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WO2025015448A1 - Procédé, dispositif, et support pour une classification d'interférence - Google Patents

Procédé, dispositif, et support pour une classification d'interférence Download PDF

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Publication number
WO2025015448A1
WO2025015448A1 PCT/CN2023/107449 CN2023107449W WO2025015448A1 WO 2025015448 A1 WO2025015448 A1 WO 2025015448A1 CN 2023107449 W CN2023107449 W CN 2023107449W WO 2025015448 A1 WO2025015448 A1 WO 2025015448A1
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WIPO (PCT)
Prior art keywords
interference
target cell
cell
characteristic
neighbor
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
PCT/CN2023/107449
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English (en)
Other versions
WO2025015448A8 (fr
Inventor
Hui Wang
Junwen Li
Chengbin WANG
Lei Zhang
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Telefonaktiebolaget LM Ericsson AB
Original Assignee
Telefonaktiebolaget LM Ericsson AB
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
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Publication date
Application filed by Telefonaktiebolaget LM Ericsson AB filed Critical Telefonaktiebolaget LM Ericsson AB
Priority to PCT/CN2023/107449 priority Critical patent/WO2025015448A1/fr
Publication of WO2025015448A1 publication Critical patent/WO2025015448A1/fr
Publication of WO2025015448A8 publication Critical patent/WO2025015448A8/fr
Pending legal-status Critical Current
Anticipated expiration legal-status Critical

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Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/30—Monitoring; Testing of propagation channels
    • H04B17/309—Measuring or estimating channel quality parameters
    • H04B17/345—Interference values
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/20—Monitoring; Testing of receivers
    • H04B17/27—Monitoring; Testing of receivers for locating or positioning the transmitter

Definitions

  • Various embodiments of the present disclosure generally relate to the field of telecommunication and in particular, to a method, device and computer readable storage medium for interference classification.
  • the term “terminal device” refers to a device which is intended for accessing services via an access network and configured to communicate over the access network.
  • the terminal device may be able to communicate with a network node, such as a base station, or with another terminal device by transmitting and/or receiving wireless signals.
  • the terminal device may include, but is not limited to: a mobile phone, a smart phone, a sensor device, a meter, a vehicle, a household appliance, a medical appliance, a media player, a camera, or any type of consumer electronic, for instance, but not limited to, a television, radio, lighting arrangement, a tablet computer, a laptop, or a personal computer (PC) .
  • PC personal computer
  • the terminal device may also include a portable, pocket-storable, hand-held, computer-comprised, or vehicle-mounted mobile device, enabled to communicate voice and/or data, via a wireless connection.
  • a portable, pocket-storable, hand-held, computer-comprised, or vehicle-mounted mobile device enabled to communicate voice and/or data, via a wireless connection.
  • the terms “terminal device” , “user equipment” and “UE” may be used interchangeably.
  • Some embodiments of the present disclosure propose an interference classification scheme.
  • the proposed scheme determines an interface type of a target cell based on evaluation of similarities between an interference characteristic of the target cell and the interference characteristics of neighbor cells of the target cell. In this way, the cells with different interference characteristics may be accurately identified, thereby improving accuracy of interference classification. Further, the identification of root causes of the interferences and the positioning of interference sources may be improved.
  • the proposed scheme is originating from a scenario of the uplink interferences
  • the proposed scheme herein may be applied in general for any interference such as a downlink interference in the communication network.
  • some example embodiments will be described using the uplink interferences as an example implementation of the interferences while the example embodiments herein can be applied in general for any other interferences.
  • FIG. 1 illustrates an example communication environment 100 in which embodiments of the present disclosure can be implemented.
  • the communication environment 100 which may be a part of a communication system, comprises a network node 110 that serves a coverage area, called a cell 115.
  • the communication environment 100 further comprises one or more neighbor network nodes 120-1, ..., 120-N of the network node 110, which serve one or more neighbor cells 125-1, ..., 125-N.
  • N represents any positive integer.
  • UEs 130-1, 130-2, ..., 130-M can communicate with the network nodes 110 and 120-1, ..., 120-N and have access to a communication network via the network nodes 110 and 120-1, ..., 120-N.
  • M represents any positive integer.
  • the UEs 130-1, 130-2, ..., 130-M may communicate with each other directly or via the network nodes 110 and 120-1, ..., 120-N. Communications in the environment 100 may be implemented according to any communication protocols and technologies that already exist or is to be developed in the future.
  • one network node may serve more cells.
  • the network node 110 may serve the cell 115 and one or more of the neighbor cells 120-1, ..., 120-N.
  • Neighbor cells may comprise cells that are configured to have neighbor relations with each other or that are geographically adjacent or close to each other.
  • the neighbor cells of a certain cell may comprise cells that have higher measurement values in measurement reports of the cell.
  • the neighbor cells of a certain cell may comprise one or more neighbor cells preconfigured based on the neighbor relations of the cell.
  • the cells may be subject to various interferences.
  • an external interference source may comprise a signal jammer in special places (such as a gas station or an examination hall) , an illegal repeater and any other interference source that is outside of the system.
  • the external interference may affect many cells in the system.
  • Some interferences in the communication environment 100 may be associated with a site infrastructure in a cell. Such interferences will also be referred to as site infrastructure issue caused interferences. These interferences may be caused by equipment, devices, elements or units in the cell, which may comprise interferences caused by hardware faults of radio remote units (RRUs) or cable or feeder performance erosion. Such interferences may affect the cell itself or co-located cells with common equipment.
  • RRUs radio remote units
  • the LTE and NR systems are both co-frequency communication systems. Due to the use of an Orthogonal Frequency Division Multiplexing (OFDM) technology, interferences between different transmissions in a cell may be avoided, but there may be interferences between neighbor cells. Especially in areas with high traffic loads, the interferences of a cell will rise due to transmissions of surrounding or adjacent cells. This type of interferences is called an interference caused by a traffic load, also referred to as a traffic load caused interference.
  • OFDM Orthogonal Frequency Division Multiplexing
  • an interference of a target cell such as the cell 115 is classified based on the similarities between the interference characteristics of the target cell and the neighbor cells such as the neighbor cells 125-1, ..., 125-N.
  • the external interferences will affect a plurality of cells in an area.
  • Interference received power caused by the same external interference source may vary with distances from cells to the interference source, but the interference characteristics of these cells in the same area may be similar.
  • Cells with the highly similar interference characteristics may be identified through the similarity evaluation for the interference characteristics of the cells. Accordingly, the external interferences may be identified.
  • the interference caused by a site infrastructure issue of a cell may affect only the cell itself or co-located cells with common equipment. Accordingly, if the interference characteristic of the target cell has a lower similarity to the interference characteristics of other cells in the area, the type of interference in the target cell may be determined as a site infrastructure issue caused interference. Thus, based on the similarity evaluation of the interference characteristics, the types of interferences in the target cell may be identified in a more effective and efficient way.
  • FIG. 2A shows a flowchart of an example method 200 of interference classification in accordance with some embodiments of the present disclosure. For the purpose of discussion, the method 200 will be described with reference to FIG. 1.
  • a neighbor cell such as the neighbor cell 125-1
  • one or more neighbor cells such as the neighbor cell 125-1, ..., 125-N
  • a target cell such as the cell 115
  • a similarity between an interference characteristic of the target cell and an interference characteristic of the neighbor cell is obtained.
  • the interference characteristic of the target cell will be referred to as a first interference characteristic
  • the interference characteristic of a neighbor cell will be referred to as a second interference characteristic.
  • the first and second interference characteristics may comprise interference characteristics in either a time domain or a frequency domain.
  • the first and second interference characteristics may comprise interference characteristics in both the time and frequency domains.
  • the similarity between the first and second interference characteristics may be obtained in at least one time period and on at least one PRB.
  • FIGS. 2B and 2C shows heat maps 212 and 214 of interference time-frequency patterns (ITFP) of two cells, referred to as Cell A and Cell B, respectively.
  • Cell A and Cell B are geographically close.
  • the interferences of both cells have obvious time-varying characteristics.
  • Table 1 shows results of similarity evaluation for the two cells.
  • the similarity evaluation in the frequency domain is less accurate for the interference of time-varying characteristics.
  • the similarity evaluation in the time and frequency domain based on the interference time-frequency domain information has higher accuracy.
  • a PRB-level uplink interference power statistics per recording output period may be obtained. Accordingly, both the frequency-domain and time-domain information of the uplink interferences may be obtained, which may allow the detection of the uplink interference pattern in the time and frequency domains.
  • a ROP is used as the minimum granularity in the time domain and a PRB is used as the minimum granularity in the frequency domain.
  • An interference time-frequency pattern is an example implementation of the interference characteristic. The similarity of the interference patterns based on the interference time-frequency domain information is calculated as follows:
  • A represents an ITFP of the target cell
  • B represents an ITFP of the first neighbor cell
  • m represents the number of PRBs in an operating bandwidth
  • n represents the number of ROPs. It is also possible that one ROP or one PRB is considered in the similarity evaluation. For example, the result derived from equation (1) may be averaged per ROP or per PRB to obtain the similarity for each ROP or for each PRB.
  • an interference type of the target cell is determined at least based on the similarity obtained for the first neighbor cell.
  • the determination of the interference type may be performed based on a comparison of the similarity with one or more threshold similarities. In an example, if it is determined that the similarity obtained for the first neighbor cell is equal to or higher than a threshold similarity (referred to as a first threshold similarity) , then the interference type of the target cell may be determined as an external interference.
  • a threshold similarity referred to as a first threshold similarity
  • the similarity evaluation may be performed for more neighbor cells. Accordingly, the interference type of the target cell may be determined based on the results of the similarity evaluation for more neighbor cells.
  • a threshold similarity (referred to as a second threshold similarity)
  • the interference type of the target cell is an interference associated with a site infrastructure in the target cell.
  • the second threshold similarity may or may not be the same as the first threshold similarity.
  • the second threshold similarity is lower than the first threshold similarity to more accurately distinguish between the external interference and the interference associated with the site infrastructure.
  • the interference classification may be based on relevance (or correlation) of an interference characteristic of the target cell with a traffic load characteristic of a surrounding area (or adjacent area) covered by the one or more neighbor cells of the target cell.
  • the traffic load characteristic of the surrounding area may comprise variations of traffic loads of the surrounding area over time.
  • the interference characteristic of the target cell used for the relevance evaluation will be referred to as a third interference characteristic of the target cell.
  • the third interference characteristic may comprise an interference characteristic in the time domain.
  • the relevance of the third interference characteristic of the target cell with the traffic load characteristic of the surrounding area may be obtained in a number of time periods.
  • high traffic loads of the surrounding cells may cause the interferences (such as an interference noise floor) of a cell to rise.
  • the relevance of the third interference characteristic of the target cell with the traffic load characteristic of the surrounding area may reflect a level of interferences of the target cell caused by traffic loads of the surrounding area. Accordingly, based on this relevance, a traffic load caused interference may be identified. For example, if the correlation is high, the interference may be the traffic load caused interference.
  • Usage of PRBs of a cell may reflect the traffic loads of the cell.
  • the traffic load characteristic of the surrounding area may be determined at least based on usage of PRBs for a neighbor cell of one or more neighbor cells of the target cell. Any other metrics related to the traffic load characteristic may be adopted.
  • the neighbor cell for the relevance evaluation will be referred to as a second neighbor cell.
  • the second neighbor cell may or may not be the same as the first neighbor cell in the similarity evaluation for the interference characteristics of the target cells and its neighbor cell (s) , as described above.
  • Proximity between radio signals of cells may affect a level of inter-cell interferences.
  • proximity between a radio signal of the target cell and a radio signal of the second neighbor cell may be used for weighting of the usage of PRBs for the second neighbor cell to further improve the performance of the interference classification.
  • the RF closeness of the target cell and the second neighbor cell may be determined based on measurement reports collected or received in the second neighbor cell. In an example, if the radio signals of the target cell and the second neighbor cell is closer, then more measurement values of the target cell may be included in the measurement reports collected in the second neighbor cell. Accordingly, a ratio of a number (referred to as a first number) of measurement reports, each including a measurement value of the target cell equal to or greater than a threshold value, and a number (referred to as a second number) of measurement reports collected in the second neighbor cell (the total number of measurement reports received in the second neighbor cell) may reflect the RF closeness of the target cell and the second neighbor cell. In this example, the RF closeness of the target cell and the second neighbor cell may be determined based on the ratio of the first and second numbers.
  • the measurement value of the target cell may be represented in any suitable form of metrics.
  • the measurement value of the target cell may comprise a received signal strength, a reference signal receiving power (RSRP) , a reference signal receiving quality (RSRQ) , a reference signal strength indicator (RSSI) , a signal to interference plus noise ratio (SINR) and/or other measurement results of the target cell.
  • the threshold value to be compared with the measurement value may be set depending on the specific implementations and/or network deployments.

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  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Electromagnetism (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Quality & Reliability (AREA)
  • Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
  • Apparatus Associated With Microorganisms And Enzymes (AREA)
  • Mobile Radio Communication Systems (AREA)

Abstract

Des modes de réalisation de la présente divulgation concernent un procédé, un dispositif, et un support de stockage lisible par ordinateur pour une classification d'interférence. Dans le procédé, pour une première cellule voisine d'une ou plusieurs cellules voisines d'une cellule cible, une similarité entre une première caractéristique d'interférence de la cellule cible et une seconde caractéristique d'interférence de la première cellule voisine est obtenue. Un type d'interférence de la cellule cible est déterminé au moins sur la base de la similarité obtenue pour la première cellule voisine.
PCT/CN2023/107449 2023-07-14 2023-07-14 Procédé, dispositif, et support pour une classification d'interférence Pending WO2025015448A1 (fr)

Priority Applications (1)

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PCT/CN2023/107449 WO2025015448A1 (fr) 2023-07-14 2023-07-14 Procédé, dispositif, et support pour une classification d'interférence

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
PCT/CN2023/107449 WO2025015448A1 (fr) 2023-07-14 2023-07-14 Procédé, dispositif, et support pour une classification d'interférence

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WO2025015448A1 true WO2025015448A1 (fr) 2025-01-23
WO2025015448A8 WO2025015448A8 (fr) 2025-06-12

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Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20170257787A1 (en) * 2014-08-21 2017-09-07 Telefonaktiebolaget Lm Ericsson (Publ) Received Signal Strength Based Interferer Classification of Cellular Network Cells
CN107888318A (zh) * 2016-09-30 2018-04-06 中国移动通信有限公司研究院 干扰分析方法及装置
CN113556774A (zh) * 2021-07-14 2021-10-26 中国电信股份有限公司 移动网络的干扰定位方法、装置、设备以及存储介质
CN115379477A (zh) * 2022-08-10 2022-11-22 中国联合网络通信集团有限公司 确定小区干扰类型的方法、装置、设备及存储介质
WO2023005727A1 (fr) * 2021-07-30 2023-02-02 华为技术有限公司 Procédé de détection d'interférence, et dispositif

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20170257787A1 (en) * 2014-08-21 2017-09-07 Telefonaktiebolaget Lm Ericsson (Publ) Received Signal Strength Based Interferer Classification of Cellular Network Cells
CN107888318A (zh) * 2016-09-30 2018-04-06 中国移动通信有限公司研究院 干扰分析方法及装置
CN113556774A (zh) * 2021-07-14 2021-10-26 中国电信股份有限公司 移动网络的干扰定位方法、装置、设备以及存储介质
WO2023005727A1 (fr) * 2021-07-30 2023-02-02 华为技术有限公司 Procédé de détection d'interférence, et dispositif
CN115379477A (zh) * 2022-08-10 2022-11-22 中国联合网络通信集团有限公司 确定小区干扰类型的方法、装置、设备及存储介质

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