WO2021136471A1 - 上行传输方法、计算机可读存储介质和分布式多天线系统 - Google Patents
上行传输方法、计算机可读存储介质和分布式多天线系统 Download PDFInfo
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- This application relates to the field of communication technology, in particular to an uplink transmission method against inter-carrier interference, a joint optimization method for the matrix coefficients of the inter-carrier interference self-cancellation coding matrix and the degree distribution coefficient of the rateless coding, a distributed multi-antenna system and Computer readable storage medium.
- DAS Distributed Antenna Systems
- DAS Distributed Antenna Systems
- the network status and channel status of the distributed multi-antenna system are more complicated and variable.
- Noise, interference and channel fading have a great impact on the quality and transmission reliability of electromagnetic wave signals. Severe noise, interference and channel fading may even cause the interruption of the communication process.
- error control technology is often used to protect the message to be sent in the actual transmission process.
- channel coding is an effective error control technology.
- HARQ Hybrid Automatic Repeat reQuest
- the sending node In a distributed multi-antenna system that uses a rateless code for channel coding, the sending node only needs the receiver to feed back an Acknowledge Character (ACK) signal to indicate successful decoding, which can effectively reduce signaling overhead.
- ACK Acknowledge Character
- the research on rateless codes in related technologies mainly includes degree distribution design, decoding method design, etc. Among them, the degree distribution function is directly related to the performance of rateless codes, and determines the decoding success rate, decoding overhead, and decoding complexity.
- Orthogonal Frequency Division Multiplexing (OFDM for short) technology is suitable for application in DAS systems due to its excellent anti-interference ability and high spectrum utilization.
- DAS systems using OFDM technology are susceptible to frequency deviation, which will cause Inter-Carrier Interference (ICI).
- ICI Inter-Carrier Interference
- the ICI self-elimination method can effectively combat ICI, and it is widely used because of its low implementation complexity.
- the ICI self-cancellation method in the related art is usually applied to the point-to-point transmission system.
- the research on the ICI self-cancellation method mainly includes the design of the coding matrix, the method of demodulation at the receiving end, etc.
- the design of the ICI self-cancellation coding matrix determines the system ICI elimination effect.
- a joint optimization method for the matrix coefficients of the inter-carrier interference self-cancellation coding matrix and the degree distribution coefficients of the rateless coding is provided, which is applied to the orthogonal frequency division multiplexing technology in the block fading channel.
- the method includes:
- the optimization problem is listed as:
- constraints of the optimization problem include:
- ⁇ max is the maximum tolerable frequency offset of the link from the user to the RRH; Is the maximum average code length; c 1 , c 2 , c 3 are the matrix coefficients of the ICI self-cancellation coding matrix; ⁇ d ⁇ represents the degree distribution coefficient of the edge of the output node of the LT code graph without rate code; ⁇ j is LT The degree distribution coefficient of the edge of the output node of the code graph with degree j; d c is the maximum degree of the edge of the output node of the LT code graph; T is the ICI self-cancellation coding matrix; ⁇ is the preset value greater than zero; x u Is external information; ⁇ 1 , ⁇ 2 , ⁇ 3 , and ⁇ 4 are the proportions of variable nodes with degrees of 1, 2, 3 or 4 in the LDPC code graph respectively; Is a constant that has nothing to do with the instantaneous gain of the channel; It is the minimum threshold of external information for correct
- the solving the optimization problem to obtain the optimized matrix coefficient and the degree distribution coefficient includes:
- the sum constraint of the degree distribution of the edge of the output node of the LT code graph Calculate the minimum value of the channel coding code length corresponding to the multiple sets of matrix coefficients and the degree distribution coefficient of the edge of the output node of the LT code graph under the conditions of the receiving end decoding start condition and the receiving end decoding convergence condition;
- the minimum value of the channel coding code length and the degree distribution coefficient of the edge of the output node of the LT code graph are selected from the multiple sets of matrix coefficients by using a genetic algorithm;
- the matrix coefficient corresponding to the maximum value in the maximum tolerable frequency offset value and the degree distribution coefficient of the edge of the output node of the corresponding LT code graph are taken as the optimal solution of the optimization problem.
- using a genetic algorithm to select matrix coefficients from the multiple sets of matrix coefficients includes:
- the randomly extracting several sets of matrix coefficients according to the cumulative probability includes:
- M is the number of groups of the multiple sets of matrix coefficients
- q k is the cumulative probability of the k-th group of matrix coefficients.
- the method further includes:
- the randomly selected groups of matrix coefficients are paired in pairs, and the binary codes of each pair of matrix coefficients are exchanged with the first preset probability to obtain several groups of matrix coefficients that are updated for the first time;
- the updated matrix coefficient is used as the matrix coefficient for calculating the maximum tolerable frequency deviation value.
- an uplink transmission method against inter-carrier interference which is applied to a distributed multi-antenna system using orthogonal frequency division multiplexing technology under a block fading channel, and the method includes:
- the distributed multi-antenna system receives uplink transmission signals from multiple remote radio heads to obtain multiple uplink transmission signals; wherein, the uplink transmission signal is the rateless encoding of user information and then modulated to obtain the uplink modulation signal. Obtained by transforming the ICI self-cancellation coding matrix; the matrix coefficients of the ICI self-cancellation coding matrix are determined by the joint optimization method described in the first aspect;
- the distributed multi-antenna system performs preprocessing and quantization processing on the multiple uplink transmission signals respectively to obtain multiple quantized signals
- the distributed multi-antenna system performs soft demodulation on the multiple quantized signals according to the matrix coefficients, and then uses a belief propagation algorithm to perform joint decoding to obtain the user information.
- the distributed multi-antenna system performs soft demodulation on the multiple quantized signals according to the matrix coefficients, and then uses a belief propagation algorithm to perform joint decoding, and obtaining the user information includes:
- the distributed multi-antenna system calculates the log-likelihood ratios of each coded bit of the rateless coding according to the multiple quantized signals, and then combines the log-likelihood ratios of the same coded bits to obtain a combined log-likelihood ratio ;
- the distributed multi-antenna system uses a belief propagation algorithm to perform joint decoding according to the combined log-likelihood ratio to obtain the user information.
- a distributed multi-antenna system is also provided.
- the distributed multi-antenna system is applied to a block fading channel and adopts orthogonal frequency division multiplexing technology.
- the distributed multi-antenna system includes Multiple radio frequency remote heads, baseband processing unit pools, of which,
- the remote radio head is used to receive an uplink transmission signal and send the uplink transmission signal to the baseband processing unit pool after preprocessing and quantization processing; wherein the uplink transmission signal is to perform rateless encoding of user information Afterwards, the uplink modulation signal is obtained by modulating, and then transformed according to the ICI self-cancellation coding matrix; the matrix coefficients of the ICI self-cancellation coding matrix are determined by jointly optimizing the matrix coefficients and the frequency distribution coefficients of the rateless coding;
- the baseband processing unit pool is configured to perform soft demodulation on the multiple quantized signals respectively according to the matrix coefficients, and then perform joint decoding using a belief propagation algorithm to obtain the user information.
- a computer-readable storage medium on which computer program instructions are stored, and when the computer program instructions are executed by a processor, the inter-carrier interference self-cancellation encoding matrix is implemented.
- the above-mentioned uplink transmission method against inter-carrier interference the joint optimization method of the matrix coefficients of the inter-carrier interference self-cancellation coding matrix and the degree distribution coefficient of the rateless coding, the distributed multi-antenna system and the computer-readable storage medium have the following advantages:
- Fig. 1 is a flowchart of a joint optimization method according to an embodiment of the present application.
- Fig. 2 is a flowchart of a joint optimization method according to a preferred embodiment of the present application.
- Fig. 3 is a schematic structural diagram of a distributed multi-antenna system according to an embodiment of the present application.
- Fig. 4 is a flowchart of an uplink transmission method against ICI according to an embodiment of the present application.
- Figure 5 is a rateless code decoding diagram of an embodiment of the present application.
- Fig. 6 is a schematic diagram of simulation results of an embodiment of the present application.
- the various technologies described in this article can be used in various mobile communication systems, such as 2G, 3G, 4G, and 5G mobile communication systems and next-generation mobile communication systems, such as the Global System for Mobile communications (GSM) , Code Division Multiple Access (CDMA) system, Time Division Multiple Access (TDMA) system, Wideband Code Division Multiple Access (Wireless, abbreviated as WCDMA), Frequency Division Multiple Access (Frequency Division Multiple Addressing, FDMA) system, Orthogonal Frequency-Division Multiple Access (OFDMA) System, Single Carrier FDMA (SC-FDMA) System, General Packet Radio Service (General Packet Radio Service, GPRS) system, Long Term Evolution (LTE) system, 5G New Radio (NR) system, and other such communication systems.
- GSM Global System for Mobile communications
- CDMA Code Division Multiple Access
- TDMA Time Division Multiple Access
- WCDMA Wideband Code Division Multiple Access
- OFDMA Frequency Division Multiple Access
- OFDMA Orthogonal Frequency
- the joint optimization method of the matrix coefficients of the ICI self-cancellation coding matrix and the degree distribution coefficients of the rateless coding provided in this application is particularly suitable for a distributed multi-antenna system using OFDM technology under a block fading channel.
- the channel gain remains unchanged during one round of transmission, but changes after each round of transmission, so that even if the user does not know the channel state, the uplink transmission scheme using the above-mentioned joint optimization method can ensure wireless Transmission rate.
- the user in the embodiment of the present application refers to a node device that sends user information
- the node device may be a smart terminal or a relay device and other node devices that need to send user information.
- Fig. 1 is a flowchart of a joint optimization method according to an embodiment of the present application. The process includes the following steps:
- Step S101 According to the statistical information of the channel state and the external information transfer analysis of the decoding process, determine the optimization problem of jointly optimizing the matrix coefficient and the degree distribution coefficient with the goal of maximizing the system transmission rate;
- Step S102 Solve the optimization problem to obtain the optimized matrix coefficients and degree distribution coefficients.
- the matrix coefficients of the ICI self-cancellation coding matrix and the degree distribution coefficients of the rateless coding are jointly optimized, thereby solving the matrix coefficients of the ICI self-cancelling coding matrix and the degree distribution of the rateless coding.
- the coefficients are individually optimized, which leads to the difficulty of taking into account the wireless transmission rate and the ICI cancellation effect in the distributed multi-antenna OFDM system under the block fading channel.
- the ICI cancellation effect is improved on the basis of guaranteeing the wireless transmission rate.
- the optimization problem is listed as:
- constraints of the optimization problem include:
- ⁇ max is the maximum tolerable frequency offset of the link from the user to the RRH; Is the maximum average code length; c 1 , c 2 , c 3 are the matrix coefficients of the ICI self-cancellation coding matrix; ⁇ d ⁇ represents the degree distribution coefficient of the edge of the output node of the LT code graph without rate code; ⁇ j is LT The degree distribution coefficient of the edge of the output node of the code graph with degree j; d c is the maximum degree of the edge of the output node of the LT code graph; T is the ICI self-cancellation coding matrix; ⁇ is the preset value greater than zero; x u Is external information; ⁇ 1 , ⁇ 2 , ⁇ 3 , and ⁇ 4 are the proportions of variable nodes with degrees of 1, 2, 3 or 4 in the LDPC code graph respectively; Is a constant that has nothing to do with the instantaneous gain of the channel; It is the minimum threshold of external information for correct
- the constraint condition C4 ensures that after the uplink modulation signal is transformed according to the ICI self-cancellation coding matrix, the output signal power of the user will not increase.
- Fig. 2 is a flowchart of a joint optimization method according to a preferred embodiment of the present application.
- step S102 includes:
- Step S102-1 Exhaustive list of frequency offset values within a preset range
- Step S102-2 Under each exhaustive frequency offset value, randomly generate multiple sets of matrix coefficients that satisfy the constraint condition of the output signal power on the matrix coefficients of the ICI self-cancellation coding matrix; Calculate the minimum value of the channel coding code length corresponding to multiple sets of matrix coefficients and the degree distribution coefficient of the edge of the output node of the LT code graph under the condition of the sum of power distribution constraints, the receiving end decoding start condition, and the receiving end decoding convergence condition; According to the minimum value of the channel coding code length and the degree distribution coefficient of the edge of the output node of the LT code graph, a genetic algorithm is used to select matrix coefficients from multiple sets of matrix coefficients;
- Step S102-3 Calculate the maximum tolerable frequency offset value according to the selected matrix coefficients and the degree distribution coefficients of the edges of the output nodes of the corresponding LT code graph;
- Step S102-4 The matrix coefficient corresponding to the maximum value in the maximum tolerable frequency offset value and the degree distribution coefficient of the edge of the output node of the corresponding LT code graph are taken as the optimal solution of the optimization problem.
- step S102-2 according to the minimum value of the channel coding code length and the degree distribution coefficient of the edge of the output node of the LT code graph, the genetic algorithm is used to obtain the coefficients from multiple sets of matrix
- the selected matrix coefficients include:
- Step S102-2-1 According to the minimum value of the channel coding code length, calculate the probability that the matrix coefficient corresponding to the minimum value of the channel coding code length will be inherited to the next generation;
- Step S102-2-2 Calculate the cumulative probability of each group of matrix coefficients according to the probability that the matrix coefficients are inherited to the next generation;
- Step S102-2-3 According to the cumulative probability, randomly select several sets of matrix coefficients.
- step S102-2-3 includes: generating a uniformly distributed pseudo-random number s in the interval [0,1], if s ⁇ q 1 , select the first group of matrix coefficients, otherwise select the kth Group so that q k-1 ⁇ s ⁇ q k holds; repeat the above steps a total of M times to obtain M groups of matrix coefficients; where M is the number of groups of matrix coefficients; q k is the cumulative probability of the k-th group of matrix coefficients .
- the method further includes:
- Step S102-2-4 Use genetic algorithm to pair several groups of matrix coefficients obtained at random, and exchange the binary codes of each pair of matrix coefficients with the first preset probability to obtain several groups of first time Updated matrix coefficients;
- Step S102-2-5 Replace some random coded values in the binary code with the second preset probability for the obtained sets of matrix coefficients updated for the first time to obtain sets of matrix coefficients updated for the second time, and These sets of matrix coefficients updated for the second time are used as the matrix coefficients for calculating the maximum tolerable frequency offset value.
- FIG. 3 is a schematic structural diagram of a distributed multi-antenna system according to an embodiment of the present application.
- the system includes a remote radio head (RRH) and a baseband processing unit (BBU) pool.
- RRH remote radio head
- BBU baseband processing unit
- the fading channel statistical information is used to optimize the degree distribution of the rateless coding and the matrix coefficients of the ICI self-cancellation coding matrix.
- FIG. 4 is a flowchart of an uplink transmission method against ICI according to an embodiment of the present application.
- the uplink transmission method against ICI includes the following steps:
- Step S401 Determine the matrix coefficients of the ICI self-cancellation coding matrix and the degree distribution coefficients of the rateless coding by jointly optimizing the matrix coefficients and the degree distribution coefficients of the rateless coding;
- Step S402 After the user performs rateless coding of the user information according to the above-mentioned frequency distribution coefficient, the codeword is modulated to obtain an uplink modulation signal, and then transforms according to the ICI self-cancellation coding matrix corresponding to the above-mentioned matrix coefficient to obtain the uplink transmission signal. And send the uplink transmission signal to each remote radio head of the distributed multi-antenna system covering the user;
- Step S403 Each remote radio head of the distributed multi-antenna system receives the uplink transmission signal, and pre-processes these uplink transmission signals into baseband signals through the remote radio head, and then quantizes the signal and sends it to the distributed multi-antenna system The baseband processing unit pool;
- Step S404 The baseband processing unit pool of the distributed multi-antenna system performs soft demodulation on the received quantized signals according to the matrix coefficients of the ICI self-cancellation coding matrix, and then uses the belief propagation algorithm to perform joint decoding to obtain user information.
- the ICI self-cancellation method modulates the codeword of the rateless coding onto a group of adjacent subcarriers at the user end, each subcarrier has its own matrix coefficient, and jointly optimizes the degree distribution coefficients of the rateless coding and
- the matrix coefficients of the ICI self-cancellation coding matrix make the ICI reach the minimum value on the basis of ensuring the wireless transmission rate; at the receiving end of the distributed multi-antenna system, these matrix coefficients are used to linearly combine these sub-carriers to make the received uplink
- the residual ICI in the transmission signal is further reduced.
- step S404 includes the following steps: the baseband processing unit pool of the distributed multi-antenna system calculates the log-likelihood ratio of each coded bit of the rateless coding according to the multiple quantized signals, and then compares the pairs of the same coded bits. The number-likelihood ratio is combined to obtain the combined log-likelihood ratio; the baseband processing unit pool of the distributed multi-antenna system uses the belief propagation algorithm to perform joint decoding according to the combined log-likelihood ratio to obtain user information.
- Step 1 The distributed multi-antenna system based on the ICI self-cancellation coding matrix adopts OFDM modulation technology.
- a single user performs uplink communication with the BBU through L distributed multi-antennas, and the number of OFDM subcarriers is N.
- the user first uses rate-free coding to encode the original message m of length K into a code word c of length N.
- R P corresponds to a code rate of the LDPC code without rate as the precoding code, and then outputs a frequency distribution of ⁇ (x) is Luby transform code (Luby Transform codes, referred to as LT) coding.
- Luby transform code Luby Transform codes
- the order of T is N ⁇ W, and the coding efficiency is T is expressed as follows:
- c 1 , c 2 , and c 3 are matrix weight coefficients.
- the preprocessor of the RRH preprocesses the received signal to obtain the baseband signal:
- the quantification rules are as follows:
- Step 4 Each RRH r sends the obtained quantized signal to the BBU via a high-speed link; applying a differential receiving method, transforms the upload signal of the RRH r into a demodulated signal x′ r :
- Step 5 The baseband processing unit pool joins the decoder to perform iterative decoding.
- Figure 5 is a rateless code decoding diagram of a preferred embodiment of the present application.
- the baseband processing unit pool joint decoder performs iterative decoding including two steps: the first step is to perform iterative decoding on the entire decoding diagram until the input node The average value of the LLR exceeds a certain threshold x p ; the second step is to iteratively decode the LDPC decoding graph to eliminate residual errors.
- the specific procedure of the first step is as follows: in the 0th round of iterative decoding, the initial LLR of input node i in the decoding graph is The initial LLR of the output node is the first iteration of L(i), and the message sent from the input node i to the check node c is updated as follows:
- i' is the input node connected to the check node c except the input node i in the decoding graph.
- the message from the input node i to the output node o is updated as follows:
- o′ represents the output node other than o.
- the message sent by the output node o back to the input node i is updated as follows:
- i′ represents the input node other than i
- Z 0 is the LLR calculated by the output node according to the quantized value of the corresponding codeword bit, which is obtained in steps 2-4
- the LLR of the input node i in the current round is:
- the second step of iterative decoding is as follows: in the 0th round of iterative decoding of the LDPC subgraph, the message sent from the variable node v to the check node c is updated as follows:
- m v is the LLR of the input node in the last iteration of the previous iteration; in the l iteration, the message sent from the variable node v to the check node c is updated as follows:
- v' represents the variable nodes connected to the check node c except v.
- the joint optimization method of the degree distribution coefficients of the rateless coding and the matrix coefficients of the ICI self-cancellation coding matrix includes the following steps:
- Step 1 Analyze the transfer of external information in the decoding process.
- the LT input node passes the LLR message to the LDPC code graph check node, and the external information it carries is:
- ⁇ i is the proportion of variable nodes with degree i in the LDPC code graph
- I the ratio of the edges connected to the check node of degree j in the LDPC code graph
- d v is the maximum degree of the variable node in the LDPC code graph
- d′ c is the maximum degree of the check node in the LDPC code graph
- the LT input node transmits the message to the output node
- the external information is:
- the output nodes corresponding to the second, third, and fourth groups of coded bits return external information to the LT input node as follows:
- ⁇ d ⁇ is the coefficient of the degree distribution of the edge of the LT output node.
- Step 2 According to the statistical information of the channel state, determine the optimization problem of jointly optimizing the matrix coefficient and the degree distribution coefficient with the goal of maximizing the system transmission rate.
- the average degree of the input node of the LT code graph when the channel gain is ⁇ H ⁇ r and the frequency offset is ⁇ r among them Is a constant that has nothing to do with the instantaneous gain of the channel, Is the theoretical maximum achievable rate, Represents the channel capacity of binary input additive Gaussian white noise with a signal-to-noise ratio of ⁇ .
- ⁇ max is the maximum tolerable frequency offset value of the link from the user to the RRH, which is defined as: for any frequency offset
- Step 3 Solve the optimization problem to obtain the optimized matrix coefficients and degree distribution coefficients.
- step 3 the following steps are included:
- Step 31 Set the maximum number of iterations, and randomly generate M groups of matrix coefficients c 1 , c 2 , c 3 under any fixed frequency offset ⁇ r , perform binary coding on them, and initialize them at the same time
- Step 32 For each set of matrix coefficients c 1 , c 2 , c 3 , under the conditions of C1, C2 and C3, first Find the corresponding optimal ⁇ d ⁇ through the linear programming method under fixed conditions, and exhaustively on this basis Find the corresponding code length (i.e. ) The minimum value and the corresponding degree distribution ⁇ d ⁇ ;
- Step 34 For any fixed frequency offset ⁇ r , genetic algorithm is used to pair the matrix coefficients selected above, and each binary code of them is performed with the probability of Pr1 (between 0 and 1, for example, 0.97) Exchange to form two sets of new coefficients; next, for each newly generated set of coefficients, replace some random code values in the original code string with the probability of Pr2 (between 0 and 1, for example, 0.1), thus completing Another update;
- Step 35 Repeat step 32 to step 34 to optimize the corresponding matrix coefficients c 1 , c 2 , c 3 and degree distribution ⁇ d ⁇ with the smallest code length value;
- Step 36 Enumerate ⁇ r exhaustively within a certain range. For any ⁇ r , calculate the corresponding maximum tolerable frequency deviation from the matrix coefficients c 1 , c 2 , c 3 and the degree distribution ⁇ d ⁇ obtained in step 35 Choose the c 1 , c 2 , c 3 and the degree distribution ⁇ d ⁇ corresponding to the largest ⁇ r as the solution of the problem.
- Fig. 6 is a schematic diagram of the simulation results of the preferred embodiment of the present application. Compared with the standard OFDM system and BEC degree distribution in the related art, or the randomly generated matrix coefficient and BEC degree distribution scheme, it is based on the joint optimization method provided by the present application. The transmission rate is closer to the theoretical achievable rate, and the ICI elimination effect is improved.
- BEC Binary Erasure Channel
- a computer-readable storage medium on which computer program instructions are stored, and when the computer program instructions are executed by a processor, the aforementioned joint optimization method is implemented.
- the disclosed system, device, or method may be implemented in other ways.
- the device embodiments described above are merely illustrative.
- the division of the modules or units is only a logical function division. In actual implementation, there may be other division methods, for example, multiple units or components may be divided. It can be combined or integrated into another system, or some features can be ignored or not implemented.
- the displayed or discussed mutual coupling or direct coupling or communication connection may be indirect coupling or communication connection through some interfaces, devices or units, and may be in electrical, mechanical or other forms.
- the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of the embodiment.
- the functional units in the various embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units may be integrated into one unit.
- the above-mentioned integrated unit can be implemented in the form of hardware or software functional unit.
- the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer readable storage medium.
- the technical solution of the present application essentially or the part that contributes to the existing technology or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium , Including several instructions to make a computer device (which may be a personal computer, a server, or a network device, etc.) or a processor (processor) execute all or part of the steps of the methods described in the various embodiments of the present application.
- the foregoing processor may include a central processing unit (CPU), or a specific integrated circuit (Application Specific Integrated Circuit, ASIC for short), or may be configured to implement one or more integrated circuits of the embodiments of the present application.
- the above-mentioned storage medium can be used for mass storage of data or instructions.
- the memory may include a hard disk drive (Hard Disk Drive, referred to as HDD), floppy disk drive, flash memory, optical disk, magneto-optical disk, magnetic tape, or Universal Serial Bus (Universal Bus, referred to as USB) drive or two A combination of one or more of these.
- the storage may include removable or non-removable (or fixed) media.
- the memory can be internal or external to the data processing device.
- the memory is a non-volatile solid state memory.
- the memory includes read-only memory (ROM).
- ROM read-only memory
- the ROM can be mask-programmed ROM, programmable ROM (PROM), erasable PROM (EPROM), electrically erasable PROM (EEPROM), electrically rewritable ROM (EAROM) or flash memory or A combination of two or more of these.
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- Mobile Radio Communication Systems (AREA)
Abstract
一种对抗载波间干扰的上行传输方法、可读存储介质和分布式多天线系统，及载波间干扰自消除编码矩阵的矩阵系数和无速率编码的度数分布系数的联合优化方法。联合优化方法应用于在块衰落信道下采用正交频分复用技术的分布式多天线系统，包括：根据信道状态的统计信息和译码过程的外信息传递分析，确定以最大化系统传输速率为目标，联合优化矩阵系数和度数分布系数的最优化问题；求解最优化问题，得到最优化的矩阵系数和度数分布系数。
Description
相关申请
本申请要求2019年12月31日申请的，申请号为201911419491.2，发明名称为“上行传输方法、计算机可读存储介质和分布式多天线系统”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
本申请涉及通信技术领域，特别是涉及一种对抗载波间干扰的上行传输方法、载波间干扰自消除编码矩阵的矩阵系数和无速率编码的度数分布系数的联合优化方法、分布式多天线系统及计算机可读存储介质。
分布式多天线系统(Distributed Antenna Systems，简称为DAS)可以有效地解决下一代无线移动通信系统在频谱效率和发射功率两个方面的技术难题。并且它作为一种网络架构，可以和很多现有系统相融合以提高覆盖和系统性能。然而，与传统的蜂窝网络相比，分布式多天线系统的网络状态和信道状态更加复杂和可变。噪声、干扰与信道衰落对电磁波信号的质量和传输可靠性有很大的影响，严重的噪声、干扰与信道衰落甚至可能导致通信过程的中断。为了对抗无线信道这些不稳定因素以保证信息的可靠传输，实际传输过程中往往采用差错控制技术对要发送的消息进行保护。其中，信道编码即是一种有效的差错控制技术。
传统的固定速率的信道编码需要获取用户信道信息，并且当解码失败时使用混合自动重传请求(Hybrid Automatic Repeat reQuest，简称为HARQ)，这将增加数字前向链路的开销。而采用无速率码进行信道编码的分布式多天线系统中，发送节点仅需要接收器反馈确认字符(Acknowledge character，简称为ACK)信号以指示成功解码，能够有效减少信令开销。相关技术中无速率码的研究主要包括度数分布设计、译码方法设计等，其中度数分布函数与无速率码的性能直接相关，决定着译码成功率、译码开销和译码复杂度等。
此外，正交频分复用(Orthogonal Frequency Division Multiplexing，简称为OFDM)技术由于其出色的抗干扰能力和很高的频谱利用率等优点使其适合应用于DAS系统中。然而，采用OFDM技术的DAS系统容易受到频率偏差的影响，这将会导致载波间干扰(Inter-Carrier Interference，简称为ICI)。ICI自消除方法可以有效对抗ICI，而且因其实现复杂度低得到广 泛应用。相关技术中ICI自消除方法通常应用于点对点传输的系统中，对ICI自消除方法的研究主要包括编码矩阵的设计、接收端解调的方法等，其中ICI自消除编码矩阵的设计决定了该系统ICI的消除效果。
相关技术尚未有将ICI自消除方法应用于衰落信道下采用OFDM技术的DAS系统中，相关技术中仅单独优化ICI自消除编码矩阵的矩阵系数或者单独优化无速率编码的度数分布系数，这导致无法兼顾无线传输的速率和ICI消除效果。
发明内容
根据本申请的各种实施例，提供一种载波间干扰自消除编码矩阵的矩阵系数和无速率编码的度数分布系数的联合优化方法，应用于在块衰落信道下采用正交频分复用技术的分布式多天线系统，所述方法包括：
根据信道状态的统计信息和译码过程的外信息传递分析，确定以最大化系统传输速率为目标，联合优化所述矩阵系数和所述度数分布系数的最优化问题；
求解所述最优化问题，得到最优化的所述矩阵系数和所述度数分布系数。
在其中一些实施例中，所述最优化问题列出为：
所述最优化问题的约束条件包括：
(1)LT码图的输出节点的边的度数分布的和约束条件C1：
(2)接收端译码启动条件C2：
ω
1>θ
(3)接收端译码收敛条件C3：
(4)输出信号功率对ICI自消除编码矩阵的矩阵系数的约束条件C4：
|c
1|
2+|c
2|
2≤1,2|c
3|
2≤1
其中，ε
max为用户到RRH的链路最大可容忍频偏；
为最大平均码长；c
1,c
2,c
3为ICI自消除编码矩阵的矩阵系数；{ω
d}表示无速率码的LT码图的输出节点的边的度数分布系数；ω
j为LT码图中度数为j的输出节点的边的度数分布系数；d
c为LT码图的输出节点的边的最大度数；T为ICI自消除编码矩阵；θ为大于零的预设值；x
u为外信息；γ
1,γ
2,γ
3,γ
4分别为LDPC 码图中度数为1、2、3或4的变量节点的比例；
为与信道的即时增益无关的常数；
为正确译码的外信息最小门限；H
r,q表示第r个RRH的链路在第q种信道状态下的信道增益；r＝1,2,…,L；L为RRH的总数量；Q为信道状态的总数量。
在其中一些实施例中，所述求解所述最优化问题，得到最优化的所述矩阵系数和所述度数分布系数包括：
在预设范围内穷举频偏值；
在每次穷举的频偏值下，随机生成满足输出信号功率对ICI自消除编码矩阵的矩阵系数的约束条件的多组矩阵系数；在LT码图的输出节点的边的度数分布的和约束条件、接收端译码启动条件、接收端译码收敛条件下，计算所述多组矩阵系数对应的信道编码码长的最小值和LT码图的输出节点的边的度数分布系数；根据所述信道编码码长的最小值和LT码图的输出节点的边的度数分布系数，采用遗传算法从所述多组矩阵系数中选取矩阵系数；
根据选取出的矩阵系数及相应的LT码图的输出节点的边的度数分布系数，计算最大可容忍频偏值；
将最大可容忍频偏值中最大值对应的矩阵系数及相应的LT码图的输出节点的边的度数分布系数作为所述最优化问题的最优解。
在其中一些实施例中，根据所述信道编码码长的最小值和LT码图的输出节点的边的度数分布系数，采用遗传算法从所述多组矩阵系数中选取矩阵系数包括：
根据所述信道编码码长的最小值，计算与所述信道编码码长的最小值相应的矩阵系数遗传到下一代的概率；
根据矩阵系数遗传到下一代的概率，计算每组矩阵系数的累积概率；
根据所述累积概率，随机抽取若干组矩阵系数。
在其中一些实施例中，所述根据所述累积概率，随机抽取若干组矩阵系数包括：
在[0,1]区间内产生一个均匀分布的伪随机数s，若s<q
1则选择第1组矩阵系数，否则选择第k组，使得q
k-1<s≤q
k成立；重复上述步骤共M次，得到M组矩阵系数；
其中，M为所述多组矩阵系数的组数；q
k为第k组矩阵系数的累积概率。
在其中一些实施例中，在所述根据所述累积概率，随机抽取若干组矩阵系数之后，所述方法还包括：
采用遗传算法，将随机抽取得到的若干组矩阵系数进行两两配对，并将每对矩阵系数的二进制编码都以第一预设概率进行交换，得到若干组第一次更新的矩阵系数；
对得到的若干组第一次更新的矩阵系数以第二预设概率替换其二进制编码中的随机某几 位编码值，得到若干组第二次更新的矩阵系数，并将这若干组第二次更新的矩阵系数作为计算最大可容忍频偏值的矩阵系数。
根据本申请的各种实施例，还提供一种对抗载波间干扰的上行传输方法，应用于在块衰落信道下采用正交频分复用技术的分布式多天线系统，所述方法包括：
所述分布式多天线系统从多个射频拉远头接收上行传输信号，得到多个上行传输信号；其中，所述上行传输信号是将用户信息进行无速率编码后，调制得到上行调制信号，再根据ICI自消除编码矩阵变换得到的；所述ICI自消除编码矩阵的矩阵系数是通过第一方面所述的联合优化方法确定的；
所述分布式多天线系统对所述多个上行传输信号分别进行预处理和量化处理，得到多个量化信号；
所述分布式多天线系统根据所述矩阵系数对所述多个量化信号分别进行软解调后，再利用置信传播算法进行联合译码，得到所述用户信息。
在其中一些实施例中，所述分布式多天线系统根据所述矩阵系数对所述多个量化信号分别进行软解调后，再利用置信传播算法进行联合译码，得到所述用户信息包括：
所述分布式多天线系统根据所述多个量化信号分别计算无速率编码各编码比特的对数似然比，再将相同编码比特的对数似然比合并，得到合并的对数似然比；
所述分布式多天线系统根据所述合并的对数似然比，利用置信传播算法进行联合译码，得到所述用户信息。
根据本申请的各种实施例，还提供一种分布式多天线系统，所述分布式多天线系统应用于块衰落信道下且采用正交频分复用技术，所述分布式多天线系统包括多个射频拉远头、基带处理单元池，其中，
所述射频拉远头用于接收上行传输信号并将所述上行传输信号进行预处理和量化处理后发送给所述基带处理单元池；其中，所述上行传输信号是将用户信息进行无速率编码后，调制得到上行调制信号，再根据ICI自消除编码矩阵变换得到的；所述ICI自消除编码矩阵的矩阵系数是通过联合优化所述矩阵系数和无速率编码的度数分布系数确定的；
所述基带处理单元池用于根据所述矩阵系数对所述多个量化信号分别进行软解调后，再利用置信传播算法进行联合译码，得到所述用户信息。
根据本申请的各种实施例，还提供一种计算机可读存储介质，其上存储有计算机程序指令，当所述计算机程序指令被处理器执行时实现所述的载波间干扰自消除编码矩阵的矩阵系数和无速率编码的度数分布系数的联合优化方法。
上述对抗载波间干扰的上行传输方法、载波间干扰自消除编码矩阵的矩阵系数和无速 率编码的度数分布系数的联合优化方法、分布式多天线系统及计算机可读存储介质具有以下优点：
通过将ICI自消除方法应用于在块衰落信道下采用正交频分复用技术的分布式多天线系统中，并联合优化ICI自消除编码矩阵的矩阵系数和无速率编码的度数分布系数的方式，解决了ICI自消除编码矩阵的矩阵系数和无速率编码的度数分布系数单独优化，导致难以兼顾无线传输的速率和ICI消除效果的问题，在保障无线传输的速率的基础上提升了ICI消除效果。
为了更好地描述和说明这里公开的那些申请的实施例和/或示例，可以参考一幅或多幅附图。用于描述附图的附加细节或示例不应当被认为是对所公开的申请、目前描述的实施例和/或示例以及目前理解的这些申请的最佳模式中的任何一者的范围的限制。
图1是本申请实施例的联合优化方法的流程图。
图2是本申请优选实施例的联合优化方法的流程图。
图3是本申请实施例的分布式多天线系统的结构示意图。
图4是本申请实施例的对抗ICI的上行传输方法的流程图。
图5是本申请实施例的无速率码译码图。
图6是本申请实施例的仿真结果示意图。
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。基于本申请中的实例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实例，都属于本申请保护的范围。
显而易见地，下面描述中的附图仅仅是本申请的一些示例或实施例，对于本领域的普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图将本申请应用于其他类似情景。此外，还可以理解的是，虽然这种开发过程中所作出的努力可能是复杂并且冗长的，然而对于与本申请公开的内容相关的本领域的普通技术人员而言，在本申请揭露的技术内容的基础上进行的一些设计，制造或者生产等变更只是常规的技术手段，不应当理解为本申请公开的内容不充分。
除非另作定义，本申请中使用的技术术语或者科学术语应当为本申请所属技术领域内 具有一般技能的人士所理解的通常意义。本申请专利申请说明书以及权利要求书中使用的“第一”、“第二”以及类似的词语并不表示任何顺序、数量或者重要性，而只是用来区分不同的组成部分。“一”、“一个”、“一种”、“该”等类似词语并不表示数量限制，可表示单数或复数。
“包括”或者“包含”等类似的词语意指出现在“包括”或者“包含”前面的元件或者物件涵盖出现在“包括”或者“包含”后面列举的元件或者物件及其等同元件，并不排除其他元件或者物件。“连接”或者“相连”等类似的词语并非限定于物理的或者机械的连接，而是可以包括电气的连接，不管是直接的还是间接的。
本文中描述的各种技术可用于各种移动通信系统，例如2G、3G、4G、5G移动通信系统以及下一代移动通信系统，又例如全球移动通信系统(Global System for Mobile communications，简称为GSM)，码分多址(Code Division Multiple Access，简称为CDMA)系统，时分多址(Time Division Multiple Access，简称为TDMA)系统，宽带码分多址(Wideband Code Division Multiple Access Wireless，简称为WCDMA)，频分多址(Frequency Division Multiple Addressing，简称为FDMA)系统，正交频分多址(Orthogonal Frequency-Division Multiple Access，简称为OFDMA)系统，单载波FDMA(SC-FDMA)系统，通用分组无线业务(General Packet Radio Service，简称为GPRS)系统，长期演进(Long Term Evolution，简称为LTE)系统，5G新空口(New Radio，简称为NR)系统以及其他此类通信系统。本文中描述的各种技术还可以用于各种其他的无线通信系统，例如，无线局域网(Wireless Local Area Network，简称为WLAN)、WiMAX等系统。
本申请提供的ICI自消除编码矩阵的矩阵系数和无速率编码的度数分布系数的联合优化方法尤其适用于块衰落信道下采用OFDM技术的分布式多天线系统。由于在块衰落信道中，信道增益在一轮传输中保持不变，但在每轮传输后都发生变化的特点，使得即使用户未知信道状态，采用上述联合优化方法的上行传输方案也能够保证无线传输速率。
需要说明的是，在本申请实施例中的用户是指发送用户信息的节点设备，该节点设备可以是智能终端、也可以是中继设备等其他需要发送用户信息的节点设备。
本实施例提供了一种载波间干扰自消除编码矩阵的矩阵系数和无速率编码的度数分布系数的联合优化方法。图1是本申请实施例的联合优化方法的流程图，该流程包括如下步骤：
步骤S101：根据信道状态的统计信息和译码过程的外信息传递分析，确定以最大化系统传输速率为目标，联合优化矩阵系数和度数分布系数的最优化问题；
步骤S102：求解最优化问题，得到最优化的矩阵系数和度数分布系数。
通过上述步骤，以最大化系统传输速率为目标，联合优化ICI自消除编码矩阵的矩阵 系数和无速率编码的度数分布系数，从而解决了ICI自消除编码矩阵的矩阵系数和无速率编码的度数分布系数单独优化，导致在块衰落信道下的分布式多天线OFDM系统中难以兼顾无线传输的速率和ICI消除效果的问题，在保障无线传输的速率的基础上提升了ICI消除效果。
在其中一些实施例中，最优化问题列出为：
最优化问题的约束条件包括：
(1)LT码图的输出节点的边的度数分布的和约束条件C1：
(2)接收端译码启动条件C2：
ω
1>θ
(3)接收端译码收敛条件C3：
(4)输出信号功率对ICI自消除编码矩阵的矩阵系数的约束条件C4：
|c
1|
2+|c
2|
2≤1,2|c
3|
2≤1
其中，ε
max为用户到RRH的链路最大可容忍频偏；
为最大平均码长；c
1,c
2,c
3为ICI自消除编码矩阵的矩阵系数；{ω
d}表示无速率码的LT码图的输出节点的边的度数分布系数；ω
j为LT码图中度数为j的输出节点的边的度数分布系数；d
c为LT码图的输出节点的边的最大度数；T为ICI自消除编码矩阵；θ为大于零的预设值；x
u为外信息；γ
1,γ
2,γ
3,γ
4分别为LDPC码图中度数为1、2、3或4的变量节点的比例；
为与信道的即时增益无关的常数；
为正确译码的外信息最小门限；H
r,q表示第r个RRH的链路在第q种信道状态下的信道增益；r＝1,2,…,L；L为RRH的总数量；Q为信道状态的总数量。
其中，约束条件C4保证了将上行调制信号根据ICI自消除编码矩阵变换后，用户的输出信号功率不会增大。
图2是本申请优选实施例的联合优化方法的流程图，在其中一些实施例中，步骤S102包括：
步骤S102-1：在预设范围内穷举频偏值；
步骤S102-2：在每次穷举的频偏值下，随机生成满足输出信号功率对ICI自消除编码矩阵的矩阵系数的约束条件的多组矩阵系数；在LT码图的输出节点的边的度数分布的和约束条 件、接收端译码启动条件、接收端译码收敛条件下，计算多组矩阵系数对应的信道编码码长的最小值和LT码图的输出节点的边的度数分布系数；根据信道编码码长的最小值和LT码图的输出节点的边的度数分布系数，采用遗传算法从多组矩阵系数中选取矩阵系数；
步骤S102-3：根据选取出的矩阵系数及相应的LT码图的输出节点的边的度数分布系数，计算最大可容忍频偏值；
步骤S102-4：将最大可容忍频偏值中最大值对应的矩阵系数及相应的LT码图的输出节点的边的度数分布系数作为最优化问题的最优解。
继续参考图2，在其中一些实施例中，在步骤S102-2中，根据信道编码码长的最小值和LT码图的输出节点的边的度数分布系数，采用遗传算法从多组矩阵系数中选取矩阵系数包括：
步骤S102-2-1：根据信道编码码长的最小值，计算与信道编码码长的最小值相应的矩阵系数遗传到下一代的概率；
步骤S102-2-2：根据矩阵系数遗传到下一代的概率，计算每组矩阵系数的累积概率；
步骤S102-2-3：根据累积概率，随机抽取若干组矩阵系数。
在其中一些实施例中，步骤S102-2-3包括：在[0,1]区间内产生一个均匀分布的伪随机数s，若s<q
1则选择第1组矩阵系数，否则选择第k组，使得q
k-1<s≤q
k成立；重复上述步骤共M次，得到M组矩阵系数；其中，M为多组矩阵系数的组数；q
k为第k组矩阵系数的累积概率。
继续参考图2，在其中一些实施例中，在步骤S102-2-3之后，方法还包括：
步骤S102-2-4：采用遗传算法，将随机抽取得到的若干组矩阵系数进行两两配对，并将每对矩阵系数的二进制编码都以第一预设概率进行交换，得到若干组第一次更新的矩阵系数；
步骤S102-2-5：对得到的若干组第一次更新的矩阵系数以第二预设概率替换其二进制编码中的随机某几位编码值，得到若干组第二次更新的矩阵系数，并将这若干组第二次更新的矩阵系数作为计算最大可容忍频偏值的矩阵系数。
本实施例还提供了一种分布式多天线系统。该分布式多天线系统应用于块衰落信道下且采用正交频分复用调制技术。图3是本申请实施例的分布式多天线系统的结构示意图，该系统包括射频拉远头(RRH)和基带处理单元(BBU)池。
利用上述系统进行上行传输之前，首先根据本申请实施例提供的联合优化方法，利用衰落信道统计信息优化出无速率编码的度数分布和ICI自消除编码矩阵的矩阵系数。
图4是本申请实施例的对抗ICI的上行传输方法的流程图，在上述的分布式多天线系统中，对抗ICI的上行传输方法包括如下步骤：
步骤S401：通过联合优化矩阵系数和无速率编码的度数分布系数确定ICI自消除编码矩阵的矩阵系数和无速率编码的度数分布系数；
步骤S402：用户将用户信息按照上述度数分布系数进行无速率编码后，码字经调制后得到上行调制信号，再根据与上述的矩阵系数对应的ICI自消除编码矩阵进行变换，得到上行传输信号，并将上行传输信号发送到覆盖该用户的分布式多天线系统的各个射频拉远头；
步骤S403：分布式多天线系统的各个射频拉远头接收上行传输信号，并通过射频拉远头对这些上行传输信号分别进行预处理变为基带信号，然后将信号量化发送给分布式多天线系统的基带处理单元池；
步骤S404：分布式多天线系统的基带处理单元池根据ICI自消除编码矩阵的矩阵系数对接收到的这些量化信号分别进行软解调后，再利用置信传播算法进行联合译码，得到用户信息。
在上述步骤中的ICI自消除方法通过在用户端将无速率编码的码字调制到一组邻近的子载波上，各个子载波有各自的矩阵系数，通过联合优化无速率编码的度数分布系数和ICI自消除编码矩阵的矩阵系数使得在保证无线传输速率的基础上ICI达到最小值；在分布式多天线系统的接收端，再使用这些矩阵系数对这些子载波进行线性组合，使得接收到的上行传输信号中残余的ICI进一步减少。相比于相关技术中单独优化无速率编码的度数分布系数无法保证ICI消除效果，而单独优化ICI自消除编码矩阵的矩阵系数无法保证无线传输速率而言，上述步骤能够兼顾无线传输的速率和ICI消除效果。
在其中一些实施例中，步骤S404包括如下步骤：分布式多天线系统的基带处理单元池根据多个量化信号分别计算无速率编码各编码比特的对数似然比，再将相同编码比特的对数似然比合并，得到合并的对数似然比；分布式多天线系统的基带处理单元池根据合并的对数似然比，利用置信传播算法进行联合译码，得到用户信息。
下面通过优选实施例对本申请的上行传输方法进行描述和说明。
本优选实施例提供的上行传输过程包括如下步骤：
步骤1：基于ICI自消除编码矩阵的分布式多天线系统采用OFDM调制技术，单个用户通过L根分布式多天线与BBU进行上行通信，OFDM子载波数为N。用户首先采用无速率编码将长度为K的原始信息m编为长度为N的码字c。这里以码率为R
P的LDPC码作为无速率码的预编码，然后再进行输出度数分布为Ω(x)的卢比变换码(Luby Transform codes，简称为LT)编码。
步骤2：将无速率码c调制成
其中x(k),k＝0,1,…,W-1，再乘以ICI自消除编码矩阵T得到
其中
T的阶数为N×W，编码效率为
T表示如下：
矩阵中c
1,c
2,c
3为矩阵权重系数。
步骤3：信号通过天线发送到覆盖该用户的各个RRH
r,r＝1,2,…,L，RRH的预处理器对收到的信号预处理得到基带信号：
其中y
r(7i+j)和n
r(7i+j)代表在RRH
r处第(7i+j)个子载波上的接收信号和高斯噪声，
j＝0,1,…,6.x(4a+b)代表第(4a+b)个传输信号，
b＝0,1,2,3。式中
表示在RRH
r处第m和第k个子载波m＝1,2,…,N，k＝1,2,…,N之间的载波间干扰，ε
r表示用户到RRH
r处的链路归一化频率偏移。H
r(k),k＝1,2,…,N表示在RRH
r处第k个子载波上的信道增益系数，在块衰落信道中，它在一轮传输中保持不变，但在每轮发生变化。
RRH对上述信号进行量化，量化电平数满足2M＝2
b，其中b为量化比特，量化间隔为Δ，量化门限为
量化后的信号为
量化规则如下：
其中，
是量化值。
步骤4：各RRH
r将得到的量化信号通过高速链路发送给BBU；应用差分接收方式，将RRH
r的上传信号变换为得到解调信号x′
r：
用户无速率码第4i个码比特c
4i等概率地取0和1，第r个RRH上传到BBU的量化信号x′
r(4i)＝q
k。基带处理单元池的软解调器输出第4i比特对应的对数似然比(LLR)可以表示为：
其中Pr(·)表示当输出比特为0或1时，接收到的量化信号为q
k的概率。将各RRH上传信号对应的LLR合并后第4i比特的LLR为：
同理可得到第(4i+1)，(4i+2)和(4i+3)比特对应的LLR。
步骤5：基带处理单元池联合译码器进行迭代译码。图5是本申请优选实施例的无速率码译码图，基带处理单元池联合译码器进行迭代译码包括两步：第一步，在整个译码图执行迭代译码，直到输入节点的LLR平均值超过某个超过门限x
p；第二步，在LDPC译码图上迭代译码以消除残留误差。
其中，第一步的具体程序如下：第0轮迭代译码，译码图中输入节点i的初始LLR为
输出节点的初始LLR为L(i)第l轮迭代，输入节点i传向校验节点c的消息更新为：
式中o为与该输入节点相连的输出节点。校验节点c传回输入节点i的消息更新为：
式中i′为译码图中除去输入节点i外与校验节点c相连的输入节点。输入节点i传向输出节点o的消息更新为：
式中o′表示除o以外的输出节点。输出节点o传回输入节点i的消息更新为：
上式中i′表示除i以外的输入节点，
是第l轮迭代中输出节点o向输入节点i发送的消息；
是第l轮迭代中输入节点i向输出节点o发送的消息；Z
0是输出节点根据对应码字比特量化值计算得到的LLR，由步骤2-4得到；当前轮输入节点i的LLR为：
当该轮输入节点的LLR均值超过门限x
p，再单独在LDPC码图上进行迭代译码。
第二步迭代译码如下：LDPC子图第0轮迭代译码，变量节点v传向校验节点c的消息更新为：
式中m
v为前面最后一轮迭代时输入节点的LLR；第l轮迭代，变量节点v传向校验节点c的消息更新为：
式中c′表示除c以外的校验节点，C
v表示与变量节点v相邻的校验节点集合，
代表在上一轮由校验节点c′传向该变量节点的消息；从校验节点c传向变量节点v的消息更新为：
式中v′表示除v以外的与校验节点c相连的变量节点。
判决比特s的对数似然比信息
若LLR(s)>0则信息比特s判为0，否则判为1，根据判决输出结果，若译码不正确则继续迭代，若译码正确或达到最大迭代次数t就结束译码。
通过上述步骤1至步骤5完成上行传输过程。
在上述上行传输方法中，无速率编码的度数分布系数以及ICI自消除编码矩阵的矩阵系数的联合优化方法包括如下步骤：
步骤1：进行译码过程的外信息传递分析。
首先，定义基带处理单元池译码过程外信息更新函数如下。LT输入节点将LLR消息传递给LDPC码图校验节点，其携带的外信息为：
式中
是第l-1次迭代LT输出节点传给输入节点的平均外信息,ζ
i为LT译码图中度数为i的输入节点比例，d
v为LT码图输入节点的最大度数，J为满足对称高斯分布的消息携带的外信息函数；LDPC校验节点传回LT输入节点的外信息为：
式中γ
i为LDPC码图中度数为i的变量节点比例，
为LDPC码图中与度数j校验节点相连的边的比例，d
v为LDPC码图变量节点最大度数，d′
c为LDPC码图检验节点最大度数；LT输入节点将消息传给输出节点的外信息为：
式中
为与度数i输入节点相连的边的比例，d
v为输入节点的最大度数；最后，第一编码比特对应的输出节点传回LT输入节点的外信息分别为：
同理，第二、三和四组编码比特对应的输出节点传回LT输入节点的外信息分别为：
式中f
0(γ
i)＝J(4γ
i),i＝1,2,3,4表示信噪比为γ
i的第i组输出比特携带的平均信息量；从这四组输出比特到输入节点传递的消息所携带的平均外信息为：
将式(18)，(19)，(20)，(21)和(22)代入(23)得到每轮
更新为：
式中
为LT码图的输入节点平均度数，{ω
d}为LT输出节点的边的度数分布的系数。
步骤2：根据信道状态的统计信息，确定以最大化系统传输速率为目标，联合优化矩阵系数和度数分布系数的最优化问题。
然后，将L条链路的信道增益定义成一个向量
即{H}
r,r＝1,2,…,L，每条链路上频偏为ε
r,r＝1,2,…,L，该向量所有可能取值构成了连续的信道增益向量空间，将其离散为Q个状态。其中{H}
r＝(H
r,1,H
r,2,…,H
r,Q)表示Q种不同的信道状态。码长
q＝1,2,…,Q，Pr(H
r,q,ε
r)表示每种状态取到的概率。信道增益为{H}
r且频偏为ε
r时的LT码图的输入节点平均度数
其中
是与信道的即时增益无关的常数，
为理论最高可达速率，
表示信噪比为γ的二进制输入加性高斯白噪声信道容量。
基于上述定义，本申请实施例的联合优化问题的最优化问题列出如下：
其约束条件分别为：
C1:
C2:ω
1>θ
C3:
对于所有的H
r,q,r＝1,2,…,L,q＝1,2,…,Q
C4:|c
1|
2+|c
2|
2≤1,2|c
3|
2≤1
式中ε
max为用户到RRH处的链路最大可容忍频偏值，其定义为：对于任意的频偏|β|<ε
max，系统平均码长都小于
为最大平均码长限制；θ为大于零的一个小量，
为正确译码的外信息最小门限。
步骤3：求解最优化问题，得到最优化的矩阵系数和度数分布系数。
在步骤3中，包括如下步骤：
步骤31：设置最大迭代次数，并在任意固定频偏ε
r下，随机生成M组矩阵系数c
1,c
2,c
3并对其进行二进制编码，同时初始化
步骤32：对于每一组矩阵系数c
1,c
2,c
3，在C1、C2和C3的条件限制下，首先在
固定下通过线性规划方法找到相应的最优{ω
d}，在此基础上穷举
找到相应码长(即
)最小值以及相应的度数分布{ω
d}；
步骤33：
(1)根据步骤32中每组矩阵系数计算出的码长值
计算出每组系数遗传到下一代的概率
(2)得到每组的累积概率
(3)在[0,1]区间内产生一个均匀分布的伪随机数s，若s<q
1则选择第1组矩阵系数，否则选择第k组，使得q
k-1<s≤q
k成立；
(4)重复(3)共M次；
步骤34：对于任意固定频偏ε
r，采用遗传算法，将以上选择出的矩阵系数进行两两配对，它们的每一位二进制编码都以Pr1的概率(0到1之间，例如0.97)进行交换，从而形成两组新 的系数；接下来对于新产生的每组系数，以Pr2的概率(0到1之间，例如0.1)替换原来编码串中的随机某几位编码值，从而完成了又一次的更新；
步骤35：重复步骤32至步骤34，优化得到相应的具有最小码长值的矩阵系数c
1,c
2,c
3和度数分布{ω
d}；
步骤36：在一定范围内穷举ε
r，对于任一ε
r，由步骤35获得的矩阵系数c
1,c
2,c
3和度数分布{ω
d}计算对应的最大可容忍频偏
选择该值最大的ε
r所对应的c
1,c
2,c
3和度数分布{ω
d}作为问题的解。
采用计算机仿真对本申请上述实施例的效果进行验证，将优化得到的矩阵系数和度数分布与二进制擦除信道(Bianry Erasure Channel，简称为BEC)度数分布、随机生成的矩阵系数和BEC度数分布、传统OFDM系统和BEC度数分布以及理论可达的速率进行比较。图6是本申请优选实施例的仿真结果示意图，相比于相关技术中标准OFDM系统和BEC度数分布，或者随机生成的矩阵系数和BEC度数分布方案而言，基于本申请提供的联合优化方法的传输速率更接近理论可达速率，且提升了ICI消除效果。
在本实施例中还提供了一种计算机可读存储介质，其上存储有计算机程序指令，当计算机程序指令被处理器执行时实现上述的联合优化方法。
在本申请所提供的几个实施例中，应该理解到，所揭露的系统，装置或方法，可以通过其它的方式实现。例如，以上所描述的装置实施例仅仅是示意性的，例如，所述模块或单元的划分，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式，例如多个单元或组件可以结合或者可以集成到另一个系统，或一些特征可以忽略，或不执行。另一点，所显示或讨论的相互之间的相合或直接相合或通信连接可以是通过一些接口、装置或单元的间接相合或通信连接，可以是电性，机械或其它的形式。
所述作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部单元末实现本实施例方案的目的。
另外，在本申请各个实施例中的各功能单元可以集成在一个处理单元中，也可以是各个单元单独物理存在，也可以两个或两个以上单元集成在一个单元中。上述集成的单元既可以采用硬件的形式实现，也可以采用软件功能单元的形式实现。
所述集成的单元如果以软件功能单元的形式实现并作为独立的产品销售或使用时，可以存储在一个计算机可读取存储介质中。基于这样的理解，本申请的技术方案本质上或者说对现有技术做出贡献的部分或者该技术方案的全部或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中，包括若干指令用以使得一台计算机设备(可以是 个人计算机，服务器，或者网络设备等)或处理器(processor)执行本申请各个实施例所述方法的全部或部分步骤。上述的理器可以包括中央处理器(CPU)，或者特定集成电路(Application Specific Integrated Circuit，简称为ASIC)，或者可以被配置成实施本申请实施例的一个或多个集成电路。上述的存储介质可以用于数据或指令的大容量存储器。举例来说而非限制，存储器可包括硬盘驱动器(Hard Disk Drive，简称为HDD)、软盘驱动器、闪存、光盘、磁光盘、磁带或通用串行总线(Universal Serial Bus，简称为USB)驱动器或者两个或更多个以上这些的组合。在合适的情况下，存储器可包括可移除或不可移除(或固定)的介质。在合适的情况下，存储器可在数据处理装置的内部或外部。在特定实施例中，存储器是非易失性固态存储器。在特定实施例中，存储器包括只读存储器(ROM)。在合适的情况下，该ROM可以是掩模编程的ROM、可编程ROM(PROM)、可擦除PROM(EPROM)、电可擦除PROM(EEPROM)、电可改写ROM(EAROM)或闪存或者两个或更多个以上这些的组合。
以上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申请专利范围的限制。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)
- 一种载波间干扰自消除编码矩阵的矩阵系数和无速率编码的度数分布系数的联合优化方法，应用于在块衰落信道下采用正交频分复用技术的分布式多天线系统，其特征在于，所述方法包括：根据信道状态的统计信息和译码过程的外信息传递分析，确定以最大化系统传输速率为目标，联合优化所述矩阵系数和所述度数分布系数的最优化问题；求解所述最优化问题，得到最优化的所述矩阵系数和所述度数分布系数。
- 根据权利要求1所述的方法，其特征在于，所述最优化问题列出为：
所述最优化问题的约束条件包括：(1)LT码图的输出节点的边的度数分布的和约束条件C1：
(2)接收端译码启动条件C2：ω 1>θ(3)接收端译码收敛条件C3：对于所有的H r,q,r＝1,2,…,L,q＝1,2,…,Q
(4)输出信号功率对ICI自消除编码矩阵的矩阵系数的约束条件C4：|c 1| 2+|c 2| 2≤1,2|c 3| 2≤1其中，ε max为用户到RRH的链路最大可容忍频偏；为最大平均码长；c 1,c 2,c 3为ICI自消除编码矩阵的矩阵系数；{ω d}表示无速率码的LT码图的输出节点的边的度数分布系数；ω j为LT码图中度数为j的输出节点的边的度数分布系数；d c为LT码图的输出节点的边的最大度数；T为ICI自消除编码矩阵；θ为大于零的预设值；x u为外信息；γ 1,γ 2,γ 3,γ 4分别为LDPC码图中度数为1、2、3或4的变量节点的比例；
为与信道的即时增益无关的常数；
为正确译码的外信息最小门限；H r,q表示第r个RRH的链路在第q种信道状态下的信道增益；r＝1,2,…,L；L为RRH的总数量；Q为信道状态的总数量。
- 根据权利要求1所述的方法，其特征在于，所述求解所述最优化问题，得到最优化的所述矩阵系数和所述度数分布系数包括：在预设范围内穷举频偏值；在每次穷举的频偏值下，随机生成满足输出信号功率对ICI自消除编码矩阵的矩阵系数的约束条件的多组矩阵系数；在LT码图的输出节点的边的度数分布的和约束条件、接收端译码启动条件、接收端译码收敛条件下，计算所述多组矩阵系数对应的信道编码码长的最小值和LT码图的输出节点的边的度数分布系数；根据所述信道编码码长的最小值和LT码图的输出节点的边的度数分布系数，采用遗传算法从所述多组矩阵系数中选取矩阵系数；根据选取出的矩阵系数及相应的LT码图的输出节点的边的度数分布系数，计算最大可容忍频偏值；将最大可容忍频偏值中最大值对应的矩阵系数及相应的LT码图的输出节点的边的度数分布系数作为所述最优化问题的最优解。
- 根据权利要求3所述的方法，其特征在于，所述根据所述信道编码码长的最小值和LT码图的输出节点的边的度数分布系数，采用遗传算法从所述多组矩阵系数中选取矩阵系数包括：根据所述信道编码码长的最小值，计算与所述信道编码码长的最小值相应的矩阵系数遗传到下一代的概率；根据矩阵系数遗传到下一代的概率，计算每组矩阵系数的累积概率；根据所述累积概率，随机抽取若干组矩阵系数。
- 根据权利要求4所述的方法，其特征在于，所述根据所述累积概率，随机抽取若干组矩阵系数包括：在[0,1]区间内产生一个均匀分布的伪随机数s，若s<q 1，则选择第1组矩阵系数，否则选择第k组，使得q k-1<s≤q k成立；重复上述步骤共M次，得到M组矩阵系数；其中，M为所述多组矩阵系数的组数；q k为第k组矩阵系数的累积概率。
- 根据权利要求4所述的方法，其特征在于，在所述根据所述累积概率，随机抽取若干组矩阵系数之后，所述方法还包括：采用遗传算法，将随机抽取得到的若干组矩阵系数进行两两配对，并将每对矩阵系数的二进制编码都以第一预设概率进行交换，得到若干组第一次更新的矩阵系数；对得到的若干组第一次更新的矩阵系数以第二预设概率替换其二进制编码中的随机某几位编码值，得到若干组第二次更新的矩阵系数，并将这若干组第二次更新的矩阵系数作为计算最大可容忍频偏值的矩阵系数。
- 一种对抗载波间干扰的上行传输方法，应用于在块衰落信道下采用正交频分复用技术的分布式多天线系统，其特征在于，所述方法包括：所述分布式多天线系统从多个射频拉远头接收上行传输信号，得到多个上行传输信号； 其中，所述上行传输信号是将用户信息进行无速率编码后，调制得到上行调制信号，再根据ICI自消除编码矩阵变换得到的；所述ICI自消除编码矩阵的矩阵系数是通过权利要求1至6中任一项所述的载波间干扰自消除编码矩阵的矩阵系数和无速率编码的度数分布系数的联合优化方法确定的；所述分布式多天线系统对所述多个上行传输信号分别进行预处理和量化处理，得到多个量化信号；所述分布式多天线系统根据所述矩阵系数对所述多个量化信号分别进行软解调后，再利用置信传播算法进行联合译码，得到所述用户信息。
- 根据权利要求7所述的方法，其特征在于，所述分布式多天线系统根据所述矩阵系数对所述多个量化信号分别进行软解调后，再利用置信传播算法进行联合译码，得到所述用户信息包括：所述分布式多天线系统根据所述多个量化信号分别计算无速率编码各编码比特的对数似然比，再将相同编码比特的对数似然比合并，得到合并的对数似然比；所述分布式多天线系统根据所述合并的对数似然比，利用置信传播算法进行联合译码，得到所述用户信息。
- 一种分布式多天线系统，所述分布式多天线系统应用于块衰落信道下且采用正交频分复用技术，其特征在于，所述分布式多天线系统包括多个射频拉远头、基带处理单元池，其中，所述射频拉远头用于接收上行传输信号并将所述上行传输信号进行预处理和量化处理后发送给所述基带处理单元池；其中，所述上行传输信号是将用户信息进行无速率编码后，调制得到上行调制信号，再根据ICI自消除编码矩阵变换得到的；所述ICI自消除编码矩阵的矩阵系数是通过联合优化所述矩阵系数和无速率编码的度数分布系数确定的；所述基带处理单元池用于根据所述矩阵系数对所述多个量化信号分别进行软解调后，再利用置信传播算法进行联合译码，得到所述用户信息。
- 一种计算机可读存储介质，其上存储有计算机程序指令，其特征在于，当所述计算机程序指令被处理器执行时实现如权利要求1至6中任一项所述的载波间干扰自消除编码矩阵的矩阵系数和无速率编码的度数分布系数的联合优化方法。
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