Joint Precoding for RIS-Assisted Wideband THz Cell-Free Massive MIMO Systems

TL;DR

This paper proposes a joint precoding framework with time delay adjustments for RIS-assisted wideband THz cell-free massive MIMO systems, effectively mitigating beam split effects and enhancing network capacity.

Contribution

It introduces a novel joint precoding approach with time delay layers to address beam split effects in wideband RIS-assisted THz MIMO networks, improving performance.

Findings

Significant improvement in achievable rate compared to conventional networks.

Effective mitigation of beam split effect through time delay adjustments.

Validated performance gains via numerical simulations.

Abstract

Terahertz (THz) cell-free massive multiple-input-multiple-output (mMIMO) networks have been envisioned as a prospective technology for achieving higher system capacity, improved performance, and ultra-high reliability in 6G networks. However, due to severe attenuation and limited scattering in THz transmission, as well as high power consumption for increased number of access points (APs), further improvement of network capacity becomes challenging. Reconfigurable intelligent surface (RIS) has been introduced as a low-cost solution to reduce AP deployment and assist in data transmission. However, due to the ultra-wide bandwidth and frequency-dependent characteristics of RISs, beam split effect has become an unavoidable obstacle. To compensate the severe performance degradation caused by beam split effect, we introduce additional time delay (TD) layers at both access points (APs) and RISs. Accordingly, we propose a joint precoding framework at APs and RISs to fully unleash the potential of the considered network. Specifically, we first formulate the joint precoding as a non-convex optimization problem. Then, given the location of unchanged RISs, we adjust the time delays (TDs) of APs to align the generated beams towards RISs. After that, with knowledge of the optimal TDs of APs, we decouple the optimization problem into three subproblems of optimizing the baseband beamformers, RISs and TDs of RISs, respectively. Exploiting multidimensional complex quadratic transform, we transform the subproblems into convex forms and solve them under alternate optimizing framework. Numerical results verify that the proposed method can effectively mitigate beam split effect and significantly improve the achievable rate compared with conventional cell-free mMIMO networks.