WO2021072953A1 - 数据压缩方法、装置、计算机设备和计算机可读存储介质 - Google Patents

数据压缩方法、装置、计算机设备和计算机可读存储介质 Download PDF

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WO2021072953A1
WO2021072953A1 PCT/CN2019/124694 CN2019124694W WO2021072953A1 WO 2021072953 A1 WO2021072953 A1 WO 2021072953A1 CN 2019124694 W CN2019124694 W CN 2019124694W WO 2021072953 A1 WO2021072953 A1 WO 2021072953A1
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Prior art keywords
data
compressed
reference coefficient
slope reference
data compression
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PCT/CN2019/124694
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English (en)
French (fr)
Inventor
刘重军
潘雷
张维
黄鹏飞
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京信通信系统（中国）有限公司
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Publication of WO2021072953A1 publication Critical patent/WO2021072953A1/zh

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W28/00—Network traffic management; Network resource management
    • H04W28/02—Traffic management, e.g. flow control or congestion control
    • H04W28/06—Optimizing the usage of the radio link, e.g. header compression, information sizing, discarding information

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  • This application relates to the field of mobile communication technology, and in particular to a data compression method, device, computer equipment, and computer-readable storage medium.
  • the access network is reconstructed into three functional entities: CU (Centralized Unit), DU (Distribute Unit), and AAU (Active Antenna Unit).
  • CU Centralized Unit
  • DU Distribute Unit
  • AAU Active Antenna Unit
  • AAU is distributed It is deployed at the site, AAU and DU form a fronthaul network, and DU and CU form a midhaul network.
  • an embodiment of the present application provides a data compression method, and the data compression method includes:
  • Acquiring data to be compressed based on a preset time period includes multiple user data;
  • the data compression slope reference coefficient is obtained according to the modulation order and user signal power corresponding to each of the user data;
  • an embodiment of the present application provides a data compression device, and the data compression device includes:
  • the first acquisition module is configured to acquire data to be compressed based on a preset time period; the data to be compressed includes multiple user data;
  • the second acquisition module is configured to acquire a data compression slope reference coefficient corresponding to the data to be compressed; the data compression slope reference coefficient is obtained according to the modulation order and user signal power corresponding to each of the user data;
  • a compression module configured to compress the data to be compressed according to the data compression slope reference coefficient to obtain compressed data
  • the sending module is configured to send the data compression slope reference coefficient and the compressed data to the receiving end, so that the receiving end decompresses the compressed data according to the data compression slope reference coefficient.
  • an embodiment of the present application provides a computer device, including a memory and a processor, the memory stores a computer program, and the processor implements the steps of the method described in the first aspect when the computer program is executed. .
  • an embodiment of the present application provides a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, the steps of the method described in the first aspect are implemented.
  • the data to be compressed includes multiple user data; the data compression slope reference coefficient corresponding to the data to be compressed is obtained; the data compression slope reference coefficient is based on each of the The user data is obtained by the modulation order and the user signal power respectively; the data to be compressed is compressed according to the data compression slope reference coefficient to obtain compressed data; the data compression slope reference coefficient and the compressed data are sent Data to the receiving end, so that the receiving end decompresses the compressed data according to the data compression slope reference coefficient; thus, the sending end compresses the data to be compressed according to the acquired data compression slope reference coefficient, using compression
  • the latter data is transmitted with the receiving end, which reduces the occupied bandwidth of data transmission, and the compression algorithm is simple and easy to implement in engineering. It is suitable for scenarios with high real-time requirements for data transmission in 5G networks, and ensures the overall performance of the system.
  • FIG. 1 is an application environment diagram of a data compression method provided by an embodiment
  • FIG. 2 is a schematic flowchart of a data compression method provided by an embodiment
  • FIG. 3 is a schematic flowchart of a data compression method provided by an embodiment
  • FIG. 4 is a schematic flowchart of a data compression method provided by an embodiment
  • FIG. 5 is a schematic flowchart of a data compression method provided by an embodiment
  • FIG. 6 is a schematic flowchart of a data compression method provided by an embodiment
  • Fig. 7 is a structural block diagram of a data compression device provided by an embodiment.
  • the BBU baseband processing unit
  • the RRU remote radio unit
  • the BBU is placed in the central computer room or the main site
  • the RRU is distributed on each site.
  • a CPRI interface is used between the BBU and the RRU, and each CPRI port is connected to an RRU.
  • Each RRU is a two-stream antenna.
  • the LTE bandwidth is 20MHz, so the capacity of the CPRI interface is 2.45Gbps. If large-scale antenna technology is adopted, the CPRI capacity between the BBU and RRU will be greatly increased.
  • the CPRI capacity needs 19.66GHz; if it is further used above 100MHz Bandwidth, the capacity of the CPRI interface between the BBU and the RRU requires several hundred Gbps.
  • the fronthaul network of the LTE system cannot handle such a large transmission capacity.
  • AAU is deployed at the site in a distributed manner.
  • a fronthaul network is formed between AAU and DU, and a midhaul network is formed between DU and CU.
  • the data compression method, device, computer equipment, and computer-readable storage medium provided by the embodiments of this application are intended to solve how to effectively reduce the gap between CU and DU, DU and AAU on the premise of ensuring the real-time communication performance of the system in 5G networks Technical issues between data transmission bandwidth.
  • the technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems will be described in detail through the embodiments and the accompanying drawings.
  • the following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments.
  • the data compression method provided in this application can be applied to the 5G access network architecture as shown in FIG. 1, and is specifically applied to the sending end of the architecture.
  • the sending end along the uplink communication link direction, the sending end can be AAU, and the corresponding receiving end is DU; the sending end can also be DU, and the corresponding receiving end is CU; along the downlink communication link direction, the sending end is It can be CU, and the corresponding receiving end is DU; the sending end can also be DU, and the corresponding receiving end is AAU.
  • the execution subject of the data compression method provided in the embodiments of the present application may be a data compression device, and the data compression device may be implemented as part or all of the sending end through software, hardware, or a combination of software and hardware.
  • the execution subject is the sending end as an example for description.
  • FIG. 2 shows a flowchart of a data compression method provided by an embodiment of the present application.
  • the data compression method of this embodiment may include the following steps:
  • Step S100 Obtain data to be compressed based on a preset time period.
  • the data to be compressed includes multiple user data.
  • the sender obtains the data to be compressed based on a preset time period, where the data to be compressed includes user data corresponding to multiple user terminals within the preset time period; the data to be compressed is required for the completion of processing by the sender
  • the user terminal sends an uplink user data packet to the sending end, and the sending end processes the data packet to obtain the data to be compressed
  • the base station sends the downlink
  • the user data packet is sent to the sending end, and the sending end processes the data packet to obtain the data to be compressed; it is understandable that for different network standards, the user data included in the uplink user data packet and the downlink user data packet can be There are no specific restrictions on time domain data or frequency domain data.
  • the preset time period may be one of an OFDM (Orthogonal Frequency Division Multiplexing, Orthogonal Frequency Division Multiplexing) symbol, one time slot, one subframe, multiple OFDM symbols, multiple time slots, and
  • Step S200 Obtain a data compression slope reference coefficient corresponding to the data to be compressed, where the data compression slope reference coefficient is obtained according to the modulation order and user signal power respectively corresponding to each user data.
  • the transmitting end obtains the data compression slope reference coefficient corresponding to the data to be compressed, and the data compression slope reference coefficient is obtained according to the modulation order and user signal power corresponding to each user data.
  • the data compression slope reference coefficient may be calculated by the transmitting end according to the modulation order and user signal power corresponding to each user data; or it may be obtained by the transmitting end from the receiving end, that is, corresponding to each user data.
  • the process of calculating the data compression slope reference coefficient by modulation order and user signal power is performed at the receiving end, and the data compression slope reference coefficient is sent to the sending end after the calculation is completed by the receiving end.
  • Each user data corresponds to a different user terminal, and the modulation order and user signal power of each user terminal are allocated by the base station; specifically, in the uplink communication link direction, the uplink transmission power corresponding to each user terminal is the user terminal's respective uplink transmission power.
  • User signal power, uplink transmission power is allocated by the base station to each user terminal; in the downlink communication link direction, the downlink transmission power corresponding to each user terminal by the base station is the user signal power of each user terminal. Take the upstream communication link as an example.
  • the DU obtains the modulation order and user signal power corresponding to each user data under the AAU module from the core network side, and the DU directly calculates the data compression
  • the slope reference coefficient, and the calculated data compression slope reference coefficient is sent to the AAU for AAU to compress the compressed data; for example, the downstream communication link is the DU and the corresponding receiver is AAU.
  • the DU is from the core
  • the network side obtains the modulation order and user signal power corresponding to each user data under the DU module
  • calculates the data compression slope reference coefficient compresses the compressed data according to the compression slope reference coefficient, and sends the compressed data to AAU.
  • the user signal power is obtained statistically and equivalently according to the number of frequency domain and time domain resources allocated by the base station to each user terminal.
  • step S300 the data to be compressed is compressed according to the data compression slope reference coefficient to obtain compressed data.
  • the sending end specifically uses U-law compression to compress the data to be compressed, and the sending end substitutes the data compression slope reference coefficient and the data to be compressed into the U-law compression formula to calculate the compressed data.
  • UL_u is the data compression slope reference coefficient obtained by the sending end
  • x represents the fixed-point quantized data input before compression (data to be compressed)
  • the data compression slope reference coefficient and the data to be compressed are substituted into formula 1
  • the calculated y y represents the output fixed-point quantized data after compression, that is, the compressed data obtained by compressing the data to be compressed according to the data compression slope reference coefficient.
  • Step S400 Send the data compression slope reference coefficient and the compressed data to the receiving end, so that the receiving end decompresses the compressed data according to the data compression slope reference coefficient.
  • the sending end sends the data compression slope reference coefficient and compressed data to the receiving end.
  • the receiving end decompresses the compressed data according to the data compression slope reference coefficient, and restores the result after decompression Data to be compressed.
  • the data to be compressed is obtained based on a preset time period; the data to be compressed includes multiple user data; the data compression slope reference coefficient corresponding to the data to be compressed is obtained; the data compression slope reference coefficient is respectively corresponding to each user data
  • the modulation order and user signal power are obtained; the compressed data is compressed according to the data compression slope reference coefficient to obtain the compressed data; the data compression slope reference coefficient and the compressed data are sent to the receiving end, so that the receiving end can refer to the data compression slope reference
  • the coefficient decompresses the compressed data; therefore, the sending end compresses the compressed data according to the obtained data compression slope reference coefficient, and uses the compressed data to transmit data with the receiving end, reducing the occupied bandwidth of data transmission and compressing
  • the algorithm is simple and easy to implement in engineering. It is suitable for scenarios with high real-time requirements for data transmission in 5G networks, ensuring the overall performance of the system.
  • FIG. 3 is a schematic flowchart of a data compression method provided by another embodiment.
  • step S200 specifically includes:
  • Step S210 Acquire the modulation order and user signal power corresponding to each user data based on a preset time period.
  • the DU is the transmitting end and the AAU is the receiving end as an example.
  • Each user data corresponds to a different user terminal.
  • the DU Based on the preset time period, the DU counts the next N DUs.
  • Step S220 According to the modulation order and user signal power corresponding to each user data, a data compression slope reference coefficient is calculated.
  • step S220 may include the following detailed steps:
  • Step a Perform weighting processing on the modulation order and user signal power corresponding to each user data to obtain weighted data.
  • Step b Based on the weighted data, the maximum value of the modulation order, and the maximum value of the compression slope coefficient, a data compression slope reference coefficient is calculated.
  • DU substitutes DL_M1, DL_M2...DL_MN and DL_P1, DL_P2...DL_PN into formula 2 to calculate the data compression slope reference coefficient, and formula 2 is as follows:
  • UL_u is the data compression slope reference coefficient
  • N is a positive integer greater than 0
  • the maximum value of the compression slope coefficient in the compression formula is configured as a default value of 256. Therefore, the DU calculates the data compression slope reference coefficient according to the modulation order and user signal power corresponding to each user data.
  • the transmitting end may also be a CU and the receiving end may be a DU.
  • the CU Based on the preset time period, the CU counts the modulation order and user corresponding to each user terminal under the CU. Signal power, CU calculates the data compression slope reference coefficient according to the modulation order, user signal power and formula 2 corresponding to each user data respectively.
  • the transmitting end obtains the modulation order and user signal power corresponding to each user data at the transmitting end based on the preset time period, and calculates the data compression slope reference according to the modulation order and user signal power corresponding to each user data.
  • Coefficient the sending end further compresses the data to be compressed according to the reference coefficient of the data compression slope to obtain compressed data. Therefore, in the downlink communication link, the DU or CU compresses the data to be compressed by the reference coefficient of the data compression slope. Transmission effectively reduces the data bandwidth between DU and AAU, CU and DU in the downlink communication link.
  • Fig. 4 is a schematic flowchart of a data compression method provided by another embodiment. Based on the embodiment shown in FIG. 2, step S200 includes:
  • Step S230 Obtain a data compression slope reference coefficient corresponding to the data to be compressed from the receiving end.
  • the data compression slope reference coefficient is calculated by the receiving end according to the modulation order and user signal power corresponding to each user data.
  • the AAU is the transmitting end and the DU is the receiving end as an example.
  • the DU calculates the modulation order UL_M1 corresponding to the N user terminals under the AAU, UL_M2...UL_MN, count the user signal powers UL_P1, UL_P2...UL_PN corresponding to N user terminals under AAU, further, DU substitutes UL_M1, UL_M2...UL_MN and UL_P1, UL_P2...UL_PN into formula 3, and calculates the data compression slope reference
  • the coefficient, formula 3 is as follows:
  • UL_u is the data compression slope reference coefficient
  • N is a positive integer greater than 0
  • the AAU Since the modulation order and user signal power corresponding to the user terminal are allocated by the base station, the AAU is used as the transmitting end as an example. If the data compression slope reference coefficient is calculated by the AAU, the user signals corresponding to the N user terminals under the AAU The power and user signal power are delivered by the core network side to the CU, the CU is transmitted to the DU, and then transmitted from the DU to the AAU, and then calculated by the AAU; in this embodiment, in order to reduce the data transmission bandwidth between DU and AAU, When the user signal power and user signal power corresponding to the N user terminals under the AAU are transmitted to the DU, the DU directly calculates the data compression slope reference coefficient, and then sends the calculated data compression slope reference coefficient to the AAU, and the AAU further according to the DU The sent data compression slope reference coefficient compresses the to-be-compressed data, which further reduces the data transmission bandwidth between AAU and DU.
  • the transmitting end may also be a DU and the receiving end may be a CU.
  • the CU calculates the modulation order of each user terminal under the DU.
  • the CU calculates the data compression slope reference coefficient, and sends the data compression slope reference coefficient to the DU.
  • the DU is based on the data compression slope sent by the CU.
  • the reference coefficient compresses the data to be compressed to obtain the compressed data, which further reduces the data transmission bandwidth between the DU and the CU.
  • Fig. 5 is a schematic flowchart of a data compression method provided by another embodiment.
  • the data to be compressed includes unsigned data and signed bit data.
  • step S300 includes:
  • step S310 the data compression slope reference coefficient and unsigned data are substituted into the U-law compression formula, and unsigned compressed data is obtained by calculation.
  • the data to be compressed includes unsigned data and sign bit data.
  • the sign bit data is used to represent the sign of the unsigned data.
  • the sign bit data in the compressed data is not compressed during compression, and only The data compression slope reference coefficient and unsigned data are substituted into the U-law compression formula, and unsigned compressed data is calculated.
  • Step S320 Combine unsigned compressed data and sign bit data to obtain compressed data.
  • the data to be compressed in this embodiment includes unsigned data and sign bit data.
  • the unsigned compressed data is calculated, and the unsigned compressed data and the sign bit data are calculated. Combine to obtain compressed data, thereby ensuring the accuracy of data compression and decompression when the data to be compressed is negative.
  • Fig. 6 is a schematic flowchart of a data compression method provided by another embodiment. Based on the embodiment shown in FIG. 2, step S300 includes:
  • Step S301 in a preset compression mapping table, search for a mapping value corresponding to the data compression slope reference coefficient and the data to be compressed.
  • the compression mapping table includes the mapping relationship between the data to be compressed and the mapping value, and the mapping relationship is associated with the data compression slope reference coefficient.
  • a compression map is created offline. Calculate the data compression slope reference coefficient corresponding to the data to be compressed, and then compress the data to be compressed according to the data compression slope reference coefficient to obtain the compressed data.
  • the calculated multiple compressed data and their corresponding data compression slope reference coefficients and the The compressed data forms a compression mapping table.
  • the sender obtains the data to be compressed based on a preset time period. Take the upstream communication link as an example.
  • DU sends the calculated data compression slope reference coefficient
  • AAU does not need to substitute the data to be compressed and the reference coefficient of data compression slope into the U-law compression formula to calculate the compressed data, but can directly look up the reference coefficient of the data compression slope and to be compressed in the preset compression mapping table.
  • the mapping value corresponding to the data is sufficient; as an example of the downstream communication link, when the transmitting end is DU and the corresponding receiving end is AAU, the DU can be calculated according to the modulation order and user signal power corresponding to each user data under the DU module After the data compression slope reference coefficient, DU does not need to substitute the data to be compressed and the data compression slope reference coefficient into the U-law compression formula to calculate the compressed data, but can directly look up the data compression slope reference coefficient in the preset compression mapping table And the mapping value corresponding to the data to be compressed.
  • Step S302 Determine the found mapping value as compressed data.
  • the sending end determines the mapping value corresponding to the data compression slope reference coefficient and the data to be compressed found in the compression mapping table as the compressed data corresponding to the data to be compressed.
  • the receiving end after receiving the data compression slope reference coefficient and the compressed data, the receiving end does not need to calculate and restore the data to be compressed according to the compressed data, but can use the data compression slope reference coefficient in the compression map A decompressed table is found in the table, and the receiving end restores the decompressed table to obtain the data to be compressed.
  • the compression mapping table is preset to reduce the amount of calculation in the data compression process, improve the speed of data compression and decompression, and more adapt to the timeliness requirements of the real-time network, and ensure the overall real-time performance of the network.
  • a data compression device including:
  • the first acquiring module 10 is configured to acquire data to be compressed based on a preset time period; the data to be compressed includes multiple user data;
  • the second obtaining module 20 is configured to obtain a data compression slope reference coefficient corresponding to the data to be compressed; the data compression slope reference coefficient is obtained according to the modulation order and user signal power corresponding to each of the user data;
  • the compression module 30 is configured to compress the data to be compressed according to the data compression slope reference coefficient to obtain compressed data
  • the sending module 40 is configured to send the data compression slope reference coefficient and the compressed data to the receiving end, so that the receiving end decompresses the compressed data according to the data compression slope reference coefficient.
  • the second obtaining module 20 includes:
  • the first obtaining unit is configured to obtain the modulation order and user signal power corresponding to each of the user data based on the preset time period;
  • the calculation unit is configured to calculate the data compression slope reference coefficient according to the modulation order and the user signal power respectively corresponding to each of the user data.
  • the second obtaining module 20 includes:
  • the second acquiring unit is configured to acquire the data compression slope reference coefficient corresponding to the data to be compressed from the receiving end; the data compression slope reference coefficient is the modulation order corresponding to each of the user data by the receiving end, respectively Number and user signal power calculated.
  • the compression module 30 includes:
  • the compression unit is configured to substitute the data compression slope reference coefficient and the data to be compressed into a U-law compression formula to calculate the compressed data.
  • the data to be compressed includes unsigned data and sign bit data
  • the compression unit includes:
  • the first calculation subunit is configured to substitute the data compression slope reference coefficient and the unsigned data into the U-law compression formula to obtain unsigned compressed data through calculation;
  • the combination subunit is used to combine the unsigned compressed data with the sign bit data to obtain the compressed data.
  • the calculation unit includes:
  • a weighting subunit configured to perform weighting processing on the modulation order and the user signal power corresponding to each of the user data to obtain weighted data
  • the second calculation subunit is configured to calculate the data compression slope reference coefficient based on the weighted data, the maximum value of the modulation order, and the maximum value of the compression slope coefficient.
  • the compression module 30 includes:
  • the search unit is configured to search for a mapping value corresponding to the data compression slope reference coefficient and the data to be compressed in a preset compression mapping table;
  • the compression mapping table includes the mapping between the data to be compressed and the mapping value Relationship, the mapping relationship is associated with the data compression slope reference coefficient;
  • the determining unit is configured to determine the found mapping value as the compressed data.
  • the data compression device provided in this embodiment can execute the foregoing data compression method embodiment, and its implementation principles and technical effects are similar, and will not be repeated here.
  • Each module in the above-mentioned data compression device can be implemented in whole or in part by software, hardware, and a combination thereof.
  • the above-mentioned modules may be embedded in the form of hardware or independent of the processor in the computer equipment, or may be stored in the memory of the computer equipment in the form of software, so that the processor can call and execute the operations corresponding to the above-mentioned modules.
  • a computer device is also provided, and the computer device may be a server.
  • the computer equipment includes a processor, a memory, a network interface, and a database connected through a system bus.
  • the processor of the computer device is used to provide calculation and control capabilities.
  • the memory of the computer device includes a non-volatile storage medium and an internal memory.
  • the non-volatile storage medium stores an operating system, a computer program, and a database.
  • the internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium.
  • the database of the computer equipment is used to store data compressed data.
  • the network interface of the computer device is used to communicate with an external terminal through a network connection.
  • the computer program is executed by the processor to realize a data compression method.
  • a computer device including a memory and a processor, and a computer program is stored in the memory, and the processor implements the following steps when the processor executes the computer program:
  • the data to be compressed is acquired based on a preset time period; the data to be compressed includes multiple user data; the data compression slope reference coefficient corresponding to the data to be compressed is acquired; the data compression slope reference coefficient is based on each user
  • the data is obtained from the modulation order and user signal power respectively corresponding to the data; the data to be compressed is compressed according to the data compression slope reference coefficient to obtain compressed data; the data compression slope reference coefficient and the compressed data are sent To the receiving end, so that the receiving end decompresses the compressed data according to the data compression slope reference coefficient.
  • Non-volatile memory may include read only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory.
  • Volatile memory may include random access memory (RAM) or external cache memory.
  • RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous chain Channel (Synchlink) DRAM (SLDRAM), memory bus (Ramb microsecond) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.
  • SRAM static RAM
  • DRAM dynamic RAM
  • SDRAM synchronous DRAM
  • DDRSDRAM double data rate SDRAM
  • ESDRAM enhanced SDRAM
  • SLDRAM synchronous chain Channel
  • RDRAM synchronous chain Channel
  • RDRAM direct RAM
  • DRAM direct memory bus dynamic RAM
  • RDRAM memory bus dynamic RAM
  • a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:
  • the data to be compressed is acquired based on a preset time period; the data to be compressed includes multiple user data; the data compression slope reference coefficient corresponding to the data to be compressed is acquired; the data compression slope reference coefficient is based on each user
  • the data is obtained from the modulation order and user signal power respectively corresponding to the data; the data to be compressed is compressed according to the data compression slope reference coefficient to obtain compressed data; the data compression slope reference coefficient and the compressed data are sent To the receiving end, so that the receiving end decompresses the compressed data according to the data compression slope reference coefficient.

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Abstract

一种数据压缩方法、装置、计算机设备和计算机可读存储介质。所述数据压缩方法包括：基于预设时间周期，获取待压缩数据；所述待压缩数据包括多个用户数据（S100）；获取与所述待压缩数据对应的数据压缩斜率参考系数；所述数据压缩斜率参考系数是根据各所述用户数据分别对应的调制阶数及用户信号功率得到的（S200）；根据所述数据压缩斜率参考系数对所述待压缩数据进行压缩，得到压缩后数据（S300）；发送所述数据压缩斜率参考系数及所述压缩后数据至接收端，以使所述接收端根据所述数据压缩斜率参考系数对所述压缩后数据进行解压（S400）。采用本方法能够在保证通信系统性能的前提下，降低数据传输的带宽。

Description

数据压缩方法、装置、计算机设备和计算机可读存储介质 技术领域
本申请涉及移动通信技术领域，特别是涉及一种数据压缩方法、装置、计算机设备和计算机可读存储介质。
背景技术
随着通信网络的发展，无线接入网也在持续演进。为了应对未来爆炸性的移动数据流量增长和海量设备的连接，满足不断涌现的各类新业务和应用场景，全球范围普遍认为5G将在2020年左右开始有效商用。
在5G网络中，接入网被重构为CU(Centralized Unit，集中单元)、DU(Distribute Unit，分布单元)和AAU(Active Antenna Unit，有源天线单元)三个功能实体，其中，AAU分布式部署于站点，AAU和DU之间组成前传网络，DU和CU之间组成中传网络。
而随着数据流量的需求剧增，前传网络及中传网络的数据承载负荷将进一步加剧，因此，在5G网络中，在保证实时通信系统性能的前提下，如何减少CU和DU之间、DU和AAU之间的数据传输带宽，是一个亟待解决的问题。
发明内容
基于此，有必要针对上述技术问题，提供一种在5G网络中，能够有效减少CU和DU之间、DU和AAU之间的数据传输带宽的数据压缩方法、装置、计算机设备和计算机可读存储介质。
第一方面，本申请实施例提供了一种数据压缩方法，所述数据压缩方法包括：
基于预设时间周期，获取待压缩数据；所述待压缩数据包括多个用户数据；
获取与所述待压缩数据对应的数据压缩斜率参考系数；所述数据压缩斜率参考系数是根据各所述用户数据分别对应的调制阶数及用户信号功率得到的；
根据所述数据压缩斜率参考系数对所述待压缩数据进行压缩，得到压缩后数据；
发送所述数据压缩斜率参考系数及所述压缩后数据至接收端，以使所述接收端根据所述数据压缩斜率参考系数对所述压缩后数据进行解压。
第二方面，本申请实施例提供一种数据压缩装置，所述数据压缩装置包括：
第一获取模块，用于基于预设时间周期，获取待压缩数据；所述待压缩数据包括多个用户数据；
第二获取模块，用于获取与所述待压缩数据对应的数据压缩斜率参考系数；所述数据压缩斜率参考系数是根据各所述用户数据分别对应的调制阶数及用户信号功率得到的；
压缩模块，用于根据所述数据压缩斜率参考系数对所述待压缩数据进行压缩，得到压缩后数据；
发送模块，用于发送所述数据压缩斜率参考系数及所述压缩后数据至接收 端，以使所述接收端根据所述数据压缩斜率参考系数对所述压缩后数据进行解压。
第三方面，本申请实施例提供一种计算机设备，包括存储器和处理器，所述存储器存储有计算机程序，所述处理器执行所述计算机程序时实现如上述第一方面所述的方法的步骤。
第四方面，本申请实施例提供一种计算机可读存储介质，其上存储有计算机程序，所述计算机程序被处理器执行时实现如上述第一方面所述的方法的步骤。
本申请实施例提供的技术方案带来的有益效果至少包括：
通过基于预设时间周期，获取待压缩数据；所述待压缩数据包括多个用户数据；获取与所述待压缩数据对应的数据压缩斜率参考系数；所述数据压缩斜率参考系数是根据各所述用户数据分别对应的调制阶数及用户信号功率得到的；根据所述数据压缩斜率参考系数对所述待压缩数据进行压缩，得到压缩后数据；发送所述数据压缩斜率参考系数及所述压缩后数据至接收端，以使所述接收端根据所述数据压缩斜率参考系数对所述压缩后数据进行解压；由此，发送端根据获取到的数据压缩斜率参考系数对待压缩数据进行压缩，采用压缩后的数据与接收端进行数据传输，降低了数据传输的占用带宽，且压缩算法简单，易于工程实现，适用于5G网络中数据传输对实时性要求高的场景，保证了系统的整体性能。
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图1为一个实施例提供的数据压缩方法的应用环境图；
图2为一个实施例提供的数据压缩方法的流程示意图；
图3为一个实施例提供的数据压缩方法的流程示意图；
图4为一个实施例提供的数据压缩方法的流程示意图；
图5为一个实施例提供的数据压缩方法的流程示意图；
图6为一个实施例提供的数据压缩方法的流程示意图；
图7为一个实施例提供的数据压缩装置的结构框图。
具体实施方式
为了使本申请的目的、技术方案及优点更加清楚明白，以下结合附图及实施例，对本申请进行进一步详细说明。应当理解，此处描述的具体实施例仅仅用以解释本申请，并不用于限定本申请。
在LTE系统中，BBU(基带处理单元)和RRU(射频拉远单元)独立放置，BBU放置在中心机房或者主要站点，而RRU分布在各个站址上。BBU与RRU之间采用CPRI接口，每个CPRI端口连接一个RRU，每个RRU为两个流的天线，LTE带宽为20MHz，故CPRI接口的容量为2.45Gbps。如果采用大规模天线技术，BBU与RRU之间的CPRI容量将大幅增加，例如，如果带宽为20MHz，且RRU采用十六个流的天线，则CPRI容量需要19.66GHz；如果再进一步采用100MHz以上的带宽，则BBU与RRU之间的CPRI接口容量就需要几百Gbps，然而，受限于CPRI 端口的最大传输容量，LTE系统的前传网络无法处理如此大的传输容量。
为了应对未来爆炸性的移动数据流量增长和海量设备的连接，满足不断涌现的各类新业务和应用场景，全球范围普遍认为5G将在2020年左右开始有效商用。5G时代，考虑重新对BBU和RRU进行定义，将RRU与天线重构为AAU(有源天线单元)，将BBU重构为中央单元CU(Central Unit)和分布单元DU(Distributed Unit)两个功能实体，采用CU和DU独立部署的方式，以更好地满足场景和应用的需求。CU与DU功能的切分以处理内容的实时性进行区分，CU设备主要包括非实时的无线高层协议栈功能，同时也支持部分核心网功能下沉和边缘应用业务的部署，而DU设备主要处理物理层功能和实时性需求的功能。AAU分布式部署于站点，AAU和DU之间组成前传网络，DU和CU之间组成中传网络。
随着传输容量需求的增大，前传网络及中传网络的数据承载负荷也将进一步加剧，因此，5G网络中，在保证实时通信系统性能的前提下，如何减少CU和DU之间、DU和AAU之间的数据传输带宽，是一个亟待解决的问题。
本申请实施例提供的数据压缩方法、装置、计算机设备和计算机可读存储介质，旨在解决5G网络中，在保证系统实时通信性能的前提下，如何有效减少CU和DU之间、DU和AAU之间的数据传输带宽的技术问题。下面将通过实施例并结合附图具体地对本申请的技术方案以及本申请的技术方案如何解决上述技术问题进行详细说明。下面这几个具体的实施例可以相互结合，对于相同或相似的概念或过程可能在某些实施例中不再赘述。
本申请提供的数据压缩方法可以应用于如图1所示的5G接入网架构中，具体是应用在该架构中的发送端。在该架构中，沿上行通信链路方向，发送端可以是AAU，对应的接收端则为DU；发送端也可以是DU，对应的接收端则为CU；沿下行通信链路方向，发送端可以是CU，对应的接收端则为DU；发送端还可以是DU，则对应的接收端为AAU。
需要说明的是，本申请实施例提供的数据压缩方法，其执行主体可以是数据压缩装置，该数据压缩装置可以通过软件、硬件或者软硬件结合的方式实现成为发送端的部分或者全部。下述方法实施例中，均以执行主体是发送端为例来进行说明。
请参考图2，其示出了本申请实施例提供的一种数据压缩方法的流程图，如图2所示，本实施例数据压缩方法可以包括以下步骤：
步骤S100，基于预设时间周期，获取待压缩数据，待压缩数据包括多个用户数据。
本实施例中，发送端基于预设时间周期，获取待压缩数据，其中，待压缩数据包括该预设时间周期内的多个用户终端对应的用户数据；待压缩数据为发送端处理完成的需要发送给接收端的传输数据，在上行通信链路方向，用户终端发送上行用户数据包至发送端，发送端对该数据包进行处理后，得到待压缩数据；在下行通信链路方向，基站发送下行用户数据包至发送端，发送端对该数据包进行处理后，得到待压缩数据；可以理解的是，对于不同的网络制式， 上行用户数据包以及下行用户数据包所包括的用户数据，可以是时域数据或者频域数据，在此不做具体限制。预设时间周期可以是一个OFDM(Orthogonal Frequency Division Multiplexing，正交频分复用)符号、一个时隙、一个子帧、多个OFDM符号、多个时隙、多个子帧中的一种。
步骤S200，获取与待压缩数据对应的数据压缩斜率参考系数，该数据压缩斜率参考系数是根据各用户数据分别对应的调制阶数及用户信号功率得到的。
发送端获取与待压缩数据对应的数据压缩斜率参考系数，该数据压缩斜率参考系数是根据各用户数据分别对应的调制阶数及用户信号功率得到的。具体地，数据压缩斜率参考系数可以是发送端根据各用户数据分别对应的调制阶数及用户信号功率计算得到的；也可以是发送端从接收端获取到的，即根据各用户数据分别对应的调制阶数及用户信号功率计算数据压缩斜率参考系数的过程是在接收端进行的，由接收端计算完成后将该数据压缩斜率参考系数发送至发送端。
各用户数据对应不同的用户终端，各用户终端的调制阶数及用户信号功率是由基站分配；具体地，在上行通信链路方向，各用户终端分别对应的上行发送功率即为各用户终端的用户信号功率，上行发送功率是由基站分配给各用户终端的；在下行通信链路方向，基站与各用户终端对应的下行发送功率即为各用户终端的用户信号功率。以上行通信链路为例，发送端是AAU，对应的接收端为DU时，DU从核心网侧获取AAU模块下各用户数据分别对应的调制阶数及用户信号功率后，DU直接计算数据压缩斜率参考系数，并将计算得到的数据压缩斜率参考系数发送至AAU，供AAU对待压缩数据进行压缩；以下行通信链路为例，发送端是DU，对应的接收端为AAU时，DU从核心网侧获取DU模块下各用户数据分别对应的调制阶数及用户信号功率后，计算数据压缩斜率参考系数，并根据该压缩斜率参考系数对待压缩数据进行压缩，将压缩后得到的数据再发送至AAU。本实施例中，作为一种实施方式，用户信号功率根据基站对各用户终端分配的频域和时域资源数进行统计等效获得。
步骤S300，根据数据压缩斜率参考系数对待压缩数据进行压缩，得到压缩后数据。
本实施例中，发送端具体采用U律压缩对待压缩数据进行压缩，发送端将数据压缩斜率参考系数及待压缩数据代入U律压缩公式中，计算得到压缩后数据。
具体地，U律压缩公式如公式1所示：
Figure PCTCN2019124694-appb-000001
其中，UL_u为发送端获取到的数据压缩斜率参考系数，x表示压缩前输入的定点量化数据(待压缩数据)，将数据压缩斜率参考系数及待压缩数据代入公式1中，计算得到的y,y表示压缩后输出定点量化数据，即为该待压缩数据根据该数据压缩斜率参考系数压缩得到的压缩后数据。
步骤S400，发送数据压缩斜率参考系数及压缩后数据至接收端，以使接收端根据数据压缩斜率参考系数对压缩后数据进行解压。
发送端发送数据压缩斜率参考系数及压缩后数据至接收端，接收端接收到该数据压缩斜率参考系数及压缩后数据后，根据该数据压缩斜率参考系数对压缩后数据进行解压，解压后恢复得到待压缩数据。
本实施例通过基于预设时间周期，获取待压缩数据；待压缩数据包括多个用户数据；获取与待压缩数据对应的数据压缩斜率参考系数；数据压缩斜率参考系数是根据各用户数据分别对应的调制阶数及用户信号功率得到的；根据数据压缩斜率参考系数对待压缩数据进行压缩，得到压缩后数据；发送数据压缩斜率参考系数及压缩后数据至接收端，以使接收端根据数据压缩斜率参考系数对压缩后数据进行解压；由此，发送端根据获取到的数据压缩斜率参考系数对待压缩数据进行压缩，采用压缩后的数据与接收端进行数据传输，降低了数据传输的占用带宽，且压缩算法简单，易于工程实现，适用于5G网络中数据传输对实时性要求高的场景，保证了系统的整体性能。
图3为另一个实施例提供的数据压缩方法的流程示意图。在上述图2所示实施例的基础上，本实施例数据压缩方法，步骤S200具体包括：
步骤S210，基于预设时间周期，获取各用户数据分别对应的调制阶数及用户信号功率。
本实施例中，具体地，以下行通信链路中，DU为发送端、AAU为接收端为例，各用户数据分别对应不同的用户终端，DU基于该预设时间周期，统计DU下N个用户终端分别对应的调制阶数DL_M1，DL_M2…DL_MN、统计DU下N个用户终端分别对应的用户信号功率DL_P1，DL_P2…DL_PN。
步骤S220，根据各用户数据分别对应的调制阶数及用户信号功率，计算得到数据压缩斜率参考系数。
本实施例中，作为一种实施方式，步骤S220可以包括如下细化步骤：
步骤a,对各用户数据分别对应的调制阶数及用户信号功率进行加权处理，得到加权后数据。
步骤b,基于加权后数据、调制阶数最大值和压缩斜率系数最大值，计算得到数据压缩斜率参考系数。
具体地，DU将DL_M1，DL_M2…DL_MN及DL_P1，DL_P2…DL_PN代入公式2中，计算得到数据压缩斜率参考系数，公式2如下所示：
Figure PCTCN2019124694-appb-000002
其中，UL_u为数据压缩斜率参考系数，N为大于0的正整数，max_M表示调制阶数最大值，例如，DU获取到用户终端的最大调制阶数为256QAM，则max_M＝8；max_u表示U律压缩公式中压缩斜率系数最大值，该压缩斜率系数最大值默认值配置256，由此，DU根据各用户数据分别对应的调制阶数及用户信号功率，计算得到数据压缩斜率参考系数。
可以理解的是，本实施例中，下行通信链路中，发送端还可以是CU、接收 端为DU，CU基于该预设时间周期，统计CU下各用户终端分别对应的调制阶数及用户信号功率，CU根据各用户数据分别对应的调制阶数、用户信号功率及公式2，计算得到数据压缩斜率参考系数。
本实施例发送端基于预设时间周期，获取发送端下各用户数据分别对应的调制阶数及用户信号功率，根据各用户数据分别对应的调制阶数及用户信号功率，计算得到数据压缩斜率参考系数；发送端进一步根据该数据压缩斜率参考系数对待压缩数据进行压缩，得到压缩后数据，由此，在下行通信链路中，DU或CU通过数据压缩斜率参考系数对待压缩数据进行压缩后再进行传输，有效降低了下行通信链路中DU与AAU、CU与DU之间数据带宽。
图4为另一个实施例提供的数据压缩方法的流程示意图。在上述图2所示实施例的基础上，步骤S200，包括：
步骤S230，从接收端获取与待压缩数据对应的数据压缩斜率参考系数。
其中，数据压缩斜率参考系数是接收端根据各用户数据分别对应的调制阶数及用户信号功率计算得到的。
本实施例中，具体地，以上行通信链路中，AAU为发送端、DU为接收端为例，DU基于该预设时间周期，统计AAU下N个用户终端分别对应的调制阶数UL_M1，UL_M2…UL_MN、统计AAU下N个用户终端分别对应的用户信号功率UL_P1，UL_P2…UL_PN，进一步地，DU将UL_M1，UL_M2…UL_MN及UL_P1，UL_P2…UL_PN代入公式3中，计算得到数据压缩斜率参考系数，公式3如下所示：
Figure PCTCN2019124694-appb-000003
其中，其中，UL_u为数据压缩斜率参考系数，N为大于0的正整数，max_M表示调制阶数最大值，例如，DU获取到用户终端的最大调制阶数为256QAM，则max_M＝8；max_u表示U律压缩公式中压缩斜率系数最大值，该压缩斜率系数最大值默认值配置256，由此，DU根据各用户数据分别对应的调制阶数及用户信号功率，计算得到数据压缩斜率参考系数，并将该数据压缩斜率参考系数发送至AAU，供AAU对待压缩数据进行压缩。
由于用户终端对应的调制阶数及用户信号功率均是由基站分配的，继续以AAU为发送端为例，若由AAU计算数据压缩斜率参考系数，则AAU下N个用户终端分别对应的用户信号功率及用户信号功率是由核心网侧下发至CU，CU传输至DU，再由DU传输至AAU，再由AAU计算；在本实施例中，为了减少DU和AAU之间的数据传输带宽，AAU下N个用户终端分别对应的用户信号功率及用户信号功率传输至DU时，则由DU直接计算数据压缩斜率参考系数，再将计算得到的数据压缩斜率参考系数发送至AAU，AAU进一步根据DU发送的数据压缩斜率参考系数对待压缩数据进行压缩，进一步降低了AAU和DU之间的数据传输带宽。
本实施例中，作为一种可能的实施方式，上行通信链路中，发送端还可以是DU、接收端为CU，CU基于该预设时间周期，统计DU下各用户终端分别对应 的调制阶数及用户信号功率，CU根据获取到的各调制阶数、用户信号功率及公式3，计算得到数据压缩斜率参考系数，并发送该数据压缩斜率参考系数至DU，DU根据CU发送的数据压缩斜率参考系数对待压缩数据进行压缩，得到压缩后数据，进一步降低了DU和CU之间的数据传输带宽。
图5为另一个实施例提供的数据压缩方法的流程示意图。待压缩数据包括无符号数据及符号位数据，在上述图2所示实施例的基础上，步骤S300，包括：
步骤S310，将数据压缩斜率参考系数及无符号数据代入U律压缩公式中，计算得到无符号压缩数据。
待压缩数据包括无符号数据及符号位数据，具体地，符号位数据用于表征无符号数据的正负，本实施例中，压缩时对待压缩数据中的符号位数据不做压缩处理，仅将数据压缩斜率参考系数及无符号数据代入U律压缩公式中，计算得到无符号压缩数据。
步骤S320，将无符号压缩数据与符号位数据进行组合，得到压缩后数据。
将用于表征无符号数据正负的符号位数据与压缩后的无符号数据进行组合，得到压缩后数据；发送端将该压缩后数据发至接收端后，接收端根据数据压缩斜率参考系数对压缩后数据中的无符号压缩数据进行解压，得到无符号数据，接收端再将压缩后数据中的符号位数据与解压得到的无符号数据进行组合，恢复得到待压缩数据。
本实施例待压缩数据包括无符号数据及符号位数据，通过将数据压缩斜率参考系数及无符号数据代入U律压缩公式中，计算得到无符号压缩数据，将无符号压缩数据与符号位数据进行组合，得到压缩后数据，由此，确保了待压缩数据为负数时，数据压缩及解压的准确性。
图6为另一个实施例提供的数据压缩方法的流程示意图。在上述图2所示实施例的基础上，步骤S300，包括：
步骤S301，在预置的压缩映射表中，查找与数据压缩斜率参考系数及待压缩数据对应的映射值。
压缩映射表包括待压缩数据及映射值之间的映射关系，映射关系与数据压缩斜率参考系数相关联。
在本实施例中，具体地，为了提升数据压缩及数据解压的处理速度，离线制作压缩映射表。计算待压缩数据对应的数据压缩斜率参考系数，再根据该数据压缩斜率参考系数对待压缩数据进行压缩，得到压缩后数据，将计算得到的多个压缩后数据与其对应的数据压缩斜率参考系数及待压缩数据形成压缩映射表。在实际实施时，发送端基于预设时间周期，获取待压缩数据，以上行通信链路为例，发送端是AAU，对应的接收端为DU时，DU将计算得到的数据压缩斜率参考系数发送至AAU，AAU不必再将待压缩数据及数据压缩斜率参考系数代入U律压缩公式中计算压缩后数据，而可以直接在预置的压缩映射表中，查找与该数据压缩斜率参考系数及待压缩数据对应的映射值即可；以下行通信链路为例，发送端是DU，对应的接收端为AAU时，DU根据DU模块下各用户数据分别对应 的调制阶数及用户信号功率，计算得到数据压缩斜率参考系数后，DU不必再将待压缩数据及数据压缩斜率参考系数代入U律压缩公式中计算压缩后数据，而可以直接在预置的压缩映射表中，查找与数据压缩斜率参考系数及待压缩数据对应的映射值。
步骤S302，将查找到的映射值确定为压缩后数据。
发送端将在压缩映射表中查找到的与数据压缩斜率参考系数及待压缩数据对应的映射值确定为该待压缩数据对应的压缩后数据。
进一步地，作为一种实施方式，接收端在接收到数据压缩斜率参考系数及压缩后数据后，不必再根据压缩后数据计算还原得到待压缩数据，而可以通过数据压缩斜率参考系数在该压缩映射表中查找到一张解压缩表格，接收端对该解压缩表格进行还原恢复，得到待压缩数据。
本实施例通过预置压缩映射表，减小了数据压缩过程中的计算量，提升了数据压缩及解压的速度，更适应实时性网络对时效的要求，保证了网络的整体实时性能。
应该理解的是，虽然图2-6的流程图中的各个步骤按照箭头的指示依次显示，但是这些步骤并不是必然按照箭头指示的顺序依次执行。除非本文中有明确的说明，这些步骤的执行并没有严格的顺序限制，这些步骤可以以其它的顺序执行。而且，图2-6中的至少一部分步骤可以包括多个子步骤或者多个阶段，这些子步骤或者阶段并不必然是在同一时刻执行完成，而是可以在不同的时刻执行，这些子步骤或者阶段的执行顺序也不必然是依次进行，而是可以与其它步骤或者其它步骤的子步骤或者阶段的至少一部分轮流或者交替地执行。
在一个实施例中，如图7所示，提供了一种数据压缩装置，包括：
第一获取模块10，用于基于预设时间周期，获取待压缩数据；所述待压缩数据包括多个用户数据；
第二获取模块20，用于获取与所述待压缩数据对应的数据压缩斜率参考系数；所述数据压缩斜率参考系数是根据各所述用户数据分别对应的调制阶数及用户信号功率得到的；
压缩模块30，用于根据所述数据压缩斜率参考系数对所述待压缩数据进行压缩，得到压缩后数据；
发送模块40，用于发送所述数据压缩斜率参考系数及所述压缩后数据至接收端，以使所述接收端根据所述数据压缩斜率参考系数对所述压缩后数据进行解压。
可选地，第二获取模块20包括：
第一获取单元，用于基于所述预设时间周期，获取各所述用户数据分别对应的调制阶数及用户信号功率；
计算单元，用于根据各所述用户数据分别对应的所述调制阶数及所述用户信号功率，计算得到所述数据压缩斜率参考系数。
可选地，第二获取模块20包括：
第二获取单元，用于从所述接收端获取与所述待压缩数据对应的数据压缩 斜率参考系数；所述数据压缩斜率参考系数是所述接收端根据各所述用户数据分别对应的调制阶数及用户信号功率计算得到的。
可选地，压缩模块30包括：
压缩单元，用于将所述数据压缩斜率参考系数及所述待压缩数据代入U律压缩公式中，计算得到所述压缩后数据。
可选地，所述待压缩数据包括无符号数据及符号位数据，所述压缩单元包括：
第一计算子单元，用于将所述数据压缩斜率参考系数及所述无符号数据代入U律压缩公式中，计算得到无符号压缩数据；
组合子单元，用于将所述无符号压缩数据与所述符号位数据进行组合，得到所述压缩后数据。
可选地，所述计算单元包括：
加权子单元，用于对各所述用户数据分别对应的所述调制阶数及所述用户信号功率进行加权处理，得到加权后数据；
第二计算子单元，用于基于所述加权后数据、调制阶数最大值和压缩斜率系数最大值，计算得到所述数据压缩斜率参考系数。
可选地，压缩模块30包括：
查找单元，用于在预置的压缩映射表中，查找与所述数据压缩斜率参考系数及所述待压缩数据对应的映射值；所述压缩映射表包括待压缩数据及映射值之间的映射关系，所述映射关系与所述数据压缩斜率参考系数相关联；
确定单元，用于将查找到的所述映射值确定为所述压缩后数据。
本实施例提供的数据压缩装置，可以执行上述数据压缩方法实施例，其实现原理和技术效果类似，在此不再赘述。
关于数据压缩装置的具体限定可以参见上文中对于数据压缩方法的限定，在此不再赘述。上述数据压缩装置中的各个模块可全部或部分通过软件、硬件及其组合来实现。上述各模块可以硬件形式内嵌于或独立于计算机设备中的处理器中，也可以以软件形式存储于计算机设备中的存储器中，以便于处理器调用执行以上各个模块对应的操作。
在一个实施例中，还提供了一种计算机设备，该计算机设备可以是服务器。该计算机设备包括通过系统总线连接的处理器、存储器、网络接口和数据库。其中，该计算机设备的处理器用于提供计算和控制能力。该计算机设备的存储器包括非易失性存储介质、内存储器。该非易失性存储介质存储有操作系统、计算机程序和数据库。该内存储器为非易失性存储介质中的操作系统和计算机程序的运行提供环境。该计算机设备的数据库用于存储数据压缩数据。该计算机设备的网络接口用于与外部的终端通过网络连接通信。该计算机程序被处理器执行时以实现一种数据压缩方法。
本领域技术人员可以理解，以上描述的结构，仅仅是与本申请方案相关的部分结构，并不构成对本申请方案所应用于其上的计算机设备的限定，具体的计算机设备可以包括比以上描述更多或更少的部件，或者组合某些部件，或者 具有不同的部件布置。
在一个实施例中，提供了一种计算机设备，包括存储器和处理器，存储器中存储有计算机程序，该处理器执行计算机程序时实现以下步骤：
基于预设时间周期，获取待压缩数据；所述待压缩数据包括多个用户数据；获取与所述待压缩数据对应的数据压缩斜率参考系数；所述数据压缩斜率参考系数是根据各所述用户数据分别对应的调制阶数及用户信号功率得到的；根据所述数据压缩斜率参考系数对所述待压缩数据进行压缩，得到压缩后数据；发送所述数据压缩斜率参考系数及所述压缩后数据至接收端，以使所述接收端根据所述数据压缩斜率参考系数对所述压缩后数据进行解压。
本领域普通技术人员可以理解实现上述实施例方法中的全部或部分流程，是可以通过计算机程序来指令相关的硬件来完成，所述的计算机程序可存储于一非易失性计算机可读取存储介质中，该计算机程序在执行时，可包括如上述各方法的实施例的流程。其中，本申请所提供的各实施例中所使用的对存储器、存储、数据库或其它介质的任何引用，均可包括非易失性和/或易失性存储器。非易失性存储器可包括只读存储器(ROM)、可编程ROM(PROM)、电可编程ROM(EPROM)、电可擦除可编程ROM(EEPROM)或闪存。易失性存储器可包括随机存取存储器(RAM)或者外部高速缓冲存储器。作为说明而非局限，RAM以多种形式可得，诸如静态RAM(SRAM)、动态RAM(DRAM)、同步DRAM(SDRAM)、双数据率SDRAM(DDRSDRAM)、增强型SDRAM(ESDRAM)、同步链路(Synchlink)DRAM(SLDRAM)、存储器总线(Ramb微秒)直接RAM(RDRAM)、直接存储器总线动态RAM(DRDRAM)、以及存储器总线动态RAM(RDRAM)等。
在一个实施例中，提供了一种计算机可读存储介质，其上存储有计算机程序，计算机程序被处理器执行时实现以下步骤：
基于预设时间周期，获取待压缩数据；所述待压缩数据包括多个用户数据；获取与所述待压缩数据对应的数据压缩斜率参考系数；所述数据压缩斜率参考系数是根据各所述用户数据分别对应的调制阶数及用户信号功率得到的；根据所述数据压缩斜率参考系数对所述待压缩数据进行压缩，得到压缩后数据；发送所述数据压缩斜率参考系数及所述压缩后数据至接收端，以使所述接收端根据所述数据压缩斜率参考系数对所述压缩后数据进行解压。
以上所述实施例的各技术特征可以进行任意的组合，为使描述简洁，未对上述实施例中的各个技术特征所有可能的组合都进行描述，然而，只要这些技术特征的组合不存在矛盾，都应当认为是本说明书记载的范围。
以上所述实施例仅表达了本申请的几种实施方式，其描述较为具体和详细，但并不能因此而理解为对发明专利范围的限制。应当指出的是，对于本领域的普通技术人员来说，在不脱离本申请构思的前提下，还可以做出若干变形和改进，这些都属于本申请的保护范围。因此，本申请专利的保护范围应以所附权利要求为准。

Claims (10)

  1. 一种数据压缩方法，所述方法包括：
    基于预设时间周期，获取待压缩数据；所述待压缩数据包括多个用户数据；
    获取与所述待压缩数据对应的数据压缩斜率参考系数；所述数据压缩斜率参考系数是根据各所述用户数据分别对应的调制阶数及用户信号功率得到的；
    根据所述数据压缩斜率参考系数对所述待压缩数据进行压缩，得到压缩后数据；
    发送所述数据压缩斜率参考系数及所述压缩后数据至接收端，以使所述接收端根据所述数据压缩斜率参考系数对所述压缩后数据进行解压。
  2. 根据权利要求1所述的数据压缩方法，其特征在于，所述获取与所述待压缩数据对应的数据压缩斜率参考系数，包括：
    基于所述预设时间周期，获取各所述用户数据分别对应的调制阶数及用户信号功率；
    根据各所述用户数据分别对应的所述调制阶数及所述用户信号功率，计算得到所述数据压缩斜率参考系数。
  3. 根据权利要求1所述的数据压缩方法，其特征在于，获取与所述待压缩数据对应的数据压缩斜率参考系数，包括：
    从所述接收端获取与所述待压缩数据对应的数据压缩斜率参考系数；所述数据压缩斜率参考系数是所述接收端根据各所述用户数据分别对应的调制阶数及用户信号功率计算得到的。
  4. 根据权利要求1-3任一项所述的数据压缩方法，其特征在于，所述根据所述数据压缩斜率参考系数对所述待压缩数据进行压缩，得到压缩后数据，包括：
    将所述数据压缩斜率参考系数及所述待压缩数据代入U律压缩公式中，计算得到所述压缩后数据。
  5. 根据权利要求4所述的数据压缩方法，其特征在于，所述待压缩数据包括无符号数据及符号位数据，所述将所述数据压缩斜率参考系数及所述待压缩数据代入U律压缩公式中，计算得到所述压缩后数据，包括：
    将所述数据压缩斜率参考系数及所述无符号数据代入U律压缩公式中，计算得到无符号压缩数据；
    将所述无符号压缩数据与所述符号位数据进行组合，得到所述压缩后数据。
  6. 根据权利要求2所述的数据压缩方法，其特征在于，所述根据各所述用户数据分别对应的所述调制阶数及所述用户信号功率，计算得到所述数据压缩斜率参考系数，包括：
    对各所述用户数据分别对应的所述调制阶数及所述用户信号功率进行加权处理，得到加权后数据；
    基于所述加权后数据、调制阶数最大值和压缩斜率系数最大值，计算得到所述数据压缩斜率参考系数。
  7. 根据权利要求1所述的数据压缩方法，其特征在于，所述根据所述数据压缩斜率参考系数对所述待压缩数据进行压缩，得到压缩后数据，包括：
    在预置的压缩映射表中，查找与所述数据压缩斜率参考系数及所述待压缩 数据对应的映射值；所述压缩映射表包括待压缩数据及映射值之间的映射关系，所述映射关系与所述数据压缩斜率参考系数相关联；
    将查找到的所述映射值确定为所述压缩后数据。
  8. 一种数据压缩装置，所述装置包括：
    第一获取模块，用于基于预设时间周期，获取待压缩数据；所述待压缩数据包括多个用户数据；
    第二获取模块，用于获取与所述待压缩数据对应的数据压缩斜率参考系数；所述数据压缩斜率参考系数是根据各所述用户数据分别对应的调制阶数及用户信号功率得到的；
    压缩模块，用于根据所述数据压缩斜率参考系数对所述待压缩数据进行压缩，得到压缩后数据；
    发送模块，用于发送所述数据压缩斜率参考系数及所述压缩后数据至接收端，以使所述接收端根据所述数据压缩斜率参考系数对所述压缩后数据进行解压。
  9. 一种计算机设备，包括存储器和处理器，所述存储器存储有计算机程序，所述处理器执行所述计算机程序时实现权利要求1至7中任一项所述方法的步骤。
  10. 一种计算机可读存储介质，其上存储有计算机程序，所述计算机程序被处理器执行时实现权利要求1至7中任一项所述的方法的步骤。
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