数据采集与处理Issue(3)：552-563,12.DOI:10.16337/j.1004-9037.2015.03.010
基于块稀疏快速重构的MISO活跃用户集与信道联合估计
Active User Identification and Channel Estimation in MISO Based on Efficient Block-sparse Signal Recovery Algorithm
摘要
Abstract
To solve the user selection and channel estimation problem in multi‐user MISO system ,a new data transmission frame structure combined with the decentralized user self‐selecting strategy in TDD mode is designed .Then ,the base station receiving uplink random pilot sequence signatured with the user identity is built as a block sparse linear model based on the natural signal sparsity from users′low active degree and the channel impulse response sparsity in delay‐spread domain .In addtion ,to resolve such an objective optimization problem ,an efficient block‐sparse signal recovery algorithm is proposed based on l2/l1 reconstruction model .In the novel algorithm ,the objective function is transformed through variable splitting and four variables are alternately updated in the framework of alternating direction method (ADM ) until the prespecified convergence criterion is satisfied .During the alternate updating procedure , Aiming at unobtainable closed form solution of the signal variable item , the block coordinate descent (BCD) method is utilized to acquire an iterative solution .Simulation results demonstrate that the pro‐posed method can achieve higher computational efficiency and the better estimation accuracy compared with two state‐of‐art fast algorithms ,such as block orthogonal matching pursuit (Block OMP) and block compressive sampling matching pursuit (Block CoSaMP) .关键词
块稀疏信号重构/分布式自选择/随机身份标识序列/交替方向法/块坐标下降法Key words
block sparse signal recovery/decentralized self select/random identity signature sequences/alternating direction method/block coordinate descent method分类
信息技术与安全科学引用本文复制引用
康凯,钟子发,朱然刚,王理..基于块稀疏快速重构的MISO活跃用户集与信道联合估计[J].数据采集与处理,2015,(3):552-563,12.基金项目
国家自然科学基金（61272333）资助项目；安徽省自然科学基金（1208085MF94）资助项目。 （）
