A Block Parallel l_0-Norm Penalized Shrinkage and Widely Linear Affine Projection Algorithm for Adaptive Filter  

作　　者：Youwen Zhang Shuang Xiao Lu Liu Dajun Sun 

机构地区：[1]Acoustic Science and Technology Laboratory, Harbin Engineering University, Harbin 150001, China [2]College of Underwater Acoustic Engineering, Harbin Engineering University, Harbin 150001, China

出　　处：《China Communications》2017年第1期86-97,共12页中国通信（英文版）

基　　金：supported by the National Natural Science Foundation of China (Grant No. 61471138, 50909029 and 61531012);Program of International S\&T Cooperation (Grant No. 2013DFR20050);the Defense Industrial Technology Development Program (Grant No. B2420132004);the Acoustic Science and Technology Laboratory (2014)

摘　　要：To improve the identification capability of AP algorithm in time-varying sparse system, we propose a block parallel l_0-SWL-DCD-AP algorithm in this paper. In the proposed algorithm, we first introduce the l_0-norm constraint to promote its application for sparse system. Second, we use the shrinkage denoising method to improve its track ability. Third, we adopt the widely linear processing to take advantage of the non-circular properties of communication signals. Last, to reduce the high computational complexity and make it easy to implemented, we utilize the dichotomous coordinate descent(DCD) iterations and the parallel processing to deal with the tapweight update in the proposed algorithm. To verify the convergence condition of the proposed algorithm, we also analyze its steadystate behavior. Several simulation are done and results show that the proposed algorithm can achieve a faster convergence speed and a lower steady-state misalignment than similar APA-type algorithm. When apply the proposed algorithm in the decision feedback equalizer(DFE), the bite error rate(BER) decreases obviously.To improve the identification capability of AP algorithm in time-varying sparse system, we propose a block parallel l_0-SWL-DCD-AP algorithm in this paper. In the proposed algorithm, we first introduce the l_0-norm constraint to promote its application for sparse system. Second, we use the shrinkage denoising method to improve its track ability. Third, we adopt the widely linear processing to take advantage of the non-circular properties of communication signals. Last, to reduce the high computational complexity and make it easy to implemented, we utilize the dichotomous coordinate descent（DCD） iterations and the parallel processing to deal with the tapweight update in the proposed algorithm. To verify the convergence condition of the proposed algorithm, we also analyze its steadystate behavior. Several simulation are done and results show that the proposed algorithm can achieve a faster convergence speed and a lower steady-state misalignment than similar APA-type algorithm. When apply the proposed algorithm in the decision feedback equalizer（DFE）, the bite error rate（BER） decreases obviously.

关 键 词：signal processing adaptive algorithm LMS l0-norm shrinkage linear DCD 

分 类 号：TN713[电子电信—电路与系统]