基于混合消息传递和部分高斯近似的联合信道估计MIMO-OFDM接收机
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摘要
本文提出了一种基于混合消息传递和部分高斯近似(Partial Gaussian Approximation,PGA)的多用户干扰消除方法,并应用到联合信道估计MIMO-OFDM接收机中。由于多用户干扰模型中存在的"乘积-求和"结构,使得选择标准消息传递规则,如置信传播(Belief Propagation,BP),期望传播(Expectation Propagation,EP),平均场规则(Mean Field,MF),或者联合方法时只能在性能或复杂度方面有所取舍。现有根据标准消息传递规则得到的最优性能接收机复杂度高,而近似程度大的低复杂度接收机性能损失严重。本文根据多用户干扰模型的自身特点,对标准消息传递规则进行了修改,提出了一种基于混合消息传递规则和部分高斯近似的多用户干扰消除方法。依据信道估计过程中不同用户的信道权重,采用不同的消息传递规则,可以实现复杂度和性能的均衡调整。仿真结果表明,本文提出的多用户干扰消除方法,在性能接近已知最优接收机的情况下,能够大幅降低复杂度。
Based on the hybrid message passing rule and partial Gaussian approximation(PGA) method,a novel multi-user interference elimination algorithm has been proposed in this paper,and is applied to the joint channel estimation and detection for MIMO-OFDM system. The"multiplication-summation"structure lies in the multi-user model makes the adoption of standard message passing rules difficult,since the performance and complexity cannot achieve simultaneously. The standard message passing rules include belief propagation(BP),expectation propagation(EP),mean field(MF),and the joint approaches as BP-MF or BP-EP. Based on the structure of multi-user interference,a hybrid message passing rule and partial Gaussian approximation based algorithm has been proposed in this paper,which can be seen as an amendment of the standard rule. By the evaluation of channel weight,the proposed method employ different message passing strategies to different users,thus compromise the complexity and performance. Simulation results shown that,the proposed MIMO-OFDM receiver approaching the best one in literature while has much lower complexity.
Based on the hybrid message passing rule and partial Gaussian approximation(PGA) method,a novel multi-user interference elimination algorithm has been proposed in this paper,and is applied to the joint channel estimation and detection for MIMO-OFDM system. The"multiplication-summation"structure lies in the multi-user model makes the adoption of standard message passing rules difficult,since the performance and complexity cannot achieve simultaneously. The standard message passing rules include belief propagation(BP),expectation propagation(EP),mean field(MF),and the joint approaches as BP-MF or BP-EP. Based on the structure of multi-user interference,a hybrid message passing rule and partial Gaussian approximation based algorithm has been proposed in this paper,which can be seen as an amendment of the standard rule. By the evaluation of channel weight,the proposed method employ different message passing strategies to different users,thus compromise the complexity and performance. Simulation results shown that,the proposed MIMO-OFDM receiver approaching the best one in literature while has much lower complexity.
引文
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[2]Worthen A P,Stark W E.Unified design of iterative receivers using factor graphs[J].IEEE Transactions on Information Theory,2001,47(2):843-849.
[3]Winn J,Bishop C M.Variational message passing[J].Journal of Machine Learning Research,2005,6(2):661-694.
[4]Yuan Z,Zhang C,Wang Z,et al.An Auxiliary variableaided hybrid message passing approach to joint channel estimation and decoding for MIMO-OFDM[J].IEEE Signal Processing Letters,2017,24(1):12-16.
[5]Minka T P.Expectation propagation for approximate Bayesian inference[C]∥Seventeenth Conference on Uncertainty in Artificial Intelligence,Washington,Morgan Kaufmann Publishers Inc,2001:362-369.
[6]Riegler E,Kirkelund G E,Manchon C N,et al.Merging belief propagation and the mean field approximation:A free energy approach[C]∥International Symposium on Turbo Codes and Iterative Information Processing.IEEE,Brest,2010:256-260.
[7]Wu S,Kuang L,Ni Z,et al.Expectation propagation approach to joint channel estimation and decoding for OFDM systems[C]∥IEEE International Conference on Acoustics,Speech and Signal Processing.IEEE,Florence,2014:1941-1945.
[8]王忠勇,郭秋歌,王法松,等.基于分层模型的SC-FDE系统低复杂度稀疏信道估计[J].信号处理,2015,31(9):1106-1111.Wang Zhongyong,Guo Qiuge,Wang Fasong,et al.The hierarchical model based on low complexity sparse channel estimation for SC-FDE system[J].Journal of Signal Processing,2015,31(9):1106-1111.(in Chinese)
[9]Zhang C,Yuan Z,Wang Z,et al.Low complexity sparse Bayesian learning using combined BP and MF with a stretched factor graph[J].Signal Processing,2016,131:344-349.
[10]何云,赵天,梁彦.大规模MIMO-OFDM系统结构化压缩感知信道估计中导频优化方法研究[J].信号处理,2017,33(1):87-94.He yun,Zhao Tian,Liang yan.Optimizing pilots for structured compressive sensing based channel estimation in massive MIMO-OFDM system[J].Journal of Signal Processing,2017,33(1):87-94.(in Chinese)
[11]Kirkelund G E,Manchon C N,Christensen L P B,et al.Variational message-passing for joint channel estimation and decoding in MIMO-OFDM[C]∥Global Telecom.Conference.IEEE,Miami,2010:1-6.
[12]Jakubisin D J,Buehrer R M,Silva C R C M D.Probabilistic receiver architecture combining BP,MF,and EP for multi-signal detection[OL].arxiv.org/abs/1604.0483.
[13]Wu S,Kuang L,Ni Z,et al.Message-passing receiver for joint channel estimation and decoding in 3D massive MIMO-OFDM systems[J].IEEE Transactions on Wireless Communications,2016,15(12):8122-8138.
[14]Zhang C,Yuan Z,Wang Z,et al.A new combination of message passing techniques for receiver design in MIMOOFDM systems[OL].arxiv.org/abs/1701.06304.
[15]Guo Q,Huang D D,Nordholm S,et al.Soft-in soft-out detection using partial Gaussian approximation[J].Access IEEE,2012,2(1):427-436.