Srivastav Prateek Saurabh, Chen Lan, Wahla Arfan Haider
Institute of Microelectronics of Chinese Academy of Sciences, Beijing 100029, China.
School of Electronics, Electrical and Communication, University of Chinese Academy of Sciences, Beijing 100049, China.
Entropy (Basel). 2020 Oct 3;22(10):1121. doi: 10.3390/e22101121.
Millimeter wave (mmWave) relying upon the multiple output multiple input (MIMO) is a new potential candidate for fulfilling the huge emerging bandwidth requirements. Due to the short wavelength and the complicated hardware architecture of mmWave MIMO systems, the conventional estimation strategies based on the individual exploitation of sparsity or low rank properties are no longer efficient and hence more modern and advance estimation strategies are required to recapture the targeted channel matrix. Therefore, in this paper, we proposed a novel channel estimation strategy based on the symmetrical version of alternating direction methods of multipliers (S-ADMM), which exploits the sparsity and low rank property of channel altogether in a symmetrical manner. In S-ADMM, at each iteration, the Lagrange multipliers are updated twice which results symmetrical handling of all of the available variables in optimization problem. To validate the proposed algorithm, numerous computer simulations have been carried out which straightforwardly depicts that the S-ADMM performed well in terms of convergence as compared to other benchmark algorithms and also able to provide global optimal solutions for the strictly convex mmWave joint channel estimation optimization problem.
基于多输入多输出(MIMO)的毫米波(mmWave)是满足巨大新兴带宽需求的新潜在候选技术。由于毫米波MIMO系统的波长较短且硬件架构复杂,基于单独利用稀疏性或低秩特性的传统估计策略不再有效,因此需要更现代和先进的估计策略来恢复目标信道矩阵。因此,在本文中,我们提出了一种基于对称形式乘子交替方向法(S-ADMM)的新型信道估计策略,该策略以对称方式同时利用信道的稀疏性和低秩特性。在S-ADMM中,每次迭代时拉格朗日乘子会更新两次,这导致对优化问题中所有可用变量进行对称处理。为了验证所提出的算法,进行了大量计算机仿真,这些仿真直接表明,与其他基准算法相比,S-ADMM在收敛方面表现良好,并且还能够为严格凸的毫米波联合信道估计优化问题提供全局最优解。