood, however, that these embodiments are given by way of illustration and not of limitation, and that various modifications to the disclosed embodiments may be apparent to those skilled in the art upon reading this disclosure while remaining within the scope of the invention.

In one embodiment, a method comprises: providing, by a first wireless communication node, a plurality of bits comprising a spreading sequence; generating a plurality of spreading symbols based on the spreading sequence; and transmitting the plurality of extension symbols to perform a communication procedure initiated by the first wireless communication node.

In another embodiment, a method performed by a first wireless communication node comprises: receiving a signal comprising a plurality of first spreading symbols; selecting a first subset from a plurality of pre-configured spreading sequences by: calculating a metric for each of a plurality of preconfigured spreading sequences of the first subset using the signal; and processing the signal to identify at least one second wireless communication node based on the first subset of the plurality of preconfigured spreading sequences.

Drawings

Various exemplary embodiments of the present invention are described in detail below with reference to the accompanying drawings. The drawings are provided for purposes of illustration only and merely depict exemplary embodiments of the invention to facilitate the reader's understanding of the invention. Accordingly, the drawings are not to be considered limiting of the breadth, scope, or applicability of the present invention. It should be noted that for clarity and ease of illustration, the drawings are not necessarily drawn to scale.

Fig. 1 illustrates an exemplary cellular communication network in which the techniques disclosed herein may be implemented, according to an embodiment of the present disclosure.

Fig. 2 illustrates a block diagram of an example base station and user equipment, in accordance with some embodiments of the present disclosure.

Fig. 3A and 3B collectively illustrate a flow diagram of an example method for identifying one or more wireless communication nodes, in accordance with some embodiments of the present disclosure.

Fig. 4A and 4B collectively illustrate a symbolic (symbololic) diagram showing how a correlation matrix is generated for identifying one or more wireless communication nodes, according to some embodiments of the present disclosure.

Detailed Description

Various exemplary embodiments of the invention are described below with reference to the drawings to enable one of ordinary skill in the art to make and use the invention. It will be apparent to those skilled in the art upon reading this disclosure that various changes or modifications can be made to the examples described herein without departing from the scope of the invention. Accordingly, the present invention is not limited to the exemplary embodiments and applications described and illustrated herein. Moreover, the particular order or hierarchy of steps in the methods disclosed herein is merely exemplary of the methods. Based upon design preferences, the specific order or hierarchy of steps in the methods or processes disclosed may be rearranged while remaining within the scope of the present invention. Accordingly, one of ordinary skill in the art will appreciate that the methods and techniques disclosed herein represent various steps or actions in a sample order, and the invention is not limited to the specific order or hierarchy presented unless otherwise explicitly stated.

Fig. 1 illustrates an example wireless communication network 100 in which the techniques disclosed herein may be implemented, according to an embodiment of the disclosure. In the following discussion, the wireless communication network 100 may be an NB-IoT network, referred to herein as "network 100". Such an exemplary network 100 includes a base station 102 (hereinafter "BS 102") and a user equipment 104 (hereinafter "UE 104") capable of communicating with each other via a communication link 110 (e.g., a wireless communication channel), and a set of

conceptual cells

126, 130, 132, 134, 136, 138, and 140 covering a geographic area 101. In fig. 1, BS102 and UE 104 are contained within respective geographic boundaries of cell 126. Each of the

other units

130, 132, 134, 136, 138 and 140 may include at least one base station operating on its allocated bandwidth to provide adequate wireless coverage to its intended users.

For example, the BS102 may operate on an allocated channel transmission bandwidth to provide sufficient coverage to the UE 104. BS102 and UE 104 may communicate via downlink radio frames 118 and uplink radio frames 124, respectively. Each radio frame 118/124 may be further divided into subframes 120/127, which may include data symbols 122/128. In the present disclosure, the BS102 and UE 104 are generally described as non-limiting examples of "communication nodes" that may practice the methods disclosed herein. Such a communication node may be capable of wireless and/or wired communication according to various embodiments of the present invention.

Fig. 2 illustrates a block diagram of an example wireless communication system 200 for transmitting and receiving wireless communication signals (e.g., OFDM/OFDMA signals) in accordance with some embodiments of the present invention. System 200 may include components and elements configured to support known or conventional operational features, which need not be described in detail herein. In one exemplary embodiment, system 200 can be employed for transmitting and receiving data symbols in a wireless communication environment, such as wireless communication environment 100 of fig. 1, as described above.

The system 200 generally includes a base station 202 (hereinafter "BS 202") and a user equipment 204 (hereinafter "UE 204"). BS 202 includes a BS (base station) transceiver module 210, a BS antenna 212, a BS processor module 214, a BS memory module 216, and a network communication module 218, each coupled and interconnected with each other as needed via a data communication bus 220. The UE204 includes a UE (user equipment) transceiver module 230, a UE antenna 232, a UE memory module 234, and a UE processor module 236, each coupled and interconnected with each other as needed via a data communication bus 240. BS 202 communicates with UE204 via communication channel 250, which communication channel 250 may be any wireless channel or other medium known in the art suitable for data transmission as described herein.

As will be appreciated by one of ordinary skill in the art, the system 200 may further include any number of modules other than those shown in fig. 2. Those of skill in the art will appreciate that the various illustrative blocks, modules, circuits, and processing logic described in connection with the embodiments disclosed herein may be implemented as hardware, computer readable software, firmware, or any practical combination thereof. To clearly illustrate this interchangeability and compatibility of hardware, firmware, and software, various illustrative components, blocks, modules, circuits, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware, firmware, or software depends upon the particular application and design constraints imposed on the overall system. Those familiar with the concepts described herein may implement such functionality in an appropriate manner for each particular application, but such implementation decisions should not be interpreted as limiting the scope of the present invention.

According to some embodiments, UE transceiver 230 may be referred to herein as an "uplink" transceiver 230, which includes RF transmitter and receiver circuitry each coupled to an antenna 232. A duplex switch (not shown) may alternately couple the uplink transmitter or receiver to the uplink antenna in a time-duplex manner. Similarly, BS transceiver 210 may be referred to herein as a "downlink" transceiver 210, which includes RF transmitter and receiver circuits that are each coupled to an antenna 212, according to some embodiments. The downlink duplex switch may alternately couple the downlink transmitter or receiver to the downlink antenna 212 in a time-duplex manner. The operation of the two

transceivers

210 and 230 is coordinated in time such that the uplink receiver is coupled to the uplink antenna 232 to receive transmissions over the wireless transmission link 250 while the downlink transmitter is coupled to the downlink antenna 212. Preferably there is a tight time synchronization with only a minimum guard time between changes in the duplex direction.

UE transceiver 230 and BS transceiver 210 are configured to communicate via a wireless data communication link 250 and cooperate with appropriately configured RF antenna devices 212/232 capable of supporting particular wireless communication protocols and modulation schemes. In some example embodiments, the UE transceiver 210 and the BS transceiver 210 are configured to support industry standards such as Long Term Evolution (LTE) and emerging 5G standards. It should be understood, however, that the present invention is not necessarily limited in application to a particular standard and associated protocol. Rather, UE transceiver 230 and BS transceiver 210 may be configured to support alternative or additional wireless data communication protocols, including future standards or variations thereof.

According to various embodiments, BS 202 may be an evolved node B (eNB), serving eNB, target eNB, femto station, or pico station, for example. In some embodiments, the UE204 may be embodied in various types of UEs, such as mobile phones, smart phones, Personal Digital Assistants (PDAs), tablets, laptops, wearable computing devices, and so forth. The

processor modules

214 and 236 may be implemented or realized with a general purpose processor, a content addressable memory, a digital signal processor, an application specific integrated circuit, a field programmable gate array, any suitable programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. In this manner, the processor may be implemented as a microprocessor, controller, microcontroller, state machine, or the like. A processor may also be implemented as a combination of computing devices, e.g., a combination of a digital signal processor and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a digital signal processor core, or any other such configuration.

Furthermore, the steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in firmware, in a software module executed by the

processor modules

214 and 236, respectively, or in any practical combination thereof.

Memory modules

216 and 234 may be implemented as RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. In this regard, the

memory modules

216 and 234 may be coupled to the

processor modules

210 and 230, respectively, such that the

processor modules

210 and 230 may read information from the

memory modules

216 and 234 and write information to the

memory modules

216 and 234, respectively. The

memory modules

216 and 234 may also be integrated into their

respective processor modules

210 and 230. In some embodiments, the

memory modules

216 and 234 may each include a cache memory for storing temporary variables or other intermediate information during execution of instructions to be executed by the

processor modules

210 and 230, respectively. The

memory modules

216 and 234 may also each include non-volatile memory for storing instructions to be executed by the

processor modules

210 and 230, respectively.

The network communication module 218 generally represents the hardware, software, firmware, processing logic, and/or other components of the base station 202 that enable bi-directional communication between the base station transceiver 210 and other network components and communication nodes configured to communicate with the base station 202. For example, the network communication module 218 may be configured to support internet or WiMAX traffic. In a typical deployment, without limitation, the network communication module 218 provides an 802.3 ethernet interface so that the base station transceiver 210 can communicate with a conventional ethernet-based computer network. In this manner, the network communication module 218 may include a physical interface for connecting to a computer network (e.g., a Mobile Switching Center (MSC)).

Referring again to fig. 1, as described above, when each of a plurality of UEs (e.g., 104) wants to initiate a random access procedure, each of the plurality of UEs transmits a preamble to the BS102 for the BS102 to identify the UE and accordingly transmits required information to the corresponding UE for subsequent data communication. As described above, such techniques and corresponding improved techniques to increase randomness (e.g., reduce collisions) have encountered various problems in 5G networks as the number of UEs increases.

The present disclosure provides various embodiments of systems and methods for the BS102 to identify each of a plurality of UEs without requiring the UEs to send any preamble signals when initiating respective random access procedures. Conversely, in some embodiments, each of the plurality of UEs spreads the respective symbols modulated based on the information bits using a spreading sequence associated with the one or more information bits that the UE intends to transmit, and transmits such spread symbols to BS102 to initiate the respective random access procedure. In some embodiments, when BS102 receives a signal containing such multiple spreading symbols, which are respectively transmitted from multiple UEs requesting a random access procedure, BS102 blindly decodes the signal using Successive Interference Cancellation (SIC) techniques to identify each UE and obtain a corresponding one or more information bits. In some embodiments, BS102 filters one or more spreading sequences continuously from a plurality of preconfigured spreading sequences by estimating at least one measurement or metric using the received signal. It should be understood that the terms "measurement" and "metric" are interchangeable, and for purposes of consistency, the term "measurement" will be used in the following discussion. More specifically, in accordance with some embodiments of the present disclosure, when receiving signals via two or more antennas of BS102, BS102 may calculate at least one measurement based on a correlation matrix derived from the signals or a cross-correlation matrix derived from the signals. As such, BS102 can effectively reduce the number of spreading sequences that BS102 will use to reconstruct the received signal (e.g., identify UEs and further acquire one or more information bits transmitted by each UE), which in turn can significantly reduce complexity and/or improve accuracy of identifying UEs, even when collisions occur.

Transmitter side (e.g., UE) embodiments

In some embodiments, when a UE (e.g., UE 104) wants to initiate a random access process, the UE 104 may perform at least some of the following steps: providing a signal comprising a plurality of bits N to be transmitted_oSequence d of_OIn which bit N_OIncluding one or more information bits N that UE 104 wants to transmit to BS102_UAnd one or more bits N representing a spreading sequence_D(ii) a For sequence d_OPerforming error detection processing (e.g., Cyclic Redundancy Check (CRC) processing) to generate a data stream including N_EBit (N)_E＞N_O) CRC sequence d of_E(ii) a Performing a coding process (e.g., Turbo coding process) on the CRC sequence to generate a CRC sequence comprising N_YBit (N)_Y＞N_E) Sequence d of_Y(ii) a For sequence d_YPerforming modulation processing (e.g., Quadrature Phase Shift Keying (QPSK) modulation processing) to generate a signal including N_CModulation symbol

Sequence d of_CWherein L is_MA number of bits representing a single modulation symbol; the use can be in the sequence d_ETo spread a sequence from a plurality of pre-configured spread sequences or may already be in sequence d_ETo the sequence d by selecting a spreading sequence from the spreading sequences indicated in (1)_CPerforming an expansion, thereby generating a sequence d_W(sequence d)_WLength of (1)' N_W，"may be equal to N_CN_SIn which N is_SIs the length of the spreading sequence); and sequence d using corresponding time-frequency resources_WAnd transmitted to BS 102. In some embodiments, after CRC processing, one or more bits N representing the spreading sequence_DCan be included, for example, in the sequence d_EIn the corresponding CRC bits. In some other embodiments, one or more bits N_DMay correspond to a spreading sequence identification representing a spreading sequence that may be used to identify the spreading sequence from a plurality of pre-configured spreading sequences. In some embodiments, one or more information bits N_UThe identity of the UE 104, which is commonly referred to as the UE ID, may be included.

Receiver side (e.g., BS) embodiments

Fig. 3A and 3B collectively illustrate a flow diagram of an exemplary method performed by BS102 for identifying one or more UEs, each transmitting multiple spreading symbols (as described above) to initiate a random access procedure, in accordance with various embodiments. The illustrated embodiment of the method 300 is merely an example. Accordingly, it should be understood that any of the various operations may be omitted, reordered, and/or added while remaining within the scope of the present disclosure. Moreover, in some embodiments, the operations of method 300 are provided to generally illustrate how BS102 identifies one or more UEs, such that each operation of method 300 will be briefly described, and further details will be provided in the following examples (e.g., examples 1-9).

In some embodiments, the method 300 begins with operation 302, in operation 302, the BS102 receives the signal "y", and using the signal y to estimate a first measurement value for each of a plurality of preconfigured spreading sequences. In some embodiments, such a signal y may comprise a sequence d comprising a plurality of spreading symbols as discussed above_WSuch that the signal y is referred to herein as the spreading symbol y. Furthermore, in some embodiments, the spreading symbol y may be a plurality of such sequences d_WEach sequence being transmitted from a respective different UE requesting a respective random access procedure. Next, method 300 continues to operation 304, where BS102 selects a first subset from the plurality of preconfigured spreading sequences based on the first measurement value in operation 304. The method 300 continues to operation 306, and in operation 306, the BS102 estimates a second measurement value for each of the first subset of preconfigured spreading sequences using the spreading symbol y. The method 300 continues to operation 308, and in operation 308, the BS102 selects Ks equalized measurement vectors (equalized measurement vectors) based on the second measurement values, and demodulates/decodes the spread symbols y using the Ks equalized measurement vectors, respectively. The method 300 continues to determining operation 310, in which operation 310 the BS102 determines whether the decoded signals are all valid by checking whether each decoded signal passed through an error detection circuit (e.g., a CRC circuit). If so, the method 300 continues to operation 312, and in operation 312, the BS102 retrieves various information from each decoded signal and uses at least a portion of the various information to obtain a corresponding reconstructed signal "s". In some embodiments, the various information may include a UE ID of a particular UE, and a spreading sequence used by the UE to initiate a random access procedure. In some embodiments, the particular UE may be "identified" when its UE ID and spreading sequence are retrieved. One of ordinary skill in the art will note that the reconstructed signal is generated by performing a series of substantially similar processes (e.g., encoding, modulation, spreading, etc.) on the transmitting end (e.g., UE 104) to reconstruct the sequence (e.g., sequence d) transmitted by UE 104_W). The method 300 continues to operation 314 where the BS102 performs channel estimation based on each reconstructed signal in operation 314. Next, the method 300 continues to operation 316, where the BS102 performs interference cancellation on the spreading symbols y in operation 316. In some embodiments, in operation316, the method 300 may be iteratively performed from operation 302 through the determination operation 310 until there are no more decoded signals that have been determined to be valid, wherein the method 300 ends at operation 318.

Example 1

In some embodiments, BS102 may receive spreading symbol y described above using a single antenna. When the extension symbol y is presented in a matrix form, the extension symbol y may be N_S×N_CMatrix, where N_SRepresents the length of the spreading sequence, which may be predefined; and N is_CRepresents the number of symbols before spreading, which may be determined by BS102 once BS102 receives spreading symbol y. BS102 then repeatedly performs the following steps 1-10 of the process to process the spreading symbols y in order to identify one or more UEs, each of which transmits a sequence (e.g., d)_W) To request the respective random access procedure.

Step 1 (corresponding to operation 302), BS102 estimates a first measurement value "m" for each of a plurality of preconfigured spreading sequences in a number of Ms. More specifically, in some embodiments, for the kth spreading sequence of the Ms preconfigured spreading sequences, the k-th spreading sequence may be selected from the set of Ms preconfigured spreading sequences

To estimate a corresponding first measured value m_kWherein c is_kRepresents the k-th spreading sequence, which may be N_SThe x 1 vector is presented and k is 1, 2, …, M_S(ii) a And is

Can be used as N_S×N_SThe matrix is presented. In addition, y^HRepresenting the conjugate transmission of the spreading symbol y when the spreading symbol y is in the form of a matrix,

representation matrix

The inverse of (c). In some casesIn the embodiment, when the extension symbol y is presented in the form of a matrix, the matrix

May be a correlation matrix of the spreading symbols y.

Step 2 (corresponding to part of operation 304), BS102 orders the respective first measurements of the Ms preconfigured spreading sequences in ascending order. More specifically, according to some embodiments, BS102 rearranges the first measurements in ascending order

To obtain

Wherein the index

To

The rearranged Ms preconfigured spreading sequences may be represented in ascending order, respectively.

Step 3 (corresponding to part of operation 304), BS102 selects Ls spreading sequences from the Ms preconfigured spreading sequences

As a first subset, wherein the Ls spreading sequences correspond to Ls smallest first measured values (L), respectively_s≤M_s). In addition, BS102 associates spreading symbols y with a first subset (e.g., Ls spreading sequences) to obtain a measurement vector "u_i". More specifically, the present invention is described in detail,

wherein u is_iIs a vector of 1 XN_CAnd i ═ 1, 2, …, L_s。

Step 4, BS102 pairs measurement vector u_iCarrying out equalization to obtain an equalization measurement vector

Wherein

Is 1 XN_CVector, and i ═ 1, 2, …, L_s。

Step 5 (corresponding to part of operation 306), BS102 calculates "r" for each equalization measurement vector. In some embodiments, the r may be a signal to interference plus noise ratio (SINR). More specifically, BS102 measures vectors for each equalization measurement

Calculating SINR to obtain

Step 6 (corresponding to operation 308), BS102 sorts the SINR values of the Ls equalization measurement vectors in descending order. More specifically, BS102 rearranges in descending order

To obtain

In addition, BS102 measures vectors from multiple equalizations

Ks equalization measurement vectors are selected, where the Ks equalization measurement vectors correspond to Ks maximum second measurement values (e.g., SINR in the current example), respectively, or each of the Ks maximum second measurement values is greater than a predetermined SINR threshold. As such, it can be appreciated that K_s≤L_s. Next, BS102 demodulates/decodes the spread symbols y using the Ks equalization measurement vectors. More specifically, BS102 can obtain Ks decoded signals by demodulating/decoding the spread symbols y using Ks spreading sequences.

In step 7 (corresponding to operation 310), the BS102 checks whether the Ks decoded signals pass through the CRC circuit. More specifically, if none (e.g., none of the Ks decoded signals passes the CRC circuit), the process ends (identifying one or more UEs from the spreading symbols y); if so (e.g., at least one of the Ks decoded signals passed through the CRC circuit), the process proceeds to step 8.

In step 8 (corresponding to operation 312), BS102 uses the Ks decoded signals to obtain a corresponding "used spreading sequence". Based on the spreading sequence used, BS102 obtains the reconstructed signal

Each of the reconstructed signals may be represented as N_S×N_CAnd (4) matrix. More specifically, in some embodiments, if in step 7 one or more of the Ks decoded signals fail the CRC circuit, BS102 may determine the corresponding reconstructed signals as each a zero matrix (e.g., s)_k0). And, if one or more of the Ks decoded signals pass through the CRC circuit, the BS102 may retrieve various information contained in the respective decoded signals to obtain corresponding reconstructed signals.

Step 9 (corresponding to operation 314), BS102, for each reconstructed signal

Estimating respective channel gain coefficients h_k，h_kCan be presented as N_S×N_CAnd (4) matrix. In some embodiments, if the reconstructed signal is a zero matrix (as determined in step 8), BS102 may determine its corresponding channel gain coefficient to be zero (i.e., not perform the channel estimation process).

Step 10 (corresponding to operation 316), BS102 performs interference cancellation on the spread symbols y. More specifically, BS102 uses the following equation

To eliminate from the spreading symbol y the signal (i.e. the sequence comprising a plurality of spreading symbols) transmitted by each "identified" UE, in order to continue to identify the remaining one or more UEs. In some embodiments，h_k·s_kIs h_kAnd s_kHadamard product of (a).

Example 2

In some embodiments, BS102 may receive spreading symbol y described above using a single antenna. When the extension symbol y is presented in a matrix form, the extension symbol y may be N_S×N_CMatrix, where N_SRepresents the length of the spreading sequence, which may be predefined; and N is_CIndicating the number of symbols before spreading, which BS102 can determine once BS102 receives spreading symbol y. BS102 then repeatedly performs the following steps 1-10 of the process to process the spreading symbols in order to identify one or more UEs, each of which transmits a sequence (e.g., d)_W) To request the respective random access procedure.

Step 1 (corresponding to operation 302), BS102 estimates a first measurement value for each of a plurality of preconfigured spreading sequences among a plurality of Ms. More specifically, in some embodiments, the k-th spreading sequence of the Ms preconfigured spreading sequences may be represented by

To estimate a corresponding first measured value m_kWherein c is_kDenotes the k-th spreading sequence, which may be N_SX 1 vector representation, and k is 1, 2, …, M_S(ii) a And is

Can be used as N_S×N_CThe matrix is represented. In addition, y^HMeaning that, when the spreading symbol y is in the form of a matrix, the conjugate transmission of the spreading symbol y,

representation matrix

The inverse of (c). In some embodiments, when the spreading symbol y is presented in the form of a matrix, the matrix

May be a correlation matrix of the spreading symbols y.

Step 2 (corresponding to part of operation 304), BS102 orders the respective first measurements of the Ms preconfigured spreading sequences in ascending order. More specifically, according to some embodiments, BS102 rearranges the respective first measurement values of the pre-configured spreading sequences in descending order

To obtain

Wherein the index

To

The rearranged preconfigured spreading sequences may be represented in ascending order, respectively.

As a first subset, wherein the Ls spreading sequences correspond to Ls smallest first measured values (Ls ≦ M), respectively_S). In addition, BS102 associates spreading symbols y with a first subset (e.g., Ls spreading sequences) to obtain a measurement vector "u_i". More specifically, the present invention is to provide a novel,

or

Wherein u is_iIs 1 XN_CVector, and i ═ 1, 2, …, L_s。

Step 4, BS102 equalizes the measurement vector to obtain an equalized measurement vector

Wherein BB1 is a vector 1 XN_CAnd i ═ 1, 2, …, L_s。

Step 5 (corresponding to part of operation 306), BS102 calculates "r" for each equalization measurement vector. In some embodiments, r may be a signal to interference plus noise ratio (SINR). More specifically, BS102 measures a vector for each equalization measurement

Calculating SINR to obtain

To obtain

In addition, BS102 measures vectors from multiple equalizations

Ks equalization measurement vectors are selected, where the Ks equalization measurement vectors correspond to Ks maximum second measurement values (e.g., SINR in the current example), respectively, or each of the Ks maximum second measurement values is greater than a predetermined SINR threshold. Thus, it can be understood that K_sLs is less than or equal to Ls. Next, BS102 demodulates/decodes the spread symbols y using the Ks equalization measurement vectors. More specifically, BS102 can obtain Ks decoded signals by demodulating/decoding the spread symbols y using Ks spreading sequences.

Step 9 (corresponding to operation 314), BS102, for each reconstructed signal

To eliminate from the spreading symbol y the signal (i.e. the sequence comprising a plurality of spreading symbols) transmitted by each "identified" UE, in order to continue to identify the remaining one or more UEs. In some embodiments, h_k·s_kIs h_kAnd s_kHadamard product of (a).

Example 3

In some embodiments, BS102 may receive spreading symbol y described above using two or more antennas. For example, the first and second antennas of BS102 may receive signals y1 and y2, respectively, each of which includes a plurality of spreading symbols. In this example, BS102 combines signals y1 and y2 with respective weights as spreading symbols y. More specifically, BS102 may calculate candidate set a of weighting vectors_jTo combine two or more signals, where j ═ 1, 2, …, N_C. That is, the candidate set includes Mc weighting vectors:

in some embodiments, the weight vector a_jIs N_RX 1 vector, where N_RIs the number of antennas of BS102 that respectively receive the component signals of spreading symbol y. Furthermore, the Mc weight vector

Satisfy the requirement of

When the extension symbol y is presented in a matrix form, the extension symbol y may be N_S×N_CMatrix, where N_SRepresents the length of the spreading sequence, which may be predefined; and N is_CIndicating the number of symbols before being spread, which BS102 can determine once BS102 receives the spread symbol y. BS102 then repeatedly performs the following steps 1-10 of the process to decode the spreading symbol y to identify one or more UEs, each of which transmits a sequence (e.g., d)_W) To request a corresponding random access procedure.

Unlike examples 1 and 2, in examples 1 and 2 BS102 only uses one antenna to receive spreading symbol y before calculating the first measurements of the plurality of preconfigured spreading sequences, and in some embodiments BS102 may perform step 0 to obtain the signal

Wherein

Is N_S×N_CAnd (4) matrix. Since the following steps are substantially similar to examples 1 and 2, detailed description of the following steps is not repeated here.

Step 1, for each weight vector a_jBS102 estimates a first measurement value "m" for each of a plurality of pre-configured spreading sequences_k，j". More specifically, in some embodiments, for the k-th spreading sequence, the k-th spreading sequence may be encoded by

To estimate a corresponding first measured value m_k，jWherein c is_kThe representation may be presented as N_SThe kth spreading sequence of the x 1 vector, and k is 1, 2, …, M_S(ii) a And is

Can be taken as N_S×N_SA matrix.

Step 2, for each weight vector a_jBS102 pair

Sorting in ascending order to obtain

Step 3, the BS102 selects Ls spreading sequences

Wherein Ls is less than or equal to M_S. In addition, BS102 correlates the spreading symbols y with Ls spreading sequences to obtain corresponding measurement vectors

Wherein u is_i，jIs 1 XN_cVector, and i ═ 1, 2, …, L_sAnd is andj＝1，2，…，M_c。

Wherein i is 1, 2, …, L_sAnd j is 1, 2, …, M_C。

Step 5, BS102 is for each

Calculating respective SINRs to obtain r_i，jWhere i is 1, 2, …, L_SAnd j is 1, 2, …, M_C。

Step 6, BS102 pair

Sorting in descending order to obtain

In addition, the BS102 includes

Selects Ks equalization measurement vectors, wherein the Ks equalization measurement vectors correspond to Ks maximum SINRs (K)_S≤L_SM_C) Or each of the Ks maximum SINRs is greater than a predefined SINR threshold. Next, BS102 demodulates/decodes the spread symbols y using Ks equalization measurement vectors (e.g., Ks spreading sequences). More specifically, BS102 can obtain Ks decoded signals by demodulating/decoding the spread symbols y using Ks spreading sequences.

In step 7, the BS102 checks whether the Ks decoded signals pass through the CRC circuit. More specifically, if none (e.g., none of the Ks decoded signals passes the CRC circuit), the process ends (identifying one or more UEs from the spreading symbols y); if so (e.g., at least one of the Ks decoded signals passed through the CRC circuit), the process proceeds to step 8.

Step 8, BS102 uses KsThe signal is decoded to obtain the corresponding used spreading sequence. Based on the spreading sequence used, BS102 obtains the reconstructed signal

Each signal

Can be presented as N_S×N_C×N_RAnd (4) matrix. More specifically, in some embodiments, if in step 7 one or more of the Ks decoded signals do not pass through the CRC circuit, BS102 may determine the corresponding reconstructed signals as each a zero matrix (e.g., s)_k0); and if one or more of the Ks signals passes the CRC circuit, BS102 may retrieve the various information contained in the respective decoded signals to obtain corresponding reconstructed signals.

Step 9, BS102 for each reconstructed signal

Estimating respective channel gain coefficients h_k，h_kCan be presented as N_S×N_C×N_RAnd (4) matrix.

In step 10, BS102 performs interference cancellation on spreading symbol y. More specifically, BS102 uses the following equation

Example 4

In some embodiments, BS102 may receive spreading symbol y described above using two or more antennas. For example, the first and second antennas of BS102 may receive signals y1 and y2, respectively. More specifically, BS102 may calculate candidate set a of weighting vectors_jTo combine withTwo or more signals, where j-1, 2, …, M_C. That is, the candidate set includes Mc weighting vectors:

in some embodiments, the weight vector a_jIs N_RA x 1 vector, where NR is the number of antennas of BS102 that respectively receive the component signals of spreading symbol y. Furthermore, the Mc weight vector

Satisfy the requirement of

When the extension symbol y is presented in a matrix form, the extension symbol y may be N_S×N_CMatrix, where N_SDenotes the length of the spreading sequence, which may be predefined, and N_CRepresents the number of symbols before being spread, which may be determined by BS102 once BS102 receives the spread symbol y; BS102 then repeatedly performs the following steps 1-10 of the process to decode the spreading symbol y to identify one or more UEs, each transmitting a sequence (e.g., d)_W) To request a corresponding random access procedure.

Wherein

Step 1, for each weight vector a_jBS102 estimates for each of a plurality of preconfigured spreading sequencesMeasuring a first measured value "m_k，j". More specifically, in some embodiments, for the k-th spreading sequence, the k-th spreading sequence may be encoded by

Can be used as N_S×N_SA matrix is presented.

Step 2, for each weight vector a_jBS102 pair

Sorting in descending order to obtain

Step 3, BS102 selects Ls spreading sequence

Wherein Ls is less than or equal to M_S. In addition, BS102 correlates the spreading symbol y with the Ls spreading sequence to obtain a corresponding measurement vector

Or

Wherein u is_i，jIs 1 XN_CVector, and i ═ 1, 2, …, L_SAnd j is 1, 2, …, M_C。

Step 4, BS102 pairs measurement vector u_i，jCarrying out equalization to obtain an equalization measurement vector

Wherein i is 1, 2, …, L_SAnd j is 1, 2,…，M_C。

step 5, BS102 is for each

Calculating respective SINRs to obtain r_i，jWhere i is 1, 2, …, L_sAnd j is 1, 2, …, M_C4。

Step 6, BS102 pair

Sorting in descending order to obtain

In addition, the BS102 includes

In step 7, the BS102 checks whether the Ks decoded signals pass through the CRC circuit. More specifically, if none (e.g., none of the Ks decoded signals passes the CRC circuit), the process ends (identifying one or more UEs from the spreading symbols y); if so (e.g., at least one of the Ks decoded signals passed the CRC circuit), then the process proceeds to step 8.

In step 8, BS102 uses the Ks decoded signals to obtain the corresponding used spreading sequences. Based on the spreading sequence used, BS102 obtains the reconstructed signal

Each signal

Can be presented as N_S×N_C×N_RAnd (4) matrix. More specifically, in some embodiments, if in step 7 one or more of the Ks decoded signals do not pass through the CRC circuit, BS102 may determine the corresponding reconstructed signals as each a zero matrix (e.g., s)_k0); and if one or more of the Ks decoded signals passes the CRC circuit, BS102 may retrieve the various information contained in the respective decoded signals to obtain corresponding reconstructed signals.

Step 9, BS102 for each reconstructed signal

Estimating the corresponding channel gain factor h_kH of_kCan be presented as N_C×N_C×N_RAnd (4) matrix.

Example 5

Similar to example 3, BS102 may receive spreading symbol y described above using two or more antennas, but unlike example 3, in some embodiments BS102 may "add (appended)" spreading symbol y1 to spreading symbol y2, or "add" spreading symbol y2 to spreading symbol y1, as spreading symbol y, discussed in further detail below. Accordingly, BS102 repeatedly performs the following steps 1-12 of the process to decode the spreading symbol y to identify one or more UEs, each transmitting a sequence (e.g., d)_W) To request a corresponding random access procedure. Note that some steps in the process are substantially similarIn the steps of the above example, the steps in the process will therefore be briefly described.

Step 1, for the kth of the Ms preconfigured spreading sequences (k ═ 1, 2, …, M_R) Spreading sequences, BS102 computes matrix d_k。

Wherein, c_kThe representation may be presented as N_SK-th spreading sequence of x 1 vector, d_kCan be presented as N_RN_S×N_RMatrix, and "0" represents N_SX 1 zero vector.

Step 2, for the k-th spreading sequence, the BS102 estimates a corresponding first measurement "m_k", wherein

Representation matrix q_kN is a positive integer, wherein

And is

In some embodiments, the matrix

Is N_RN_S×N_RN_SA matrix, which may be a correlation matrix of the spreading symbols y when the spreading symbols y are presented in the form of a matrix.

Step 3, BS102 pair

Sorting in descending order to obtain

Step 4, BS102 selection

Wherein L is_S≤M_R。

Step 5, for each weight vector a_j(similar to the weight vector in example 3), the BS102 computes an AND

Corresponding to spreading sequence

Wherein u is_i，jIs 1 XN_CVector, i ═ 1, 2, …, L_SAnd j is 1, 2, …, M_C。

Step 6, BS102 pairs u_i，jCarrying out equalization to obtain

Wherein i is 1, 2, …, L_SAnd j is 1, 2, …, M_C。

Step 7, BS102 for each

Calculating SINRr_i，j。

Step 8, BS102 pair

Sorting in descending order to obtain

In addition, the BS102 includes

Selects Ks equalization measurement vectors, wherein the Ks equalization measurement vectors correspond to Ks maximum SINRs (k) respectively_S≤L_SM_C) Or each of the Ks maximum SINRs is greater than a predetermined SINR threshold. Is connected withBS102 demodulates/decodes the spread symbols y using Ks equalization measurement vectors (e.g., Ks spreading sequences). More specifically, BS102 can obtain Ks decoded signals by demodulating/decoding the spread symbols y using Ks spreading sequences.

In step 9, the BS102 checks whether the Ks decoded signals pass through the CRC circuit. More specifically, if none (e.g., none of the Ks decoded signals passes the CRC circuit), the process ends (identifying one or more UEs from the spreading symbols y); if so (e.g., at least one of the Ks decoded signals passes through the CRC circuit), the process proceeds to step 10.

In step 10, BS102 uses the Ks decoded signals to obtain the corresponding spreading sequences to be used. Based on the spreading sequence used, BS102 obtains the reconstructed signal

Each reconstructed signal

Can be presented as N_RN_S×N_CAnd (4) matrix. More specifically, in some embodiments, if in step 9 one or more of the Ks decoded signals did not pass through the CRC circuit, BS102 may determine the corresponding reconstructed signals as each a zero matrix (e.g., s)_k0); and if one or more of the Ks decoded signals passes the CRC circuit, BS102 may retrieve the various information contained in the respective decoded signals to obtain corresponding reconstructed signals.

Step 11, BS102 for each reconstructed signal

Estimating respective channel gain coefficients h_k，h_kCan be presented as N_RN_S×N_CAnd (4) matrix. In some embodiments, if the reconstructed signal is a zero matrix (as determined in step 10), BS102 may determine its corresponding channel gain coefficient to be zero (i.e., not perform the channel estimation process).

In step 12, BS102 performs interference cancellation on spreading symbol y. More specifically, BS102 uses the following equation

Example 6

Similar to example 3, BS102 may receive spreading symbol y described above using two or more antennas, but unlike example 3, in some embodiments BS102 may "add" spreading symbol y1 to spreading symbol y2, or "add" spreading symbol y2 to spreading symbol y1, as spreading symbol y, discussed in further detail below. Accordingly, BS102 repeatedly performs the following steps 1-12 of the process to decode the spreading symbol y to identify one or more UEs, each transmitting a sequence (e.g., d)_W) To request a corresponding random access procedure. Note that some steps in the process are substantially similar to those of the above example, and thus the steps in the process will be briefly described.

Representation matrix q_kN is a positive integer, wherein

And is

In some embodiments, the matrix

Step 3, BS102 pair

Sorting in ascending order to obtain

Step 4, BS102 selection

Wherein L is_S≤M_R。

Step 5, for each weight vector a_j(similar to the weight vector in example 3), the BS102 calculates a weight vector corresponding to

Of spreading sequences

Or

Wherein u is_i，jIs 1 XN_CVector, i ═ 1, 2, …, L_SAnd j is 1,2，…，M_C。

step 6, BS102 pairs u_i，jCarrying out equalization to obtain

Wherein i is 1, 2, …, L_SAnd j is 1, 2, …, M_C。

Step 7, BS102 for each

And calculating the SINR.

Step 8, BS102 pair

Sorting in descending order to obtain

In addition, the BS102 includes

Selects Ks equalization measurement vectors, wherein the Ks equalization measurement vectors correspond to Ks maximum SINRs (K) respectively_S≤L_SM_C) Or each of the Ks maximum SINRs is greater than a predetermined SINR threshold. Next, BS102 demodulates/decodes the spread symbols y using Ks equalization measurement vectors (i.e., Ks spreading sequences). More specifically, BS102 can obtain Ks decoded signals by demodulating/decoding the spread symbols y using Ks spreading sequences.

Each reconstructed signal

Step 11, BS102 for each reconstructed signal

Example 7

In this example, BS102 performs a process substantially similar to the process discussed in example 4, except that BS102 uses a different technique to estimate weight vector a_jOtherwise, this will be discussed in step 5 below. Therefore, it should be noted thatSome steps in the process will be briefly described.

Representation matrix q_kN is a positive integer, wherein

And is

In some embodiments, the matrix

Step 3, BS102 pair

Sorting in descending order to obtain

Step 4, BS102 selection

Wherein L is_S≤M_R。

Step 5, BS102 uses

Calculating a weighting vector a_jWherein

j＝1，2，…，N_RAnd 1. ltoreq. j_min≤N_R。

Is a matrix

A characteristic value of (A), and

is N_RA x 1 vector;

is corresponding to the characteristic value

Feature vectors of, e.g.

Wherein i is 1, 2, …, L_SAnd j ═ 1, 2, …, N_R。

Step 6, BS102 calculates and

corresponding to spreading sequence

Wherein u is_iIs 1 XN_CThe vector, and i ═ 1, 2,…，L_S。

step 7, BS102 pairs u_iCarrying out equalization to obtain

Wherein i is 1, 2, …, L_S。

Step 8, BS102 is for each

Calculating SINRr_i。

Step 9, BS102 pair

Sorting in descending order to obtain

In addition, the BS102 includes

Selects Ks balanced measurement vectors, wherein the Ks spreading sequences respectively correspond to Ks maximum second measurement values (K)_s≤L_s) Or each of the Ks largest second measurement values is greater than the predetermined SINR threshold. Next, BS102 demodulates/decodes the spread symbols y using the Ks equalization measurement vectors. More specifically, BS102 can obtain Ks decoded signals by demodulating/decoding the spread symbols y using Ks spreading sequences.

In step 10, the BS102 checks whether the Ks decoded signals pass through the CRC circuit. More specifically, if none (e.g., none of the Ks decoded signals passes the CRC circuit), the process ends (identifying one or more UEs from the spreading symbols y); if so (e.g., at least one of the Ks decoded signals passes through the CRC circuit), the process proceeds to step 10.

In step 11, BS102 uses the Ks decoded signals to obtain the corresponding spreading sequences to be used. Based on the spreading sequence used, BS102 obtains the reconstructed signal

Each reconstructed signal

Can be presented as N_RN_S×N_CAnd (4) matrix. More specifically, in some embodiments, if in step 10 one or more of the Ks decoded signals did not pass through the CRC circuit, BS102 may determine the corresponding reconstructed signals as each a zero matrix (e.g., s)_k0); and if one or more of the Ks decoded signals passes the CRC circuit, BS102 may retrieve the various information contained in the respective decoded signals to obtain corresponding reconstructed signals.

Step 12, BS102 for each reconstructed signal

Estimating the corresponding channel gain factor h_k，h_kCan be presented as N_RN_S×N_CAnd (4) matrix. In some embodiments, if the reconstructed signal is a zero matrix (as determined in step 10), BS102 may determine its corresponding channel gain coefficient to be zero (i.e., not perform the channel estimation process).

In step 13, BS102 performs interference cancellation on spreading symbol y. More specifically, BS102 uses the following equation

Example 8

In this example, BS102 performs a process substantially similar to the process discussed in example 4, except that BS102 uses a different technique to estimate weight vector a_jOtherwise, this will be discussed in step 5 below. Therefore, it should be noted that some steps in the process will be briefly described.

Representation matrix q_kN is a positive integer, wherein

And is

In some embodiments, the matrix

Step 3, BS102 pair

Sorting in ascending order to obtain

Step 4, BS102Selecting

Wherein L is_S≤M_R。

Step 5, BS102 uses

Calculating a weighting vector a_jWherein

j＝1，2，…，N_RAnd 1. ltoreq. j_min≤N_R。

Is a matrix

A characteristic value of (A), and

is N_RA x 1 vector;

is corresponding to the characteristic value

The feature vector of (a), for example,

wherein i is 1, 2, …, L_SAnd j ═ 1, 2, …, N_R。

Step 6, BS102 calculates and

corresponding to spreading sequence

Or

Wherein u is_iIs 1 XN_CVector sum i 1, 2, …, L_S。

Step 7, BS102 pairs u_iCarrying out equalization to obtain

Wherein i is 1, 2, …, L_S。

Step 8, BS102 is for each

Calculating SINR r_i。

Step 9, BS102 pair

Sorting in descending order to obtain

In addition, the BS102 includes

Selects Ks balanced measurement vectors, wherein the Ks spreading sequences respectively correspond to Ks maximum second measurement values (K)_s≤L_s) Or each of the Ks largest second measurement values is greater than a predetermined SINR threshold. Next, BS102 demodulates/decodes the spread symbols y using the Ks equalization measurement vectors. More specifically, BS102 can obtain Ks decoded signals by demodulating/decoding the spread symbols y using Ks spreading sequences.

Each reconstructed signal

Step 12, BS102 for each reconstructed signal

Example 9

In this example, BS102 performs a process substantially similar to the process discussed in example 5, except that BS102 uses a different technique to estimate first measurement value m_kAs will be described belowStep 1 of (a). Therefore, it should be noted that some steps in the process will be briefly described.

Step 1, for the k-th spreading sequence, the BS102 estimates a corresponding first measurement "m_k", wherein

Representation matrix q_kN is a positive integer, wherein

And is

In some embodiments, the matrix

Is N_S×N_SA matrix, which may be a correlation matrix of the spreading symbols y when the spreading symbols y are presented in the form of a matrix.

Step 2, BS102 pair

Sorting in descending order to obtain

Step 3, BS102 selection

Wherein L is_S≤M_R。

Step 4, BS102 acquires signals

Wherein

Is N_S×N_CAnd (4) matrix.

Step 5, BS102 calculates and

corresponding to spreading sequences

Wherein u is_iIs 1 XN_CVector, i ═ 1, 2, …, L_SAnd j is 1, 2, …, M_C. And is

Wherein

Is N_S×N_SAnd (4) matrix.

Step 6, BS102 pairs u_i，jCarrying out equalization to obtain

Wherein i is 1, 2, …, L_SAnd j is 1, 2, …, M_C。

Step 7, BS102 for each

The SINR is calculated and the calculated SINR is used,

step 8, BS102 pair

Sorting in descending order to obtain

In addition, the BS102 includes

Selects Ks balanced measurement vectors, wherein the Ks spreading sequences respectively correspond to Ks maximum second measurement values (K)_s≤L_s) Or each ofThe Ks largest second measurements are greater than the predetermined SINR threshold. Next, BS102 demodulates/decodes the spread symbols y using the Ks equalization measurement vectors. More specifically, BS102 can obtain Ks decoded signals by demodulating/decoding the spread symbols y using Ks spreading sequences.

In step 10, the BS102 uses the Ks decoded signals to obtain a reconstructed signal

Each reconstructed signal

Can be presented as N_RN_S×N_CAnd (4) matrix. Specifically, BS102 uses the Ks decoded signals to obtain the corresponding used spreading sequences. Based on the spreading sequence used, BS102 obtains the reconstructed signal

Each signal may be represented by N_RN_S×N_CAnd displaying in a matrix form. More specifically, in some embodiments, if in step 9 one or more of the Ks decoded signals did not pass through the CRC circuit, BS102 may determine the corresponding reconstructed signals as each a zero matrix (e.g., s)_k0); and if one or more of the Ks decoded signals passes the CRC circuit, BS102 may retrieve the various information contained in the respective decoded signals to obtain corresponding reconstructed signals.

Step 11, BS102 for each reconstructed signal

Estimating a corresponding channel gain systemNumber h_k，h_kCan be presented as N_RN_S×N_CAnd (4) matrix. In some embodiments, if the reconstructed signal is a zero matrix (as determined in step 10), BS102 may determine its corresponding channel gain coefficient to be zero (i.e., not perform the channel estimation process).

As described above, in various embodiments of the present disclosure, BS102 uses received signal y (spreading symbol y) to generate a correlation matrix (e.g.,

) And further using the correlation matrix to identify one or more UEs. Fig. 4A and 4B symbolically show how such a correlation matrix can be generated using a simplified example, where 2 UEs transmit a plurality of spreading symbols, respectively. In the embodiment shown in FIG. 4A, a first UE (1)^stUE) generation includes 5 (e.g., N as described above)_C) A sequence of modulation symbols 401 (e.g., a sequence d as described above)_C) Using a length-4 spreading sequence 403 (e.g., N as described above)_S) To generate a sequence 405 comprising 20 spreading symbols (e.g., sequence d as described above)_w) And transmits the sequence 405 over a channel 407. Similarly, a second UE (2)^ndUE) generation includes 5 (e.g., N as described above)_C) A sequence 411 of modulation symbols (e.g., a sequence d as described above)_C) Using a length of 4 (e.g., N as described above)_S) Generates a sequence 415 including 20 spreading symbols (e.g., sequence d as described above)_W) And sent over channel 417The sequence 415 is sent. In some embodiments, the spreading sequences used by the first and second UEs, respectively, may be the same or different from each other.

Still referring to fig. 4, after the first UE and the second UE transmit the

sequences

415 and 417 over

respective channels

407 and 417, the BS102 receives the

sequences

415 and 417 over the

channels

407 and 417 as a plurality of spreading symbols 431 (e.g., signal y as described above). In some embodiments, the spreading symbol 431 may be the sum of the transmitted

sequences

415 and 417. As described above, the spreading symbols 431 may be presented in a matrix form, which is shown as the matrix 433 shown in fig. 4B. Specifically, the matrix 433 has five columns 433-1, 433-2, 433-3, 433-4, and 433-5, each having 4 spreading symbols (which may be transmitted from the first and/or second UEs). In some embodiments, based on the above equations by examples 1-9, the correlation matrix may be calculated as:

this is also shown in the embodiment shown in fig. 4B. According to some embodiments, BS102 then processes the spreading symbols 431 using such a correlation matrix to identify the first and second UEs, as described above.

While various embodiments of the present invention have been described above, it should be understood that they have been presented by way of example only, and not limitation. Likewise, the various figures may depict example architectures or configurations provided to enable one of ordinary skill in the art to understand the example features and functionality of the present invention. However, those skilled in the art will appreciate that the invention is not limited to the example architectures or configurations illustrated, but can be implemented using a variety of alternative architectures and configurations. In addition, as one of ordinary skill in the art will appreciate, one or more features of one embodiment may be combined with one or more features of another embodiment described herein. Thus, the breadth and scope of the present disclosure should not be limited by any of the above-described exemplary embodiments.

It will also be understood that any reference herein to elements using a name such as "first," "second," etc., does not generally limit the number or order of those elements. Rather, these names may be used herein as a convenient means of distinguishing between two or more elements or instances of an element. Thus, reference to first and second elements does not mean that only two elements can be employed, or that the first element must precede the second element in some manner.

In addition, those of ordinary skill in the art would understand that information and signals may be represented using any of a variety of different technologies and techniques. For example, data, instructions, commands, information, signals, bits, and symbols that may be referenced throughout the above description may be represented by voltages, currents, electromagnetic waves, magnetic fields or particles, optical fields or particles, or any combination thereof.

Those of ordinary skill would further appreciate that any of the various illustrative logical blocks, modules, processors, means, circuits, methods, and functions described in connection with the aspects disclosed herein may be implemented as electronic hardware (e.g., a digital implementation, an analog implementation, or a combination of the two), firmware, various forms of process or design code incorporating instructions (which may be referred to herein, for convenience, as "software" or a "software module"), or any combination of these technologies. To clearly illustrate this interchangeability of hardware, firmware, and software, various illustrative components, blocks, modules, circuits, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware, firmware, or software, or combinations of such technologies, depends upon the particular application and design constraints imposed on the overall system. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present disclosure.

Furthermore, those of ordinary skill in the art will appreciate that the various illustrative logical blocks, modules, devices, components, and circuits described herein may be implemented within or performed by Integrated Circuits (ICs) that may include a general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, or any combination thereof. The logic blocks, modules, and circuits may also include antennas and/or transceivers to communicate with various components within the network or within the device. A general purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller or state machine. A processor may also be implemented as a combination of computing devices, e.g., a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other suitable configuration to perform the functions described herein.

If implemented in software, the functions may be stored as one or more instructions or code on a computer-readable medium. Thus, the steps of a method or algorithm disclosed herein may be implemented as software stored on a computer-readable medium. Computer-readable media includes both computer storage media and communication media including any medium that can communicate a computer process or code from one place to another. A storage media may be any available media that can be accessed by a computer. By way of example, and not limitation, such computer-readable media can comprise RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store desired process code in the form of instructions or data structures and that can be accessed by a computer.

In this document, the term "module" as used herein refers to any combination of software, firmware, hardware, and the like, for performing the associated functions described herein. Additionally, for purposes of discussion, the various modules are described as discrete modules; however, it will be apparent to one of ordinary skill in the art that two or more modules may be combined to form a single module that performs the associated functions in accordance with embodiments of the present invention.

Further, in embodiments of the present invention, memory or other storage and communication components may be employed. It will be appreciated that the above description for clarity has described embodiments of the invention with reference to different functional units and processors. It will be apparent, however, that any suitable distribution of functionality between different functional units, processing logic elements, or domains may be used without detracting from the invention. For example, functionality illustrated to be performed by separate processing logic elements or controllers may be performed by the same processing logic elements or controllers. Thus, references to specific functional units are only to references to suitable means for providing the described functionality rather than indicative of a strict logical or physical structure or organization.

Various modifications to the embodiments described in this disclosure will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the scope of the disclosure. Thus, the present disclosure is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the novel features and principles disclosed herein as set forth in the following claims.

Claims

1. A method comprising:

providing, by the first wireless communication node, a plurality of bits including the spreading sequence;

based on the spreading sequence, generating a plurality of spreading symbols; and

The plurality of spreading symbols are sent to perform a communication procedure initiated by the first wireless communication node.

2. The method of claim 1, wherein the communication procedure comprises at least one random access procedure.

3. The method of claim 1, wherein the plurality of bits further comprises one or more information bits to be transmitted by the first wireless communication node.

4. The method of claim 3, wherein the plurality of bits further comprises one or more cyclic redundancy check bits, and the spreading sequence is included in the one or more cyclic redundancy check bits bits or the one or more information bits.

5. The method of claim 1, wherein the plurality of bits further comprises a spreading sequence identification associated with the spreading sequence for identifying the spreading sequence from a plurality of preconfigured spreading sequences.

6. The method of claim 1, wherein the plurality of bits further comprises an identification of the first wireless communication node.

7. A computing device configured to perform the method of any of claims 1 to 6.

8. A non-transitory computer-readable medium having stored thereon computer-executable instructions for performing the method of any of claims 1-6.

9. A method performed by a first wireless communication node, comprising:

receiving a signal comprising a plurality of first spreading symbols;

Selecting a first subset from the plurality of preconfigured spreading sequences by using the signal to compute a metric for each of the plurality of preconfigured spreading sequences of the first subset; and

The signal is processed to identify at least one second wireless communication node based on the plurality of preconfigured spreading sequences of the first subset.

10. The method of claim 9, wherein a plurality of spreading symbols are generated based on a plurality of information bits transmitted by the second wireless communication node to perform a random access procedure.

11. The method of claim 9, wherein the plurality of first spreading symbols are sent by one or more wireless communication nodes, each of the wireless communication nodes requesting a corresponding random access procedure.

12. The method of claim 9, further comprising:

The plurality of first spreading symbols are received using a first antenna of the first wireless communication node.

13. The method of claim 12, wherein the metric is calculated based on a correlation matrix of the signal when the signal is presented in matrix form.

14. The method of claim 13, further comprising:

sorting the metrics of the plurality of preconfigured extension sequences in ascending order;

selects the first number of the smallest sorting metric; and

The first subset is determined to be some of the plurality of preconfigured spreading sequences having the first number of smallest ranking metrics.

15. The method of claim 13, further comprising:

Metrics for multiple preconfigured extended sequences are sorted in descending row order;

select the largest sorting measure of the first number; and

The first subset is determined to be some of the plurality of preconfigured spreading sequences having the first number of largest ranking metrics.

16. The method of claim 9, further comprising:

associating the signal with a plurality of preconfigured spreading sequences of the first subset to provide a plurality of measurement vectors;

equalizing the plurality of measurement vectors;

calculating a signal-to-interference-plus-noise ratio for each of the plurality of equalized measurement vectors; and

A subset is selected from the plurality of equalized measurement vectors, wherein each equalized measurement vector of the plurality of equalized measurement vectors of the one subset satisfies a predetermined condition.

17. The method of claim 16, further comprising:

decoding the signal using the plurality of equalized measurement vectors of the subset;

retrieving one or more spreading sequences used and identifying the at least one second wireless communication node based on the corresponding decoding results of the signal;

reconstructing the signal using the one or more used spreading sequences;

performing channel estimation based on each of the reconstructed signals; and

Interference cancellation is performed on the signal.

18. The method of claim 9, further comprising:

The signal is received using a first antenna and a second antenna of the first wireless communication node, wherein the plurality of first spreading symbols are received by the first antenna and are included in the signal by a plurality of first spreading symbols. Two spreading symbols are received by the second antenna.

19. The method of claim 18, further comprising:

weighting the plurality of first spreading symbols and the plurality of second spreading symbols, respectively; and

The weighted plurality of first spreading symbols and the weighted plurality of second spreading symbols are combined into a signal.

20. The method of claim 18, further comprising:

When the plurality of first extension symbols and the plurality of second extension symbols are respectively presented in matrix form, adding the plurality of first extension symbols in matrix form to the plurality of second extension symbols in matrix form as the signal.

21. The method of claim 18, wherein the metric is calculated based on a correlation matrix of the signal when the signal is presented in the matrix.

22. The method of claim 21, further comprising:

selects the first number of the smallest sorting metric; and

The first subset is determined to be some of a plurality of preconfigured spreading sequences having the first number of smallest ranking metrics.

23. The method of claim 21, further comprising:

sorting the metrics of the plurality of preconfigured extension sequences in descending order;

select the largest sorting measure of the first number; and

The first subset is determined to be some of a plurality of preconfigured spreading sequences having the first number of maximum ranking metrics.

24. The method of claim 21, further comprising:

The signal is associated with a plurality of preconfigured spreading sequences of the first subset to provide a plurality of measurement vectors.

25. The method of claim 24, further comprising:

Equalize multiple measurement vectors;

calculating a signal-to-interference-plus-noise ratio for each of the plurality of equalization measurement vectors; and

A subset is selected from the plurality of equalization measurement vectors, wherein each equalization measurement vector of the plurality of equalization measurement vectors in the one subset satisfies a predetermined condition.

26. The method of claim 25, further comprising:

reconstructing the signal using the one or more used spreading sequences;

performing channel estimation based on the reconstructed signal; and

Interference cancellation is performed on the signal.

27. A computing device configured to perform the method of any of claims 9 to 26.

28. A non-transitory computer readable medium having stored thereon computer executable instructions for performing the method of any of claims 9 to 26.