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arXiv 2002.01629cs.ITeess.SPmath.IT

智能反射面辅助毫米波大规模 MIMO 系统的宽带信道估计

Broadband Channel Estimation for Intelligent Reflecting Surface Aided mmWave Massive MIMO Systems

Ziwei Wan, Zhen Gao, Mohamed-Slim Alouini

AI总结:

针对 IRS 辅助毫米波大规模 MIMO 的高维宽带信道估计难题,提出基于压缩感知的下行导频框架,结合分布式 OMP、公共稀疏性与冗余字典降低导频开销并提升估计性能。

摘要:

本文研究智能反射面(IRS)辅助的毫米波(mmWave)大规模 MIMO 系统的宽带信道估计(CE)。由于基站(BS)端的有源大规模 MIMO 和无源 IRS 均具有很大的维度,此类系统的信道估计是一项具有挑战性的任务。为解决该问题,本文针对 IRS 辅助的毫米波大规模 MIMO 系统提出了一种基于压缩感知(CS)的信道估计方案,利用毫米波频段大规模阵列的角度域信道稀疏性,以较低的导频开销改善信道估计。具体而言,本文首先提出一种下行导频传输框架。在利用视距主导的 BS 到 IRS 信道已知这一先验知识设计导频信号的基础上,可依据 CS 理论联合估计 BS 到用户以及 IRS 到用户的高维信道。此外,为高效估计宽带信道,采用了分布式正交匹配追踪算法,利用不同子载波上信道共享的公共稀疏性。另外,还设计了用于抑制功率泄漏的冗余字典,以增强信道估计性能。仿真结果验证了所提方案的有效性。

英文摘要:

This paper investigates the broadband channel estimation (CE) for intelligent reflecting surface (IRS)-aided millimeter-wave (mmWave) massive MIMO systems. The CE for such systems is a challenging task due to the large dimension of both the active massive MIMO at the base station (BS) and passive IRS. To address this problem, this paper proposes a compressive sensing (CS)-based CE solution for IRS-aided mmWave massive MIMO systems, whereby the angular channel sparsity of large-scale array at mmWave is exploited for improved CE with reduced pilot overhead. Specifically, we first propose a downlink pilot transmission framework. By designing the pilot signals based on the prior knowledge that the line-of-sight dominated BS-to-IRS channel is known, the high-dimensional channels for BS-to-user and IRS-to-user can be jointly estimated based on CS theory. Moreover, to efficiently estimate broadband channels, a distributed orthogonal matching pursuit algorithm is exploited, where the common sparsity shared by the channels at different subcarriers is utilized. Additionally, the redundant dictionary to combat the power leakage is also designed for the enhanced CE performance. Simulation results demonstrate the effectiveness of the proposed scheme.

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