论文标题

大型MIMO系统的块分布式压缩传感基于双重选择性渠道估计和试点设计

Block Distributed Compressive Sensing Based Doubly Selective Channel Estimation and Pilot Design for Large-Scale MIMO Systems

论文作者

Gong, Bo, Gui, Lin, Qin, Qibo, Ren, Xiang, Chen, Wen

论文摘要

大规模多输入多输出(MIMO)系统中的双重选择性(DS)通道估计是一个具有挑战性的问题,因为要估算的大量通道系数,这需要无法承受的和刺激性的飞行员开销。在本文中,首先,我们对所有BEM订单和所有发射型天线对之间基础扩展模型(BEM)系数的共同稀疏性进行了分析。然后提出了一种新型的飞行员模式,该模式插入后卫飞行员在叠加的飞行员模式下处理载体间干扰(ICI)。此外,通过利用不同BEM订单和不同天线之间的BEM系数的共同稀疏性,我们提出了一个基于大型MIMO系统的基于块的分布式压缩感应(BDC)的DS通道估计器。它的结构性稀疏性导致在保证估计准确性的前提下减少飞行员开销。此外,提出了一种试验设计算法,称为块离散随机优化(BDSO)。它通过降低测量矩阵的不同块之间的相干性来优化飞行员位置。此外,将线性平滑方法扩展到大规模的MIMO系统,以提高估计的准确性。与现有方案相比,仿真结果验证了我们提出的估计器和试点设计算法的性能增长。

The doubly selective (DS) channel estimation in the large-scale multiple-input multiple-output (MIMO) systems is a challenging problem due to the large number of the channel coefficients to be estimated, which requires unaffordable and prohibitive pilot overhead. In this paper, firstly we conduct the analysis about the common sparsity of the basis expansion model (BEM) coefficients among all the BEM orders and all the transmit-receive antenna pairs. Then a novel pilot pattern is proposed, which inserts the guard pilots to deal with the inter carrier interference (ICI) under the superimposed pilot pattern. Moreover, by exploiting the common sparsity of the BEM coefficients among different BEM orders and different antennas, we propose a block distributed compressive sensing (BDCS) based DS channel estimator for the large-scale MIMO systems. Its structured sparsity leads to the reduction of the pilot overhead under the premise of guaranteeing the accuracy of the estimation. Furthermore, taking consideration of the block structure, a pilot design algorithm referred to as block discrete stochastic optimization (BDSO) is proposed. It optimizes the pilot positions by reducing the coherence among different blocks of the measurement matrix. Besides, a linear smoothing method is extended to large-scale MIMO systems to improve the accuracy of the estimation. Simulation results verify the performance gains of our proposed estimator and the pilot design algorithm compared with the existing schemes.

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