WO2021174908A1 - 毫米波系统优化覆盖的方法及装置、电子设备及存储介质 - Google Patents

毫米波系统优化覆盖的方法及装置、电子设备及存储介质 Download PDF

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WO2021174908A1
WO2021174908A1 PCT/CN2020/129062 CN2020129062W WO2021174908A1 WO 2021174908 A1 WO2021174908 A1 WO 2021174908A1 CN 2020129062 W CN2020129062 W CN 2020129062W WO 2021174908 A1 WO2021174908 A1 WO 2021174908A1
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optimal
energy optimization
codebook
codebooks
value
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PCT/CN2020/129062
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English (en)
French (fr)
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刘明
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中兴通讯股份有限公司
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Priority to EP20922739.6A priority Critical patent/EP4117330A4/en
Publication of WO2021174908A1 publication Critical patent/WO2021174908A1/zh

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W76/00—Connection management
    • H04W76/20—Manipulation of established connections
    • H04W76/28—Discontinuous transmission [DTX]; Discontinuous reception [DRX]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W16/00—Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
    • H04W16/18—Network planning tools
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/0413—MIMO systems
    • H04B7/0456—Selection of precoding matrices or codebooks, e.g. using matrices antenna weighting
    • 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
    • H04B17/318—Received signal strength
    • H04B17/327—Received signal code power [RSCP]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/30—Monitoring; Testing of propagation channels
    • H04B17/382—Monitoring; Testing of propagation channels for resource allocation, admission control or handover
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

Definitions

  • the present disclosure relates to the field of mobile communications, and in particular to a method and device for optimizing coverage of a millimeter wave system, electronic equipment, and a storage medium.
  • 5G Fifth Generation
  • the beam (Beam) used by the air interface of the 5G millimeter wave (mmWAVE) system adopts hybrid analog shaping, by loading different codebooks (Codebook) in the AAU (Active Antenna Unit). Provide beam enable in different directions to bring coverage gain.
  • Codebook codebooks
  • beams have the following characteristics: (1) The more codebook beams, the wider and finer the coverage. (2) The larger the number of codebook beams, the higher the requirements for the equipment's hardware and software processing capabilities, and the longer the beam scanning and pairing time is.
  • the beams under different codebooks are different. Using different beam codebooks in the same wireless environment will produce completely different coverage situations, and the signal coverage and service performance of UEs in the same location vary greatly. The selection and optimization of codebooks are important issues facing millimeter wave system testing and networking coverage.
  • the tester manually selects the codebook and loads it to AAU by estimating the coverage of the wireless environment. And artificially place the UE to a position facing the AAU direction, and obtain the result that the UE is basically within the coverage of the main lobe of the beam.
  • the number of UEs increases and is randomly distributed, or UEs move to other locations.
  • the UE is very easy to be in the sidelobe coverage of the beam, resulting in weak coverage. This will cause the UE to receive poor signals, poor performance, and poor user experience.
  • embodiments of the present disclosure provide a method and device for optimizing coverage of a millimeter wave system, an electronic device, and a storage medium.
  • a method for optimizing coverage of a millimeter wave system including:
  • the codebook corresponding to the optimal energy optimization value is determined as the optimal codebook in the current scenario.
  • a device for optimizing coverage of a millimeter wave system is provided.
  • the device is applied to the method for optimizing coverage of a millimeter wave system according to an embodiment of the present disclosure, and the device includes: statistics Module, select module, confirm module, among them:
  • the statistics module is used to count the energy optimization values of the optimal beams of all UEs received by the cells under all codebooks to obtain a set of energy optimization values of all codebooks;
  • the selection module is configured to select an optimal energy optimization value from the energy optimization value set according to a preset optimal selection strategy
  • the determining module is configured to determine the codebook corresponding to the optimal energy optimization value as the optimal codebook in the current scenario.
  • an electronic device including: a storage memory, a processor, and a computer program stored on the memory and capable of running on the processor, and the computer program is When the processor is executed, the steps of the method for optimizing coverage of the millimeter wave system provided by the embodiments of the present disclosure are implemented.
  • a computer-readable storage medium stores a program of a method for optimizing coverage of a millimeter wave system, and the method for optimizing coverage of a millimeter wave system is When the program is executed by the processor, the steps of the method for optimizing coverage of the millimeter wave system provided by the embodiment of the present disclosure are implemented.
  • FIG. 1 is a schematic diagram of millimeter wave beam coverage provided by an embodiment of the present disclosure
  • FIG. 2 is a schematic flowchart of a method for optimizing coverage of a millimeter wave system according to an embodiment of the present disclosure
  • FIG. 3 is a schematic structural diagram of an apparatus for optimizing coverage of a millimeter wave system according to an embodiment of the present disclosure
  • FIG. 4 is a schematic flowchart of a method for optimizing coverage of a millimeter wave system according to an embodiment of the present disclosure
  • FIG. 5 is a schematic flowchart of another method for optimizing coverage of a millimeter wave system according to an embodiment of the present disclosure
  • FIG. 6 is a schematic structural diagram of an electronic device provided by an embodiment of the disclosure.
  • module means, “part” or “unit” used to indicate elements is only for facilitating the description of the present disclosure, and has no specific meaning in itself. Therefore, “module”, “part” or “unit” can be used in a mixed manner.
  • the present disclosure proposes a scheme for optimizing codebooks in a millimeter wave system to improve coverage.
  • the scheme can be used for beam codebook configuration in different scenarios in a 5G millimeter wave system, and affects coverage performance and service performance in different scenarios.
  • the present disclosure provides a method for optimizing coverage of a millimeter wave system, and the method includes:
  • the user terminal equipment UE generally refers to the user terminal equipment in the 5G millimeter wave system.
  • the energy optimization value set of all codebooks is formed by counting the energy optimization values of the optimal beams of all UEs received by the cells in all codebooks, and the energy optimization value set is based on the preset optimal value. Select the strategy to select the optimal energy optimization value, you can filter out the optimal codebook suitable for the current scenario, use the optimal codebook, improve the cell capacity, the cell provides better access and services, can provide better UE Signal coverage can cover more UEs, improve the service performance of UEs, and thus improve user experience.
  • the technology provided in this embodiment can be used for beam codebook configuration in different scenarios, affecting coverage performance and service performance in different scenarios, considering the real application scenarios of cell coverage and user distribution after the communication system is commercialized, according to the distribution of terminal UEs choose to load the beam codebook that conforms to the current UE distribution, thereby improving the overall coverage and performance of the network.
  • the energy optimization value is an energy accumulation value.
  • the energy optimization values of the optimal beams of all UEs received by the cells under all codebooks are counted to obtain the energy optimization value set of all codebooks, including: statistics on all UEs received by the cells under all codebooks
  • the energy cumulative value of the optimal beam is obtained, and the energy cumulative value set of all codebooks is obtained.
  • the energy optimization value is an energy average value.
  • the energy optimization values of the optimal beams of all UEs received by the cells under all codebooks are counted to obtain the energy optimization value set of all codebooks, including: statistics on all UEs received by the cells under all codebooks
  • the energy average value of the optimal beam is obtained, and the energy average value set of all codebooks is obtained.
  • the statistics of the energy optimization values of the optimal beams of all UEs received by the cells under all the codebooks, to obtain the energy optimization value set of all the codebooks including:
  • the statistics of the RSRP energy optimization values of the optimal beams of all UEs received by the cell under one codebook include:
  • the base station counts the RSRP energy optimization value R of the best beams of all UEs received during the beam pairing process.
  • the larger the R value the larger the number of UEs that can be accessed under the current beam codebook or the strong energy.
  • f is the length of the codebook timer, and the unit can provide four options of second/minute/hour/day, which can be set as required. The larger the f, the more accurate the collected data, and the longer it takes to traverse all codebooks at the same time.
  • the energy optimization value is the energy accumulation value
  • the RSRP energy accumulation value set (R1, R2...Rn) under each codebook is obtained according to the method of the above-mentioned embodiment.
  • the energy optimization value is the energy average value
  • the RSRP energy average set (R1, R2...Rn) under each codebook is obtained according to the method of the above-mentioned embodiment.
  • the base station by counting the number of codebooks, selecting another codebook, starting the codebook timer t, the base station counts the energy optimization values of the best beams of all UEs received during the beam pairing process and accumulates them. After resetting the device to zero, it stops, and the energy optimization value of the optimal beam of all UEs received by the cell under the codebook is obtained.
  • the energy optimization value set of all codebooks is obtained, so that the energy optimization value set can be selected according to the preset optimal selection strategy Optimal energy optimization value, filter out the optimal codebook suitable for the current scenario, use the optimal codebook, increase the cell capacity, the cell provides better access and services, can provide better signal coverage for the UE, can cover more With more UEs, the service performance of the UEs is improved, thereby improving the user experience.
  • the technology provided in this embodiment can be used for beam codebook configuration in different scenarios, affecting coverage performance and service performance in different scenarios, considering the real application scenarios of cell coverage and user distribution after the communication system is commercialized, according to the distribution of terminal UEs choose to load the beam codebook that conforms to the current UE distribution, thereby improving the overall coverage and performance of the network.
  • the preset optimal selection strategy is a maximum value selection strategy
  • the optimal energy optimization value is selected according to the preset optimal selection strategy from the energy optimization value set, include:
  • the energy optimization value set of all the codebooks is formed by counting the energy optimization values of the optimal beams of all UEs received by the cells under all codebooks, and the comparison is performed to select the energy optimization value with the largest energy optimization value.
  • the optimal energy optimization value the optimal codebook suitable for the current scenario corresponding to the optimal energy optimization value can be screened out, and the optimal codebook can be used to improve the cell capacity and provide better access and services to the cell.
  • the UE provides better signal coverage, can cover more UEs, and improve the service performance of the UEs, thereby improving user experience.
  • the technology provided in this embodiment can be used for beam codebook configuration in different scenarios, affecting coverage performance and service performance in different scenarios, considering the real application scenarios of cell coverage and user distribution after the communication system is commercialized, according to the distribution of terminal UEs choose to load the beam codebook that conforms to the current UE distribution, thereby improving the overall coverage and performance of the network.
  • the method further includes: loading the determined optimal codebook into an AAU system for operation.
  • the AAU Active Antenna Unit, integrated active antenna unit
  • the AAU is an equipment module that integrates signal processing and radio frequency input and output in a 5G millimeter wave system.
  • the determined optimal codebook is loaded into the AAU system for operation, so that the cell capacity can be improved, the cell can provide better access and services, and can provide better signal coverage for the UE, and can cover More UEs improve the service performance of UEs, thereby improving user experience.
  • the technology provided in this embodiment can be used for beam codebook configuration in different scenarios, which affects coverage performance and service performance in different scenarios.
  • the present disclosure provides a device for optimizing coverage of a millimeter wave system.
  • the device includes: a statistics module 10, a selection module 20, and a determination module 30; wherein:
  • the statistics module 10 is configured to count the energy optimization values of the optimal beams of all UEs received by cells in all codebooks, and obtain a set of energy optimization values of all codebooks.
  • the selection module 20 is configured to select an optimal energy optimization value from the energy optimization value set according to a preset optimal selection strategy.
  • the determining module 30 is configured to determine the codebook corresponding to the optimal energy optimization value as the optimal codebook in the current scenario.
  • the user terminal equipment UE generally refers to the user terminal equipment in the 5G millimeter wave system.
  • the energy optimization value set of all codebooks is formed by counting the energy optimization values of the optimal beams of all UEs received by the cells in all codebooks, and the energy optimization value set is based on the preset optimal value. Select the strategy to select the optimal energy optimization value, you can filter out the optimal codebook suitable for the current scenario, use the optimal codebook, improve the cell capacity, the cell provides better access and services, can provide better UE Signal coverage can cover more UEs, improve the service performance of UEs, and thus improve user experience.
  • the technology provided in this embodiment can be used for beam codebook configuration in different scenarios, affecting coverage performance and service performance in different scenarios, considering the real application scenarios of cell coverage and user distribution after the communication system is commercialized, according to the distribution of terminal UEs choose to load the beam codebook that conforms to the current UE distribution, thereby improving the overall coverage and performance of the network.
  • the energy optimization value is an energy accumulation value.
  • the statistics module 10 is specifically configured to: count the cumulative energy values of the optimal beams of all UEs received by the cells under all codebooks, and obtain a set of cumulative energy values of all codebooks.
  • the energy optimization value is an energy average value.
  • the statistics module 10 is specifically configured to: count the energy average values of the optimal beams of all UEs received by the cells under all codebooks to obtain a set of energy average values of all codebooks.
  • the statistics module 10 is specifically configured to:
  • the statistics of the RSRP energy optimization values of the optimal beams of all UEs received by the cell under one codebook include:
  • the base station counts the RSRP energy optimization value R of the best beams of all UEs received during the beam pairing process.
  • the larger the R value the larger the number of UEs that can be accessed under the current beam codebook or the strong energy.
  • f is the length of the codebook timer, and the unit can provide four options of second/minute/hour/day, which can be set as required. The larger the f, the more accurate the collected data, and the longer it takes to traverse all codebooks at the same time.
  • the base station by counting the number of codebooks, selecting another codebook, starting the codebook timer t, the base station counts the energy optimization values of the best beams of all UEs received during the beam pairing process and accumulates them. After resetting the device to zero, it stops, and the energy optimization value of the optimal beam of all UEs received by the cell under the codebook is obtained.
  • the energy optimization value set of all codebooks is obtained, so that the energy optimization value set can be selected according to the preset optimal selection strategy Optimal energy optimization value, filter out the optimal codebook suitable for the current scenario, use the optimal codebook, increase the cell capacity, the cell provides better access and services, can provide better signal coverage for the UE, can cover more With more UEs, the service performance of the UEs is improved, thereby improving the user experience.
  • the technology provided in this embodiment can be used for beam codebook configuration in different scenarios, which affects coverage performance and service performance in different scenarios.
  • the preset optimal selection strategy is a maximum value selection strategy
  • the selection module 20 is specifically configured to:
  • the energy optimization value set of all the codebooks is formed by counting the energy optimization values of the optimal beams of all UEs received by the cells under all codebooks, and the comparison is performed to select the energy optimization value with the largest energy optimization value.
  • the optimal energy optimization value the optimal codebook corresponding to the optimal energy optimization value suitable for the current scenario can be screened out, and the optimal codebook can be used to increase the cell capacity and provide better access and services to the cell.
  • the UE provides better signal coverage, can cover more UEs, and improve the service performance of the UEs, thereby improving user experience.
  • the technology provided in this embodiment can be used for beam codebook configuration in different scenarios, which affects coverage performance and service performance in different scenarios.
  • the device further includes: a loading module configured to load the determined optimal codebook into an AAU system for operation.
  • the AAU system is an equipment module that integrates signal processing and radio frequency input and output in a 5G millimeter wave system.
  • the determined optimal codebook is loaded into the AAU system for operation, so that the cell capacity can be improved, the cell can provide better access and services, and can provide better signal coverage for the UE, and can cover More UEs improve the service performance of UEs, thereby improving user experience.
  • the technology provided in this embodiment can be used for beam codebook configuration in different scenarios, affecting coverage performance and service performance in different scenarios, considering the real application scenarios of cell coverage and user distribution after the communication system is commercialized, according to the distribution of terminal UEs choose to load the beam codebook that conforms to the current UE distribution, thereby improving the overall coverage and performance of the network.
  • the present disclosure provides a method for optimizing coverage of a millimeter wave system.
  • the energy optimization value is described by taking the energy accumulation value as an example.
  • the present disclosure provides a method for optimizing coverage of a millimeter wave system, and the method includes:
  • Step S503 Load the codebook, and the codebook timer t starts timing. Step S504 is executed.
  • Step S504 The base station counts the accumulated energy values of the best beams of all UEs received during the beam pairing process, and the accumulated energy values are counted as R. The larger the R value, the larger the number of UEs that can be accessed under the current beam codebook or the strong energy. Step S505 is executed.
  • the accumulated energy value R of RSRP is stored.
  • f is the length of the codebook timer, and the unit can provide four options of second/minute/hour/day, which can be set as required. The larger the f, the more accurate the collected data, and the longer it takes to traverse all codebooks at the same time. Step S506 is executed.
  • Step S509 Compare the energy accumulation value sets (R1, R2...Rn), and select the energy accumulation value with the largest energy accumulation value in the energy accumulation value set as the optimal energy accumulation value. Step S510 is executed.
  • Step S510 Determine the codebook corresponding to the optimal energy accumulation value as the optimal codebook in the current scenario. Step S511 is executed.
  • Step S511 Load the determined optimal codebook into the AAU system for operation. Step S512 is executed.
  • the codebook timer t is turned on, and the base station counts the accumulated energy values of the best beams of all UEs received during the beam pairing process, and the timer is set Stop after zero, and obtain the cumulative value of the energy of the optimal beams of all UEs received by the cell under the codebook.
  • the energy cumulative value set of all codebooks is obtained, so that the energy cumulative value set can be selected according to the preset optimal selection strategy
  • the optimal energy accumulation value, the codebook corresponding to the optimal energy accumulation value is determined as the optimal codebook suitable for the current scenario, and the optimal codebook is used to increase the cell capacity and provide better access and services for the cell, It can provide better signal coverage for UEs, cover more UEs, and improve the service performance of UEs, thereby enhancing user experience.
  • the technology provided in this embodiment can be used for beam codebook configuration in different scenarios, affecting coverage performance and service performance in different scenarios, considering the real application scenarios of cell coverage and user distribution after the communication system is commercialized, according to the distribution of terminal UEs choose to load the beam codebook that conforms to the current UE distribution, thereby improving the overall coverage and performance of the network.
  • the present disclosure provides a method for optimizing coverage of a millimeter wave system.
  • the energy optimization value is described by taking an energy average value as an example.
  • the present disclosure provides a method for optimizing coverage of a millimeter wave system, and the method includes:
  • Step S604 Load the codebook, and the codebook timer t starts timing. Step S604 is executed.
  • Step S604 The base station counts the energy average value of the best beams of all UEs received during the beam pairing process, and the energy average value is calculated as R. The larger the R value, the larger the number of UEs that can be accessed under the current beam codebook or the strong energy. Step S605 is executed.
  • f is the length of the codebook timer, and the unit can provide four options of second/minute/hour/day, which can be set as required. The larger the f, the more accurate the collected data, and the longer it takes to traverse all codebooks at the same time. Step S606 is executed.
  • Step S609 Compare the energy average set (R1, R2...Rn), and select the energy average with the largest energy average in the energy average set as the optimal energy average. Step S610 is executed.
  • Step S610 Determine the codebook corresponding to the optimal energy average value as the optimal codebook in the current scenario. Step S611 is executed.
  • Step S611 Load the determined optimal codebook into the AAU system for operation.
  • Step S612 is executed.
  • the energy average value set of all codebooks is obtained, so that the energy average value set can be selected according to the preset optimal selection strategy Optimal energy average value, filter out the optimal codebook suitable for the current scenario, use the optimal codebook, increase the cell capacity, the cell provides better access and services, can provide better signal coverage for the UE, can cover more With more UEs, the service performance of the UEs is improved, thereby improving the user experience.
  • the technology provided in this embodiment can be used for beam codebook configuration in different scenarios, affecting coverage performance and service performance in different scenarios, considering the real application scenarios of cell coverage and user distribution after the communication system is commercialized, according to the distribution of terminal UEs choose to load the beam codebook that conforms to the current UE distribution, thereby improving the overall coverage and performance of the network.
  • an embodiment of the present disclosure also provides an electronic device.
  • the electronic device 900 includes a memory 902, a processor 901, and is stored in the memory 902 and can run on the processor 901.
  • the memory 902 and the processor 901 are coupled together through the bus system 903, and the one or more computer programs are executed by the processor 901 to realize the The following steps of a method for optimizing coverage of a millimeter wave system:
  • the methods disclosed in the foregoing embodiments of the present disclosure may be applied to the processor 901 or implemented by the processor 901.
  • the processor 901 may be an integrated circuit chip with signal processing capability. In the implementation process, the steps of the foregoing method can be completed by an integrated logic circuit of hardware in the processor 901 or instructions in the form of software.
  • the processor 901 may be a general-purpose processor, a DSP, or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, and the like.
  • the processor 901 may implement or execute various methods, steps, and logical block diagrams disclosed in the embodiments of the present disclosure.
  • the general-purpose processor may be a microprocessor or any conventional processor or the like.
  • the steps of the method disclosed in the embodiments of the present disclosure may be directly embodied as being executed and completed by a hardware decoding processor, or executed and completed by a combination of hardware and software modules in the decoding processor.
  • the software module may be located in a storage medium, and the storage medium is located in the memory 902.
  • the processor 901 reads the information in the memory 902 and completes the steps of the foregoing method in combination with its hardware.
  • the memory 902 of the embodiment of the present disclosure may be a volatile memory or a non-volatile memory, and may also include both volatile and non-volatile memory.
  • the non-volatile memory can be read-only memory (ROM, Read-Only Memory), programmable read-only memory (PROM, Programmable Read-Only Memory), and erasable programmable read-only memory (EPROM, Erasable Read-Only Memory).
  • RAM Random Access Memory
  • SRAM Static Random Access Memory
  • SSRAM static random access memory
  • DRAM Dynamic Random Access Memory
  • SDRAM Synchronous Dynamic Random Access Memory
  • DDRSDRAM Double Data Rate Synchronous Dynamic Random Access Memory
  • ESDRAM Double Data Rate Synchronous Dynamic Random Access Memory
  • ESDRAM Double Data Rate Synchronous Dynamic Random Access Memory
  • the embodiment of the present disclosure also provides a computer storage medium, specifically a computer-readable storage medium, for example, includes a memory 902 storing a computer program, and a millimeter wave system is stored on the computer storage medium.
  • a computer storage medium specifically a computer-readable storage medium, for example, includes a memory 902 storing a computer program, and a millimeter wave system is stored on the computer storage medium.
  • One or more programs of the method for optimizing coverage of the millimeter wave system when the one or more programs of the method for optimizing coverage of the millimeter wave system are executed by the processor 901, to realize the optimization of the millimeter wave system provided by the embodiment of the present disclosure.
  • the following steps of the method :
  • the method and device for optimizing coverage of millimeter wave system, electronic equipment and storage medium proposed in the embodiments of the present disclosure include: counting the optimal beams of all UEs received by cells under all codebooks To obtain the energy optimization value set of all codebooks; select the optimal energy optimization value from the energy optimization value set according to the preset optimal selection strategy; assign the codebook corresponding to the optimal energy optimization value Determined as the optimal codebook in the current scenario.
  • the energy optimization value set of all codebooks is formed by counting the energy optimization values of the optimal beams of all UEs received by the cells under all codebooks, and the energy optimization value set is based on the preset optimal value.
  • the technology provided in this embodiment can be used for beam codebook configuration in different scenarios, affecting coverage performance and service performance in different scenarios, considering the real application scenarios of cell coverage and user distribution after the communication system is commercialized, according to the distribution of terminal UEs choose to load the beam codebook that conforms to the current UE distribution, thereby improving the overall coverage and performance of the network.
  • the technical solution of the present disclosure essentially or the part that contributes to the existing technology can be embodied in the form of a software product, and the computer software product is stored in a storage medium (such as ROM/RAM, magnetic disk, The optical disc) includes several instructions to make a terminal (which can be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) execute the methods described in the various embodiments of the present disclosure.
  • a terminal which can be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.

Abstract

本公开公开一种毫米波系统优化覆盖的方法及装置、电子设备及存储介质，包括：统计所有码本下小区收到的所有UE的最优波束的能量优化值，得到所有码本的能量优化值集合；从所述能量优化值集合中根据预设最优选择策略选出最优能量优化值；将所述最优能量优化值对应的码本确定为当前场景下的最优码本。通过本公开实施例，可以筛选出适合当前场景的最优码本，使用最优码本，提高小区容量，小区提供更好的接入和业务，能为UE提供更好的信号覆盖，能覆盖更多的UE，提升UE的业务性能，从而提升用户体验。本实施例提供的技术能用于不同场景下的波束码本配置，影响不同场景下的覆盖性能和业务性能。

Description

毫米波系统优化覆盖的方法及装置、电子设备及存储介质
相关申请的交叉引用
本公开要求享有2020年3月2号提交的名称为“毫米波系统优化覆盖的方法及装置、电子设备及存储介质”的中国专利申请CN202010137714.2的优先权，其全部内容通过引用并入本文中。
技术领域
本公开涉及移动通信领域，特别涉及一种毫米波系统优化覆盖的方法及装置、电子设备及存储介质。
背景技术
当前，5G(Fifth Generation)技术正日益发展。5G强大的能力和丰富的连接场景势必会激发各行各业的应用需求。
在一些实施方案中，5G毫米波(mmWAVE)系统的空口使用的波束(Beam)采用混合模拟赋形，通过在AAU(Active Antenna Unit，一体化有源天线单元)中加载不同码本(Codebook)提供不同的方向的波束使能，带来覆盖增益。
如图1所示，波束存在如下特性：(1)码本波束个数越多，覆盖的范围越广且越精细。(2)码本波束个数越多，对设备的软硬件处理能力要求更高，同时波束轮扫和配对的时间更长。
不同码本下的波束不一样，在同一无线环境采用不同的波束码本将产生完全不同的覆盖情况，同一位置的UE的信号覆盖和业务性能表现差别巨大。码本的选择和优化是毫米波系统测试以及组网覆盖要面临的重要问题。
目前，测试人员通过对无线环境覆盖预估，手动选择码本加载到AAU。并且人为摆放UE到正对AAU方向的位置，得到UE基本处在波束的主瓣覆盖内的结果。在通信系统商用后，UE数量增加并呈随机分布，又或者出现UE移动到其他位置的情况。UE极易处在波束的副瓣覆盖内，产生弱覆盖的情况。这将造成UE接收信号差、性能差，用户体验差的情况。
发明内容
有鉴于此，本公开实施例提供的一种毫米波系统优化覆盖的方法及装置、电子设备及存储介质。
本公开解决上述技术问题所采用的技术方案如下：
根据本公开实施例的一个方面，提供的一种毫米波系统优化覆盖的方法，所述方法包括：
统计所有码本下小区收到的所有UE的最优波束的能量优化值，得到所有码本的能量优化值集合；
从所述能量优化值集合中根据预设最优选择策略选出最优能量优化值；
将所述最优能量优化值对应的码本确定为当前场景下的最优码本。
根据本公开实施例的另一个方面，提供的一种毫米波系统优化覆盖的装置，所述装置应用于本公开实施例所述的一种毫米波系统优化覆盖的方法，所述装置包括：统计模块、选择模块、确定模块，其中：
所述统计模块，用于统计所有码本下小区收到的所有UE的最优波束的能量优化值，得到所有码本的能量优化值集合；
所述选择模块，用于从所述能量优化值集合中根据预设最优选择策略选出最优能量优化值；
所述确定模块，用于将所述最优能量优化值对应的码本确定为当前场景下的最优码本。
根据本公开实施例的另一个方面，提供的一种电子设备，包括：存存储器、处理器及存储在所述存储器上并可在所述处理器上运行的计算机程序，所述计算机程序被所述处理器执行时实现本公开实施例提供的所述的一种毫米波系统优化覆盖的方法的步骤。
根据本公开实施例的另一个方面，提供的一种计算机可读存储介质，所述存储介质上存储有一种毫米波系统优化覆盖的方法的程序，所述一种毫米波系统优化覆盖的方法的程序被处理器执行时实现本公开实施例提供的所述的一种毫米波系统优化覆盖的方法的步骤。
本公开本公开
附图说明
图1是本公开实施例提供的一种毫米波波束覆盖示意图；
图2是本公开实施例提供的一种毫米波系统优化覆盖的方法的流程示意图；
图3是本公开实施例提供的一种毫米波系统优化覆盖的装置的结构示意图；
图4是本公开实施例提供的一种毫米波系统优化覆盖的方法的流程示意图；
图5是本公开实施例提供的另一种毫米波系统优化覆盖的方法的流程示意图；
图6为本公开实施例提供的一种电子设备的结构示意图。
本公开目的的实现、功能特点及优点将结合实施例，参照附图做进一步说明。
具体实施方式
为了使本公开所要解决的技术问题、技术方案及有益效果更加清楚、明白，以下结合附图和实施例，对本公开进行进一步详细说明。应当理解，此处所描述的具体实施例仅仅以解释本公开，并不用于限定本公开。
在后续的描述中，使用用于表示元件的诸如“模块”、“部件”或“单元”的后缀仅为了有利于本公开的说明，其本身没有特定的意义。因此，“模块”、“部件”或“单元”可以混合地使用。
需要说明的是，本公开的说明书和权利要求书及上述附图中的术语“第一”、“第二”等是用于区别类似的对象，而不必用于描述特定的顺序或先后次序。
本公开提出一种在毫米波系统中优化码本提升覆盖的方案，该方案可以用于5G毫米波系统中不同场景下的波束码本配置，影响不同场景下的覆盖性能和业务性能。
在一个实施例中，如图2所示，本公开提供一种毫米波系统优化覆盖的方法，所述方法包括：
S1、统计所有码本下小区收到的所有UE的最优波束的能量优化值，得到所有码本的能量优化值集合。
S2、从所述能量优化值集合中根据预设最优选择策略选出最优能量优化值。
S3、将所述最优能量优化值对应的码本确定为当前场景下的最优码本。
在一些实施方案中，所述用户终端设备UE，泛指5G毫米波系统中的用户终端设备。
在本实施例中，通过统计所有码本下小区收到的所有UE的最优波束的能量优化值形成 所有码本的能量优化值集合，并从所述能量优化值集合中根据预设最优选择策略选出最优能量优化值，就可以筛选出适合当前场景的最优码本，使用最优码本，提高小区容量，小区提供更好的接入和业务，能为UE提供更好的信号覆盖，能覆盖更多的UE，提升UE的业务性能，从而提升用户体验。本实施例提供的技术能用于不同场景下的波束码本配置，影响不同场景下的覆盖性能和业务性能，考虑到通信系统商用后小区覆盖和用户分布的真实应用场景，根据终端UE的分布选择加载符合当前UE分布的波束码本，从而提升网络整体的覆盖和性能。
在一个实施例中，所述能量优化值为能量累计值。所述S1中，所述统计所有码本下小区收到的所有UE的最优波束的能量优化值，得到所有码本的能量优化值集合，包括：统计所有码本下小区收到的所有UE的最优波束的能量累计值，得到所有码本的能量累计值集合。
在一个实施例中，所述能量优化值为能量平均值。所述S1中，所述统计所有码本下小区收到的所有UE的最优波束的能量优化值，得到所有码本的能量优化值集合，包括：统计所有码本下小区收到的所有UE的最优波束的能量平均值，得到所有码本的能量平均值集合。
在一个实施例中，所述S1中，所述统计所有码本下小区收到的所有UE的最优波束的能量优化值，得到所有码本的能量优化值集合；包括：
S11、统计码本数量，得到码本数量N。
S12、统计一个码本下小区收到的所有UE的最优波束的RSRP(Reference Signal Receiving Power，参考信号接收功率)能量优化值R。
S13、判断所有码本是否都已加载。如果N-1＝0，所有码本已加载，执行步骤S15，否则执行步骤S14。
S14、更新N值，N＝N-1，加载下一个码本，执行步骤S12。
S15、得到各码本的RSRP能量优化值集合，该集合用数组(R1,R2....Rn)来表示，其中，数组中数值n的取值依据系统的码本个数N来定，n＝N。
在一些实施方案中，所述S12中，所述统计一个码本下小区收到的所有UE的最优波束的RSRP能量优化值，包括：
S121、加载一个码本，码本定时器t开始计时。
S122、基站统计波束配对过程中收到的所有UE的最佳波束的RSRP能量优化值R。R值越大说明当前波束码本下能接入的UE个数多或者能量强。
S123、当码本定时器计时达到码本定时器时长时，即码本定时器t＝f，码本定时器t置0，保存RSRP的能量优化值R。其中，f为码本定时器时长，单位可提供秒/分/时/天四种选择，根据需要进行设定。f越大，收集的数据越准确，同时遍历全部码本的时间就越长。
在一些实施方案中，所述能量优化值为能量累计值，按上述实施例的方法，得到各码本下的RSRP能量累计值集合(R1,R2....Rn)。
在一些实施方案中，所述能量优化值为能量平均值，按上述实施例的方法，得到各码本下的RSRP能量平均值集合(R1,R2....Rn)。
在本实施例中，通过统计码本数量，再选取一个码本，开启码本定时器t，由基站统计到波束配对过程中收到的所有UE的最佳波束的能量优化值并累计，定时器置零后停止，得到该码本下小区收到的所有UE的最优波束的能量优化值。直至统计所有码本下小区收到的所有UE的最优波束的能量优化值，得到所有码本的能量优化值集合，从而可以在所述能量优化值集合中根据预设最优选择策略选出最优能量优化值，筛选出适合当前场景的最优码本，使用最优码本，提高小区容量，小区提供更好的接入和业务，能为UE提供更好的信号覆盖，能覆盖更多的UE，提升UE的业务性能，从而提升用户体验。本实施例提供的技术能用于不同场景下的波束码本配置，影响不同场景下的覆盖性能和业务性能，考虑到通信系统商用后小区覆盖和用户分布的真实应用场景，根据终端UE的分布选择加载符合当前UE分布的波束码本，从而提升网络整体的覆盖和性能。
在一个实施例中，所述S2中，所述预设最优选择策略为最大值选择策略，所述从所述能量优化值集合中根据预设最优选择策略选出最优能量优化值，包括：
比较所述能量优化值集合中各个所述能量优化值，选出其中能量优化值最大的能量优化值作为最优能量优化值。
在实施例中，通过统计所有码本下小区收到的所有UE的最优波束的能量优化值形成所有码本的能量优化值集合，并进行比较，选出其中能量优化值最大的能量优化值作为最优能量优化值，从而可以筛选出与最优能量优化值对应的适合当前场景的最优码本，使用最优码本，提高小区容量，小区提供更好的接入和业务，能为UE提供更好的信号覆盖，能覆盖更多的UE，提升UE的业务性能，从而提升用户体验。本实施例提供的技术能用于不同 场景下的波束码本配置，影响不同场景下的覆盖性能和业务性能，考虑到通信系统商用后小区覆盖和用户分布的真实应用场景，根据终端UE的分布选择加载符合当前UE分布的波束码本，从而提升网络整体的覆盖和性能。
在一个实施例中，所述方法还进一步包括：将确定的所述最优码本加载到AAU系统中运行。
在一些实施方案中，所述AAU(Active Antenna Unit，一体化有源天线单元)系统为5G毫米波系统中集成了信号处理与射频输入和输出的设备模块。
在本实施例中，将确定的所述最优码本加载到AAU系统中运行，从而可以提高小区容量，小区提供更好的接入和业务，能为UE提供更好的信号覆盖，能覆盖更多的UE，提升UE的业务性能，从而提升用户体验。本实施例提供的技术能用于不同场景下的波束码本配置，影响不同场景下的覆盖性能和业务性能。
在一个实施例中，如图3所示，本公开提供一种毫米波系统优化覆盖的装置，所述装置包括：统计模块10、选择模块20、确定模块30；其中：
所述统计模块10，用于统计所有码本下小区收到的所有UE的最优波束的能量优化值，得到所有码本的能量优化值集合。
所述选择模块20，用于从所述能量优化值集合中根据预设最优选择策略选出最优能量优化值。
所述确定模块30，用于将所述最优能量优化值对应的码本确定为当前场景下的最优码本。
在一些实施方案中，所述用户终端设备UE，泛指5G毫米波系统中的用户终端设备。
在本实施例中，通过统计所有码本下小区收到的所有UE的最优波束的能量优化值形成所有码本的能量优化值集合，并从所述能量优化值集合中根据预设最优选择策略选出最优能量优化值，就可以筛选出适合当前场景的最优码本，使用最优码本，提高小区容量，小区提供更好的接入和业务，能为UE提供更好的信号覆盖，能覆盖更多的UE，提升UE的业务性能，从而提升用户体验。本实施例提供的技术能用于不同场景下的波束码本配置，影响不同场景下的覆盖性能和业务性能，考虑到通信系统商用后小区覆盖和用户分布的真实应用场景，根据终端UE的分布选择加载符合当前UE分布的波束码本，从而提升网络整体的覆盖和性能。
在一个实施例中，所述能量优化值为能量累计值。所述统计模块10，具体用于：统计 所有码本下小区收到的所有UE的最优波束的能量累计值，得到所有码本的能量累计值集合。
在一个实施例中，所述能量优化值为能量平均值。所述统计模块10，具体用于：统计所有码本下小区收到的所有UE的最优波束的能量平均值，得到所有码本的能量平均值集合。
在一个实施例中，所述统计模块10，具体用于：
S11、统计码本数量，得到码本数量N。
S12、统计一个码本下小区收到的所有UE的最优波束的RSRP能量优化值R。
S13、判断所有码本是否都已加载。如果N-1＝0，所有码本已加载，执行步骤S15，否则执行步骤S14。
S14、更新N值，N＝N-1，加载下一个码本，执行步骤S12。
S15、得到各码本的RSRP能量优化值集合，该集合用数组(R1,R2....Rn)来表示，其中，数组中数值n的取值依据系统的码本个数N来定，n＝N。
在一些实施方案中，所述S12中，所述统计一个码本下小区收到的所有UE的最优波束的RSRP能量优化值，包括：
S121、加载一个码本，码本定时器t开始计时。
S122、基站统计波束配对过程中收到的所有UE的最佳波束的RSRP能量优化值R。R值越大说明当前波束码本下能接入的UE个数多或者能量强。
S123、当码本定时器计时达到码本定时器时长时，即码本定时器t＝f，码本定时器t置0，保存RSRP的能量优化值R。其中，f为码本定时器时长，单位可提供秒/分/时/天四种选择，根据需要进行设定。f越大，收集的数据越准确，同时遍历全部码本的时间就越长。
在本实施例中，通过统计码本数量，再选取一个码本，开启码本定时器t，由基站统计到波束配对过程中收到的所有UE的最佳波束的能量优化值并累计，定时器置零后停止，得到该码本下小区收到的所有UE的最优波束的能量优化值。直至统计所有码本下小区收到的所有UE的最优波束的能量优化值，得到所有码本的能量优化值集合，从而可以在所述能量优化值集合中根据预设最优选择策略选出最优能量优化值，筛选出适合当前场景的最优码本，使用最优码本，提高小区容量，小区提供更好的接入和业务，能为UE提供更好的信 号覆盖，能覆盖更多的UE，提升UE的业务性能，从而提升用户体验。本实施例提供的技术能用于不同场景下的波束码本配置，影响不同场景下的覆盖性能和业务性能。
在一个实施例中，所述预设最优选择策略为最大值选择策略，所述选择模块20，具体用于：
比较所述能量优化值集合中各个所述能量优化值，选出其中能量优化值最大的能量优化值作为最优能量优化值。
在实施例中，通过统计所有码本下小区收到的所有UE的最优波束的能量优化值形成所有码本的能量优化值集合，并进行比较，选出其中能量优化值最大的能量优化值作为最优能量优化值，从而可以筛选出与最优能量优化值对应的适合当前场景的最优码本，使用最优码本，提高小区容量，小区提供更好的接入和业务，能为UE提供更好的信号覆盖，能覆盖更多的UE，提升UE的业务性能，从而提升用户体验。本实施例提供的技术能用于不同场景下的波束码本配置，影响不同场景下的覆盖性能和业务性能。
在一个实施例中，所述装置还进一步包括：加载模块，所述加载模块用于将确定的所述最优码本加载到AAU系统中运行。
在一些实施方案中，所述AAU系统为5G毫米波系统中集成了信号处理与射频输入和输出的设备模块。
在本实施例中，将确定的所述最优码本加载到AAU系统中运行，从而可以提高小区容量，小区提供更好的接入和业务，能为UE提供更好的信号覆盖，能覆盖更多的UE，提升UE的业务性能，从而提升用户体验。本实施例提供的技术能用于不同场景下的波束码本配置，影响不同场景下的覆盖性能和业务性能，考虑到通信系统商用后小区覆盖和用户分布的真实应用场景，根据终端UE的分布选择加载符合当前UE分布的波束码本，从而提升网络整体的覆盖和性能。
需要说明的是，上述装置实施例与方法实施例属于同一构思，其具体实现过程详见方法实施例，且方法实施例中的技术特征在所述装置实施例中均对应适用，这里不再赘述。
以下结合具体的实施例和附图对本公开的技术方案作进一步的说明。
在一个实施例中，如图4所示，本公开提供一种毫米波系统优化覆盖的方法，在本实施例中，所述能量优化值以能量累计值为例进行说明。
本公开提供一种毫米波系统优化覆盖的方法，所述方法包括：
S501、流程开始。
S502、统计码本数量，得到码本数量N。
S503、加载码本，码本定时器t开始计时。执行步骤S504。
S504、基站统计波束配对过程中收到的所有UE的最佳波束的能量累计值，能量累计值计为R。R值越大说明当前波束码本下能接入的UE个数多或者能量强。执行步骤S505。
S505、当码本定时器计时达到码本定时器时长时，即码本定时器t＝f，码本定时器t置0。保存RSRP的能量累计值R。其中，f为码本定时器时长，单位可提供秒/分/时/天四种选择，根据需要进行设定。f越大，收集的数据越准确，同时遍历全部码本的时间就越长。执行步骤S506。
S506、判断所有码本是否都已加载(if N-1＝0)。如果N-1＝0，所有码本已加载，执行步骤S508，否则执行步骤S507。
S507、更新N值，N＝N-1。加载下一个码本。执行步骤S503。
S508、得到各码本下的RSRP能量累计值集合，该集合用数组(R1,R2....Rn)来表示，其中，数组中数值n的取值依据系统的码本个数N来定，n＝N。执行步骤S509。
S509、比较能量累计值集合(R1,R2....Rn)，选出能量累计值集合中能量累计值最大的能量累计值作为最优能量累计值。执行步骤S510。
S510、将所述最优能量累计值对应的码本确定为当前场景下的最优码本。执行步骤S511。
S511、将确定的所述最优码本加载到AAU系统中运行。执行步骤S512。
S512、流程结束。
在本实施例中，通过统计码本数量，再选取一个码本，开启码本定时器t，由基站统计到波束配对过程中收到的所有UE的最佳波束的能量累计值，定时器置零后停止，得到该码本下小区收到的所有UE的最优波束的能量累计值。直至统计所有码本下小区收到的所有UE的最优波束的能量累计值，得到所有码本的能量累计值集合，从而可以在所述能量累计值集合中根据预设最优选择策略选出最优能量累计值，将所述最优能量累计值对应的码本确定为适合当前场景的最优码本，使用最优码本，提高小区容量，为小区提供更好的接入和业务，能为UE提供更好的信号覆盖，能覆盖更多的UE，提升UE的业务性能，从而提升用户体验。本实施例提供的技术能用于不同场景下的波束码本配置，影响不同场景下的覆 盖性能和业务性能，考虑到通信系统商用后小区覆盖和用户分布的真实应用场景，根据终端UE的分布选择加载符合当前UE分布的波束码本，从而提升网络整体的覆盖和性能。
在一个实施例中，如图5所示，本公开提供一种毫米波系统优化覆盖的方法，在本实施例中，所述能量优化值以能量平均值为例进行说明。
本公开提供一种毫米波系统优化覆盖的方法，所述方法包括：
S601、流程开始。
S602、统计码本数量，得到码本数量N。
S603、加载码本，码本定时器t开始计时。执行步骤S604。
S604、基站统计波束配对过程中收到的所有UE的最佳波束的能量平均值，能量平均值计为R。R值越大说明当前波束码本下能接入的UE个数多或者能量强。执行步骤S605。
S605、当码本定时器计时达到码本定时器时长时，即码本定时器t＝f，码本定时器t置0。保存RSRP的能量平均值R。其中，f为码本定时器时长，单位可提供秒/分/时/天四种选择，根据需要进行设定。f越大，收集的数据越准确，同时遍历全部码本的时间就越长。执行步骤S606。
S606、判断所有码本是否都已加载(if N-1＝0)。如果N-1＝0，所有码本已加载，执行步骤S608，否则执行步骤S607。
S607、更新N值，N＝N-1。加载下一个码本。执行步骤S603。
S608、得到各码本下的RSRP能量平均值集合，该集合用数组(R1,R2....Rn)来表示，其中，数组中数值n的取值依据系统的码本个数N来定，n＝N。执行步骤S609。
S609、比较能量平均值集合(R1,R2....Rn)，选出能量平均值集合中能量平均值最大的能量平均值作为最优能量平均值。执行步骤S610。
S610、将所述最优能量平均值对应的码本确定为当前场景下的最优码本。执行步骤S611。
S611、将确定的所述最优码本加载到AAU系统中运行。执行步骤S612。
S612、流程结束。
在本实施例中，通过统计码本数量，再选取一个码本，开启码本定时器t，由基站统计到波束配对过程中收到的所有UE的最佳波束的能量平均值，定时器置零后停止，得到该 码本下小区收到的所有UE的最优波束的能量平均值。直至统计所有码本下小区收到的所有UE的最优波束的能量平均值，得到所有码本的能量平均值集合，从而可以在所述能量平均值集合中根据预设最优选择策略选出最优能量平均值，筛选出适合当前场景的最优码本，使用最优码本，提高小区容量，小区提供更好的接入和业务，能为UE提供更好的信号覆盖，能覆盖更多的UE，提升UE的业务性能，从而提升用户体验。本实施例提供的技术能用于不同场景下的波束码本配置，影响不同场景下的覆盖性能和业务性能，考虑到通信系统商用后小区覆盖和用户分布的真实应用场景，根据终端UE的分布选择加载符合当前UE分布的波束码本，从而提升网络整体的覆盖和性能。
此外，本公开实施例还提供一种电子设备，如图6所示，所述电子设备900包括：存储器902、处理器901及存储在所述存储器902中并可在所述处理器901上运行的一个或者多个计算机程序，所述存储器902和所述处理器901通过总线系统903耦合在一起，所述一个或者多个计算机程序被所述处理器901执行时以实现本公开实施例提供的一种毫米波系统优化覆盖的方法的以下步骤：
S1、统计所有码本下小区收到的所有UE的最优波束的能量优化值，得到所有码本的能量优化值集合。
S2、从所述能量优化值集合中根据预设最优选择策略选出最优能量优化值。
S3、将所述最优能量优化值对应的码本确定为当前场景下的最优码本。
上述本公开实施例揭示的方法可以应用于所述处理器901中，或者由所述处理器901实现。所述处理器901可能是一种集成电路芯片，具有信号处理能力。在实现过程中，上述方法的各步骤可以通过所述处理器901中的硬件的集成逻辑电路或软件形式的指令完成。所述处理器901可以是通用处理器、DSP、或者其他可编程逻辑器件、分立门或者晶体管逻辑器件、分立硬件组件等。所述处理器901可以实现或者执行本公开实施例中的公开的各方法、步骤及逻辑框图。通用处理器可以是微处理器或者任何常规的处理器等。结合本公开实施例所公开的方法的步骤，可以直接体现为硬件译码处理器执行完成，或者用译码处理器中的硬件及软件模块组合执行完成。软件模块可以位于存储介质中，该存储介质位于存储器902，所述处理器901读取存储器902中的信息，结合其硬件完成前述方法的步骤。
可以理解，本公开实施例的存储器902可以是易失性存储器或者非易失性存储器，也可以包括易失性和非易失性存储器两者。其中，非易失性存储器可以是只读存储器(ROM，Read-Only Memory)、可编程只读存储器(PROM，Programmable Read-Only Memory)、可擦 除可编程只读存储器(EPROM，Erasable Read-Only Memory)、电可擦除只读存储器(EEPROM，Electrically Erasable Programmable Read-Only Memory)、磁性随机存取存储器(FRAM，Ferromagnetic Random Access Memory)、闪存(Flash Memory)或其他存储器技术、光盘只读存储器(CD-ROM，Compact Disk Read-Only Memory)、数字多功能盘(DVD，Digital Video Disk)或其他光盘存储、磁盒、磁带、磁盘存储或其他磁存储装置；易失性存储器可以是随机存取存储器(RAM，Random Access Memory)，通过示例性但不是限制性说明，许多形式的RAM可用，例如静态随机存取存储器(SRAM，Static Random Access Memory)、静态随机存取存储器(SSRAM，Synchronous Static Random Access Memory)、动态随机存取存储器(DRAM，Dynamic Random Access Memory)、同步动态随机存取存储器(SDRAM，Synchronous Dynamic Random Access Memory)、双倍数据速率同步动态随机存取存储器(DDRSDRAM，Double Data Rate Synchronous Dynamic Random Access Memory)、增强型同步动态随机存取存储器(ESDRAM，Enhanced Synchronous Dynamic Random Access Memory)、同步连接动态随机存取存储器(SLDRAM，SyncLink Dynamic Random Access Memory)、直接内存总线随机存取存储器(DRRAM，Direct Rambus Random Access Memory)。本公开实施例描述的存储器旨在包括但不限于这些和任意其它适合类型的存储器。
需要说明的是，上述电子设备实施例与方法实施例属于同一构思，其具体实现过程详见方法实施例，且方法实施例中的技术特征在所述电子设备实施例中均对应适用，这里不再赘述。
另外，在示例性实施例中，本公开实施例还提供一种计算机存储介质，具体为计算机可读存储介质，例如包括存储计算机程序的存储器902，所述计算机存储介质上存储有一种毫米波系统优化覆盖的方法的一个或者多个程序，所述一种毫米波系统优化覆盖的方法的一个或者多个程序被处理器901执行时以实现本公开实施例提供的一种毫米波系统优化覆盖的方法的以下步骤：
S1、统计所有码本下小区收到的所有UE的最优波束的能量优化值，得到所有码本的能量优化值集合。
S2、从所述能量优化值集合中根据预设最优选择策略选出最优能量优化值。
S3、将所述最优能量优化值对应的码本确定为当前场景下的最优码本。
需要说明的是，上述计算机可读存储介质上的一种毫米波系统优化覆盖的方法程序实施例与方法实施例属于同一构思，其具体实现过程详见方法实施例，且方法实施例中的技术特征在上述计算机可读存储介质的实施例中均对应适用，这里不再赘述。
与相关技术相比，本公开实施例提出的一种毫米波系统优化覆盖的方法及装置、电子设备及存储介质，所述方法包括：统计所有码本下小区收到的所有UE的最优波束的能量优化值，得到所有码本的能量优化值集合；从所述能量优化值集合中根据预设最优选择策略选出最优能量优化值；将所述最优能量优化值对应的码本确定为当前场景下的最优码本。通过本公开实施例，通过统计所有码本下小区收到的所有UE的最优波束的能量优化值形成所有码本的能量优化值集合，并从所述能量优化值集合中根据预设最优选择策略选出最优能量优化值，就可以筛选出适合当前场景的最优码本，使用最优码本，提高小区容量，小区提供更好的接入和业务，能为UE提供更好的信号覆盖，能覆盖更多的UE，提升UE的业务性能，从而提升用户体验。本实施例提供的技术能用于不同场景下的波束码本配置，影响不同场景下的覆盖性能和业务性能，考虑到通信系统商用后小区覆盖和用户分布的真实应用场景，根据终端UE的分布选择加载符合当前UE分布的波束码本，从而提升网络整体的覆盖和性能。
需要说明的是，在本文中，术语“包括”、“包含”或者其任何其他变体意在涵盖非排他性的包含，从而使得包括一系列要素的过程、方法、物品或者装置不仅包括那些要素，而且还包括没有明确列出的其他要素，或者是还包括为这种过程、方法、物品或者装置所固有的要素。在没有更多限制的情况下，由语句“包括一个……”限定的要素，并不排除在包括该要素的过程、方法、物品或者装置中还存在另外的相同要素。
上述本公开实施例序号仅仅为了描述，不代表实施例的优劣。
通过以上的实施方式的描述，本领域的技术人员可以清楚地了解到上述实施例方法可借助软件加必需的通用硬件平台的方式来实现，当然也可以通过硬件，但很多情况下前者是更佳的实施方式。基于这样的理解，本公开的技术方案本质上或者说对现有技术做出贡献的部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质(如ROM/RAM、磁碟、光盘)中，包括若干指令用以使得一台终端(可以是手机，计算机，服务器，空调器，或者网络设备等)执行本公开各个实施例所述的方法。
上面结合附图对本公开的实施例进行了描述，但是本公开并不局限于上述的具体实施方式，上述的具体实施方式仅仅是示意性的，而不是限制性的，本领域的普通技术人员在本公开的启示下，在不脱离本公开宗旨和权利要求所保护的范围情况下，还可做出很多形式，这些均属于本公开的保护之内。

Claims (9)

  1. 一种毫米波系统优化覆盖的方法，其特征在于，所述方法包括：
    统计所有码本下小区收到的所有UE的最优波束的能量优化值，得到所有码本的能量优化值集合；
    从所述能量优化值集合中根据预设最优选择策略选出最优能量优化值；
    将所述最优能量优化值对应的码本确定为当前场景下的最优码本。
  2. 根据权利要求1所述的方法，其特征在于，所述统计所有码本下小区收到的所有UE的最优波束的能量优化值，得到所有码本的能量优化值集合；包括：
    统计码本数量，得到码本数量N；
    统计一个码本下小区收到的所有UE的最优波束的能量优化值R；
    判断所有码本是否都已加载，如还有码本未加载，则加载下一个码本，返回以上统计一个码本下小区收到的所有UE的最优波束的能量优化值的步骤；
    如所有码本已加载，得到所有码本的能量优化值集合(R1,R2....Rn)，其中，数值n＝N。
  3. 根据权利要求2所述的方法，其特征在于，所述统计一个码本下小区收到的所有UE的最优波束的能量优化值，包括：
    加载所述码本，码本定时器t开始计时；
    基站统计波束配对过程中收到的所有UE的最佳波束的能量优化值R；
    当码本定时器计时达到码本定时器时长时，码本定时器t置0，保存能量优化值R。
  4. 根据权利要求1所述的方法，其特征在于，所述预设最优选择策略为最大值选择策略，所述从所述能量优化值集合中根据预设最优选择策略选出最优能量优化值，包括：比较所述能量优化值集合中各个所述能量优化值，选出其中能量优化值最大的能量优化值作为最优能量优化值。
  5. 根据权利要求1至4任一项所述的方法，其特征在于，所述能量优化值为能量累计值，或能量平均值。
  6. 根据权利要求1所述的方法，其特征在于，所述方法还进一步包括：将确定的所述最优码本加载到AAU系统中运行。
  7. 一种毫米波系统优化覆盖的装置，其特征在于，所述装置应用于如权利要求1至6 中任一项所述的一种毫米波系统优化覆盖的方法，所述装置包括：统计模块、选择模块、确定模块，其中：
    所述统计模块，用于统计所有码本下小区收到的所有UE的最优波束的能量优化值，得到所有码本的能量优化值集合；
    所述选择模块，用于从所述能量优化值集合中根据预设最优选择策略选出最优能量优化值；
    所述确定模块，用于将所述最优能量优化值对应的码本确定为当前场景下的最优码本。
  8. 一种电子设备，其特征在于，包括：存储器、处理器及存储在所述存储器上并可在所述处理器上运行的计算机程序，所述计算机程序被所述处理器执行时实现如权利要求1至6中任一项所述的一种毫米波系统优化覆盖的方法的步骤。
  9. 一种存储介质，其特征在于，所述存储介质上存储有一种毫米波系统优化覆盖的方法的程序，所述一种毫米波系统优化覆盖的方法的程序被处理器执行时实现如权利要求1至6中任一项所述的一种毫米波系统优化覆盖的方法的步骤。
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