多天线信号联合接收处理关键技术研究

发布时间：2018-06-14 19:54

本文选题：最大似然估计 + 符号检测　；参考：《解放军信息工程大学》2014年博士论文

【摘要】：随着无线通信的迅猛发展,以可靠信息传输为前提,低发射功率,高数据速率和高频谱效率等要求越来越迫切。多变的传输环境、复杂的通信网络以及不断降低的信号功率,使得接收技术面临着愈发严峻的挑战。在传统单路信号接收技术中,多个同参数的估计与符号检测通常基于逐层处理的结构,然而为了进一步降低同步门限提高接收性能,.多个同步参数与符号信息的联合处理方法与实现结构是接收技术的一个重要研究方向。同时,多天线信号联合接收是一种能够有效提升接收性能的多数据流联合处理结构,’在深空通信、低轨卫星通信以及分集接收等系统中得到广泛的研究与应用。本文的主要研究工作围绕通信信号接收中多参数及多信号间的联合处理技术展开。针对同步参数与符号信息的联合处理问题,多天线信号接收中的联合同步、联合信道参数估计以及联合符号检测问题进行了深入的分析研究。论文的主要内容以及主要创新点概括为如下几方面：1、针对小样本、低信噪比条件下符号定时与符号信息的联合处理问题,基于非完整数据集下的最大似然估计模型,提出了一种无须定时恢复的最大似然符号检测算法。算法直接利用匹配滤波器输出序列求解,在EM算法框架下通过迭代计算实现最大似然符号检测。利用理论结果,‘推导得到了基于过采样信号离散化求和的估计式与低采样率下基于多项式函数积分的估计式,并在此基础上给出一种新的迭代实现结构,与传统基于定时恢复的符号检测算法相比避免了对最佳采样点进行内插恢复。仿真分析表明,算法输出误码率能够逼近理想联合最大似然解,优于传统非数据辅助类算法,与判决反馈类联合处理算法相比在短数据条件下误码率更低,且收敛更快。2、针对同步参数未知条件下的符号信息提取问题,在最大似然准则下提出一种无须同步参数估计的迭代符号检测算法。与传统接收处理中逐级同步处理的结构不同,该算法将符号定时、载波频偏与载波相位等同步参数作为缺失信息在EM算法框架下与符号信息联合处理,得到一种新的最大似然符号检测算法。并在理论结果基础上推导得到闭式的迭代估计式,与传统基于EM的联合最大似然同步参数估计算法相比求解计算更加简单,且在短数据条件下误码率更低,迭代收敛更快并对信号参数不敏感。3、在多天线联合接收背景下,提出了一种基于最大似然的多数据流联合同步与联合符号检测算法。传统结构通过信号合成实现多信号联合处理,需要先进行信号参数校准或先完成信号同步。多天线联合符号检测算法通过利用多数据流中承载的相同符号信息,实现了信号间参数差异估计补偿与信号同步的联合处理,以及最大似然准则下的联合符号检测。与传统符号合成结构相比,避免了低信噪比带来的同步门限问题；与波形合成结构相比,无需首先进行计算量较大的波形校准与相干合成,而是直接基于多路未进行同步或校准的接收信号实现最大似然准则下的联合符号检测。仿真分析表明,多数据流联合同步与联合符号检测算法在低信噪比下较传统信号合成技术处理损失大大降低,尤其在较大规模组阵接收应用中具有更优的误码率性能。4、针对非均匀组阵接收条件下的联合最大似然符号检测问题,建立了多数据流信噪比参数与符号信息的联合最大似然估计模型。在SAGE (Space-Alternating Generalized EM)算法框架下给出了多数据流多参数的联合迭代处理算法,实现了最大似然准则下多天线未同步信号的信噪比参数与符号信息的联合迭代求解。针对非均匀组阵中未知的信号功率与噪声功率谱密度,通过多数据流多参数的联合处理,避免了传统信噪比与符号的联合估计算法需要先完成各路信号同步的缺点；而与基于信号波形的信噪比估计算法相比,由于进一步利用了各接收信号的符号信息,多参数联合求解算法具有更高的参数估计精度。仿真分析表明,多数据流多参数联合最大似然算法无论是信噪比估计精度或是输出误码率,均优于采用传统信噪比估计算法的信号合成技术。5、针对多径衰落信道下的符号检测问题,基于定时同步、信道参数与符号信息的联合处理,给出了一种多天线信号联合最大似然信道估计与符号检测算法。从多径信道参数未知时的匹配滤波和定时同步问题出发,将多径信道复增益与符号速率抽样下等效信道作为未知参数与符号信息联合求解,建立了多径时延信息缺失条件下的多参数联合最大似然估计模型。在EM算法框架下,通过多径时延参数的期望化处理,利用过采样信号得到一种信道参数估计与符号检测的迭代求解结构,实现了最大似然准则下多数据流定时同步、信道估计与符号检测的联合处理。并通过仿真,分析了算法误码率以及多路联合求解带来的性能提升。
[Abstract]:With the rapid development of wireless communication, the requirement of low transmission power, high data rate and high frequency spectrum efficiency is becoming more and more urgent. The changing transmission environment, complex communication network and the continuous reduction of signal power make the receiving technology face more and more severe challenges. In the traditional single channel signal receiving technology At the same time, multiple parameter estimation and symbol detection are usually based on layer by layer processing, but in order to further reduce the synchronization threshold to improve the reception performance, the joint processing and implementation structure of multiple synchronization parameters and symbol information is an important research direction of the reception technology. The multi data flow joint processing structure which effectively improves the reception performance is widely studied and applied in the systems of deep space communication, low orbit satellite communication and diversity reception. The main research work of this paper is around the joint processing technology of multiple parameters and multiple signals in the reception of communication signals. Joint synchronization, joint synchronization in multi antenna signal reception, joint channel parameter estimation and joint symbol detection are deeply analyzed. The main contents and main innovations of this paper are summarized as follows: 1, joint processing of symbol timing and symbol information for small sample and low SNR bars Based on the maximum likelihood estimation model under the nonholonomic data set, a maximum likelihood symbol detection algorithm without timing recovery is proposed. The algorithm uses the matching filter output sequence to solve the maximum likelihood method directly. The maximum likelihood symbol detection is realized by iterative calculation under the EM algorithm framework. The estimation formula of the sum of signal discretization and the estimation formula based on the polynomial function integration under the low sampling rate, and on this basis, a new iterative implementation structure is given. Compared with the traditional symbol detection algorithm based on the timing recovery, the optimal sampling point is avoided by interpolation. The imitation true analysis shows that the error rate of the algorithm can be approximated. The ideal joint maximum likelihood solution is better than the traditional non data auxiliary class algorithm. Compared with the decision feedback class joint processing algorithm, the bit error rate is lower in the short data condition and the convergence is faster.2. In view of the problem of symbol information extraction under the unknown synchronization parameters, an iterative symbol without synchronization parameter estimation is proposed under the maximum likelihood criterion. The algorithm is different from the structure of the step by step synchronization in the traditional reception processing. The algorithm combines the synchronization parameters such as symbol timing, carrier frequency offset and carrier phase as missing information in the framework of EM algorithm with symbol information, and obtains a new maximum likelihood symbol detection algorithm. The iterative estimation method is more simple than the traditional EM based joint maximum likelihood synchronization parameter estimation algorithm. In the short data condition, the bit error rate is lower, the iterative convergence is faster and the signal parameters are not sensitive to.3. In the multi antenna joint reception background, a joint synchronization of multi data flow based on maximum likelihood is proposed. Joint symbol detection algorithm. The traditional structure realizes joint processing of multiple signals through signal synthesis. It needs to calibrate the signal parameters or synchronize the signal first. The multi antenna joint symbol detection algorithm realizes the combination of the difference estimation compensation and the signal synchronization by using the same symbol information in the multi data stream. The joint symbol detection under the maximum likelihood criterion. Compared with the traditional symbol synthetic structure, it avoids the synchronization threshold caused by low signal to noise ratio. Compared with the waveform synthesis structure, it is not necessary to first carry out the waveform calibration and coherent synthesis of the larger amount of computation, but directly based on the multichannel received signals that have not been synchronized or calibrated. The simulation analysis shows that the combined synchronization and joint symbol detection algorithm of multiple data streams is much lower than the traditional signal synthesis technology in low signal to noise ratio, especially in large scale array receiving applications with better bit error rate performance.4. A joint maximum likelihood estimation model of multiple data stream signal-to-noise ratio and symbol information is established for the joint maximum likelihood symbol detection problem. A joint iterative processing algorithm for multi data flow and multiple parameters is given under the framework of SAGE (Space-Alternating Generalized EM) algorithm, which realizes the signal of multiple antenna unsynchronized signals under the maximum likelihood criterion. The joint iterative solution of the noise ratio parameter and the symbol information. Aiming at the unknown signal power and the noise power spectrum density in the inhomogeneous array, the joint processing of multi data flow and multiple parameters avoids the shortcomings of the joint estimation algorithm of the traditional signal to noise ratio and symbol, and the signal to noise ratio based on the signal waveform. Compared with the estimation algorithm, the multi parameter joint solution algorithm has a higher parameter estimation precision because of the further use of the symbol information of each received signal. The simulation analysis shows that the multiple data flow and multi parameter joint maximum likelihood algorithm is superior to the traditional signal to noise ratio estimation algorithm, whether it is the signal to noise ratio estimation accuracy or the output error rate. .5, for symbol detection in multipath fading channels, based on timing synchronization and joint processing of channel parameters and symbol information, a joint maximum likelihood channel estimation and symbol detection algorithm for multi antenna signals is presented. Based on the matching filtering and timing synchronization of multipath channel parameters, multipath channels are used. The equivalent channel of complex gain and symbol rate sampling is combined to solve the unknown parameter and symbol information, and a multi parameter joint maximum likelihood estimation model is established under the absence of multipath delay information. Under the framework of the EM algorithm, a channel parameter estimation and symbol is obtained by using the over sampling signal to estimate the multipath delay parameters. The iterative solution structure of the number detection has realized the joint processing of multiple data flow timing synchronization and channel estimation and symbol detection under maximum likelihood criterion. Through simulation, the performance improvement of the algorithm caused by the error rate and multiple joint solution of the algorithm is analyzed.
【学位授予单位】：解放军信息工程大学
【学位级别】：博士
【学位授予年份】：2014
【分类号】：TN911.25;TN820

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