MIMO系統(tǒng)下空時編碼及檢測算法的研究
發(fā)布時間：2019-03-18 20:15
【摘要】：在社會對通信需求與日劇增的同時,無線通信技術的應用逐漸深入到社會生活的方方面面。為了能夠在復雜的通信環(huán)境中實現(xiàn)大容量和高速率的數(shù)據(jù)傳輸,使用MIMO技術可以提升系統(tǒng)信道容量。MIMO技術作為當下成熟應用于第四代移動通信的核心技術之一,本文對MIMO技術下的空時編碼和檢測算法兩大關鍵部分進行了主要研究�？諘r編碼技術是在MIMO技術基礎上,結(jié)合時間與空間的相關性對傳送信息比特進行空時編碼,比SISO系統(tǒng)容量提升幾十倍。由于傳送會受到無線通信信道時變特性和多徑衰落影響,因此在接收端提出有效可靠的檢測算法來恢復出原始信號。本文首先從整體上對MIMO系統(tǒng)模型進行簡述,介紹基本的分集復用、無線信道以及均衡估計,并從SISO系統(tǒng)信道容量推導出MIMO系統(tǒng)容量公式,利用MATLAB仿真證明MIMO技術對容量有巨大的提升。接著對兩類空時編碼展開了研究,接受端必須已知CSI的分層空時編碼、空時網(wǎng)格編碼和空時分組編碼,無需CSI的差分空時編碼,綜合考慮每種編碼方式的性能和復雜度,確定適合應用于何種場景下。最后如何準確恢復衰落后的原始信號,對檢測算法研究并提出改進方案,最佳ML算法對于大型MIMO系統(tǒng)來說檢測復雜度過高,線性ZF、MMSE算法檢測性能卻達不到要求,都存在很明顯的弊端;在此前提下提出眾多非線性算法,如干擾消除算法和QR分解算法結(jié)構(gòu)簡單性能也能夠滿足要求,并對串行干擾消除算法做出相應改進;為了追求最佳的檢測效果跟較低復雜度,研究了球形檢測算法,性能與ML算法相當,搜索空間卻小很多,使用MATLAB軟件仿真驗證效果。
[Abstract]:At the same time, the application of wireless communication technology gradually goes deep into all aspects of social life. In order to realize large-capacity and high-speed data transmission in complex communication environment, the channel capacity of the system can be improved by using MIMO technology. As one of the core technologies used in the fourth generation of mobile communication, MIMO technology is one of the core technologies. In this paper, two key parts of space-time coding and detection algorithm in MIMO technology are studied. Space-time coding (STC) is a space-time coding technique for transmitting information bits, which is based on MIMO technology and combined with the correlation between time and space, which is several times higher than the capacity of SISO system. Because the transmission will be affected by the time-varying characteristics and multipath fading of the wireless communication channel, an effective and reliable detection algorithm is proposed at the receiver to recover the original signal. In this paper, the MIMO system model is introduced, and the basic diversity multiplexing, wireless channel and equalization estimation are introduced, and the MIMO system capacity formula is derived from the channel capacity of SISO system. The simulation results of MATLAB show that MIMO technology can greatly improve the capacity. Secondly, two classes of space-time coding are studied. The receiver must know the layered space-time coding of CSI, space-time trellis coding and space-time block coding, and do not need the differential space-time coding of CSI, considering the performance and complexity of each coding method. Determine which scenarios are suitable for application. Finally, how to accurately restore the original signal after fading, the detection algorithm is studied and improved, the optimal ML algorithm for large-scale MIMO system detection complexity is too high, but the linear ZF,MMSE algorithm detection performance is not up to the requirements. There are obvious disadvantages; On this premise, many non-linear algorithms, such as interference cancellation algorithm and QR decomposition algorithm, can also meet the requirements, and make corresponding improvements to the serial interference cancellation algorithm. In order to pursue the best detection effect and lower complexity, the spherical detection algorithm is studied. The performance of spherical detection algorithm is similar to that of ML algorithm, but the search space is much smaller. MATLAB software is used to simulate and verify the effect.
【學位授予單位】：北方工業(yè)大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TN919.3
本文編號：2443202
[Abstract]:At the same time, the application of wireless communication technology gradually goes deep into all aspects of social life. In order to realize large-capacity and high-speed data transmission in complex communication environment, the channel capacity of the system can be improved by using MIMO technology. As one of the core technologies used in the fourth generation of mobile communication, MIMO technology is one of the core technologies. In this paper, two key parts of space-time coding and detection algorithm in MIMO technology are studied. Space-time coding (STC) is a space-time coding technique for transmitting information bits, which is based on MIMO technology and combined with the correlation between time and space, which is several times higher than the capacity of SISO system. Because the transmission will be affected by the time-varying characteristics and multipath fading of the wireless communication channel, an effective and reliable detection algorithm is proposed at the receiver to recover the original signal. In this paper, the MIMO system model is introduced, and the basic diversity multiplexing, wireless channel and equalization estimation are introduced, and the MIMO system capacity formula is derived from the channel capacity of SISO system. The simulation results of MATLAB show that MIMO technology can greatly improve the capacity. Secondly, two classes of space-time coding are studied. The receiver must know the layered space-time coding of CSI, space-time trellis coding and space-time block coding, and do not need the differential space-time coding of CSI, considering the performance and complexity of each coding method. Determine which scenarios are suitable for application. Finally, how to accurately restore the original signal after fading, the detection algorithm is studied and improved, the optimal ML algorithm for large-scale MIMO system detection complexity is too high, but the linear ZF,MMSE algorithm detection performance is not up to the requirements. There are obvious disadvantages; On this premise, many non-linear algorithms, such as interference cancellation algorithm and QR decomposition algorithm, can also meet the requirements, and make corresponding improvements to the serial interference cancellation algorithm. In order to pursue the best detection effect and lower complexity, the spherical detection algorithm is studied. The performance of spherical detection algorithm is similar to that of ML algorithm, but the search space is much smaller. MATLAB software is used to simulate and verify the effect.
【學位授予單位】：北方工業(yè)大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TN919.3
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，本文編號：2443202
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