FTN系统中基于矩阵分解的预编码算法
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摘要
为进一步提高超奈奎斯特(FTN)码元速率传输系统中的信号检测性能、减轻符号间干扰并降低复杂度,在FTN系统中引入预编码算法,主要包括:奇异值分解(SVD),几何均值分解(GMD),统一信道分解(UCD)。将三种不同预编码方法、未预编码直接硬判决及部分判决反馈均衡(PDFE)仿真并比较得到:UCD预编码在任何信噪比条件下均优于GMD预编码,SVD预编码和PDFE性能在高信噪比时比GMD预编码性能要差,SVD预编码性能和直接硬判决相比略差。
In order to further improve the detection performance of Faster-than-Nyquist signaling,and reduce the ISI as well as its computational complexity,the precoding algorithms were introduced in FTN signaling,including Singular Value Decomposition(SVD),Geometric Mean Decomposition(GMD)and Uniform Channel Decomposition(UCD).The performance of these three precoding algorithms,PDFE and directly Hard Decision(HD)without FTN signaling was compared and the conclusion was reached that UCD precoding can perform better than GMD precoding at any SNR value,that SVD precoding and PDFE can perform worse than GMD precoding at higher SNR,and that only the performance of SVD precoding is slightly worse than directly HD.
In order to further improve the detection performance of Faster-than-Nyquist signaling,and reduce the ISI as well as its computational complexity,the precoding algorithms were introduced in FTN signaling,including Singular Value Decomposition(SVD),Geometric Mean Decomposition(GMD)and Uniform Channel Decomposition(UCD).The performance of these three precoding algorithms,PDFE and directly Hard Decision(HD)without FTN signaling was compared and the conclusion was reached that UCD precoding can perform better than GMD precoding at any SNR value,that SVD precoding and PDFE can perform worse than GMD precoding at higher SNR,and that only the performance of SVD precoding is slightly worse than directly HD.
引文
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[2]LE C,SCHELLMANN M,FUHRWERK M,et al.On the practical benefits of faster-than-Nyquist signaling[C]∥2014International Conference on Advanced Technologies for Communications.Hanoi,Vietnam:IEEE Press,2014:208-213.
[3]FORNEY G D.Maximum-likelihood sequence estimation of digital sequences in the presence of inter-symbol interference[J].IEEE Transactions on Information Theory,1972,18(3):363-378.
[4]HAYES J F.The viterbi algorithm applied to digital data transmission[J].IEEE Communications Magazine,2002,40(5):26-32.
[5]ANDERSON J B,PRLJA A,RUSEK F.New reduced state space BCJR algorithms for ISI channel[C]∥International Symposium on Information Theory.Seoul,Korea:IEEE Press,2009:889-893.
[6]PRLJA A,ANDERSON J B.Reduced-complexity receivers for strongly narrowband inter-symbol interference introduced by faster-than-Nyquist signaling[J].IEEE Transactions on Communication,2012,60(9):2591-2601.
[7]BAEK M S,HUR N H,LIM H.Novel interference cancellation technique based on matrix computation for FTN communication system[C]∥IEEE Military Communications Conference.Daejeon,Korea:IEEE Press,2014:830-834.
[8]JOHN B A,RUSEK F,OWALL V.Faster-than-Nyquist signaling[J].Proceedings of the IEEE,2013,101(8):23-35.
[9]RINGH E.Low complexity algorithm for faster-than-Nyquist signaling:using coding to avoid an NP-hard problem[D].Stockholm,Sweden:Royal Institute of Technology,2013.
[10]JIANG Y,WILLIAN W H,LI J.The geometric mean decomposition[J].Linear Algebra and Its Applications,2005,396:373-384.
[11]JIANG Y,LI J,WILLIAN W H.Uniform channel decomposition for MIMO communication[J].IEEE Transactions on Signal Process,2005,53(11):4283-4294.
[12]JIANG Y,LI J,WILLIAN W H.MIMO transceiver design using geometric mean decomposition[C]∥IEEE Information Workshop.San Antonio:IEEE Press,2004:193-197.