本文選題：最大似然估計(jì) + 符號(hào)檢測�。� 參考：《解放軍信息工程大學(xué)》2014年博士論文

【摘要】：隨著無線通信的迅猛發(fā)展,以可靠信息傳輸為前提,低發(fā)射功率,高數(shù)據(jù)速率和高頻譜效率等要求越來越迫切。多變的傳輸環(huán)境、復(fù)雜的通信網(wǎng)絡(luò)以及不斷降低的信號(hào)功率,使得接收技術(shù)面臨著愈發(fā)嚴(yán)峻的挑戰(zhàn)。在傳統(tǒng)單路信號(hào)接收技術(shù)中,多個(gè)同參數(shù)的估計(jì)與符號(hào)檢測通�；谥饘犹幚淼慕Y(jié)構(gòu),然而為了進(jìn)一步降低同步門限提高接收性能,.多個(gè)同步參數(shù)與符號(hào)信息的聯(lián)合處理方法與實(shí)現(xiàn)結(jié)構(gòu)是接收技術(shù)的一個(gè)重要研究方向。同時(shí),多天線信號(hào)聯(lián)合接收是一種能夠有效提升接收性能的多數(shù)據(jù)流聯(lián)合處理結(jié)構(gòu),’在深空通信、低軌衛(wèi)星通信以及分集接收等系統(tǒng)中得到廣泛的研究與應(yīng)用。本文的主要研究工作圍繞通信信號(hào)接收中多參數(shù)及多信號(hào)間的聯(lián)合處理技術(shù)展開。針對(duì)同步參數(shù)與符號(hào)信息的聯(lián)合處理問題,多天線信號(hào)接收中的聯(lián)合同步、聯(lián)合信道參數(shù)估計(jì)以及聯(lián)合符號(hào)檢測問題進(jìn)行了深入的分析研究。論文的主要內(nèi)容以及主要?jiǎng)?chuàng)新點(diǎn)概括為如下幾方面：1、針對(duì)小樣本、低信噪比條件下符號(hào)定時(shí)與符號(hào)信息的聯(lián)合處理問題,基于非完整數(shù)據(jù)集下的最大似然估計(jì)模型,提出了一種無須定時(shí)恢復(fù)的最大似然符號(hào)檢測算法。算法直接利用匹配濾波器輸出序列求解,在EM算法框架下通過迭代計(jì)算實(shí)現(xiàn)最大似然符號(hào)檢測。利用理論結(jié)果,‘推導(dǎo)得到了基于過采樣信號(hào)離散化求和的估計(jì)式與低采樣率下基于多項(xiàng)式函數(shù)積分的估計(jì)式,并在此基礎(chǔ)上給出一種新的迭代實(shí)現(xiàn)結(jié)構(gòu),與傳統(tǒng)基于定時(shí)恢復(fù)的符號(hào)檢測算法相比避免了對(duì)最佳采樣點(diǎn)進(jìn)行內(nèi)插恢復(fù)。仿真分析表明,算法輸出誤碼率能夠逼近理想聯(lián)合最大似然解,優(yōu)于傳統(tǒng)非數(shù)據(jù)輔助類算法,與判決反饋類聯(lián)合處理算法相比在短數(shù)據(jù)條件下誤碼率更低,且收斂更快。2、針對(duì)同步參數(shù)未知條件下的符號(hào)信息提取問題,在最大似然準(zhǔn)則下提出一種無須同步參數(shù)估計(jì)的迭代符號(hào)檢測算法。與傳統(tǒng)接收處理中逐級(jí)同步處理的結(jié)構(gòu)不同,該算法將符號(hào)定時(shí)、載波頻偏與載波相位等同步參數(shù)作為缺失信息在EM算法框架下與符號(hào)信息聯(lián)合處理,得到一種新的最大似然符號(hào)檢測算法。并在理論結(jié)果基礎(chǔ)上推導(dǎo)得到閉式的迭代估計(jì)式,與傳統(tǒng)基于EM的聯(lián)合最大似然同步參數(shù)估計(jì)算法相比求解計(jì)算更加簡單,且在短數(shù)據(jù)條件下誤碼率更低,迭代收斂更快并對(duì)信號(hào)參數(shù)不敏感。3、在多天線聯(lián)合接收背景下,提出了一種基于最大似然的多數(shù)據(jù)流聯(lián)合同步與聯(lián)合符號(hào)檢測算法。傳統(tǒng)結(jié)構(gòu)通過信號(hào)合成實(shí)現(xiàn)多信號(hào)聯(lián)合處理,需要先進(jìn)行信號(hào)參數(shù)校準(zhǔn)或先完成信號(hào)同步。多天線聯(lián)合符號(hào)檢測算法通過利用多數(shù)據(jù)流中承載的相同符號(hào)信息,實(shí)現(xiàn)了信號(hào)間參數(shù)差異估計(jì)補(bǔ)償與信號(hào)同步的聯(lián)合處理,以及最大似然準(zhǔn)則下的聯(lián)合符號(hào)檢測。與傳統(tǒng)符號(hào)合成結(jié)構(gòu)相比,避免了低信噪比帶來的同步門限問題；與波形合成結(jié)構(gòu)相比,無需首先進(jìn)行計(jì)算量較大的波形校準(zhǔn)與相干合成,而是直接基于多路未進(jìn)行同步或校準(zhǔn)的接收信號(hào)實(shí)現(xiàn)最大似然準(zhǔn)則下的聯(lián)合符號(hào)檢測。仿真分析表明,多數(shù)據(jù)流聯(lián)合同步與聯(lián)合符號(hào)檢測算法在低信噪比下較傳統(tǒng)信號(hào)合成技術(shù)處理損失大大降低,尤其在較大規(guī)模組陣接收應(yīng)用中具有更優(yōu)的誤碼率性能。4、針對(duì)非均勻組陣接收條件下的聯(lián)合最大似然符號(hào)檢測問題,建立了多數(shù)據(jù)流信噪比參數(shù)與符號(hào)信息的聯(lián)合最大似然估計(jì)模型。在SAGE (Space-Alternating Generalized EM)算法框架下給出了多數(shù)據(jù)流多參數(shù)的聯(lián)合迭代處理算法,實(shí)現(xiàn)了最大似然準(zhǔn)則下多天線未同步信號(hào)的信噪比參數(shù)與符號(hào)信息的聯(lián)合迭代求解。針對(duì)非均勻組陣中未知的信號(hào)功率與噪聲功率譜密度,通過多數(shù)據(jù)流多參數(shù)的聯(lián)合處理,避免了傳統(tǒng)信噪比與符號(hào)的聯(lián)合估計(jì)算法需要先完成各路信號(hào)同步的缺點(diǎn)；而與基于信號(hào)波形的信噪比估計(jì)算法相比,由于進(jìn)一步利用了各接收信號(hào)的符號(hào)信息,多參數(shù)聯(lián)合求解算法具有更高的參數(shù)估計(jì)精度。仿真分析表明,多數(shù)據(jù)流多參數(shù)聯(lián)合最大似然算法無論是信噪比估計(jì)精度或是輸出誤碼率,均優(yōu)于采用傳統(tǒng)信噪比估計(jì)算法的信號(hào)合成技術(shù)。5、針對(duì)多徑衰落信道下的符號(hào)檢測問題,基于定時(shí)同步、信道參數(shù)與符號(hào)信息的聯(lián)合處理,給出了一種多天線信號(hào)聯(lián)合最大似然信道估計(jì)與符號(hào)檢測算法。從多徑信道參數(shù)未知時(shí)的匹配濾波和定時(shí)同步問題出發(fā),將多徑信道復(fù)增益與符號(hào)速率抽樣下等效信道作為未知參數(shù)與符號(hào)信息聯(lián)合求解,建立了多徑時(shí)延信息缺失條件下的多參數(shù)聯(lián)合最大似然估計(jì)模型。在EM算法框架下,通過多徑時(shí)延參數(shù)的期望化處理,利用過采樣信號(hào)得到一種信道參數(shù)估計(jì)與符號(hào)檢測的迭代求解結(jié)構(gòu),實(shí)現(xiàn)了最大似然準(zhǔn)則下多數(shù)據(jù)流定時(shí)同步、信道估計(jì)與符號(hào)檢測的聯(lián)合處理。并通過仿真,分析了算法誤碼率以及多路聯(lián)合求解帶來的性能提升。
[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.
【學(xué)位授予單位】：解放軍信息工程大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2014
【分類號(hào)】：TN911.25;TN820

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