Large System Analysis of Cooperative Multi-cell Downlink Transmission via Regularized Channel Inversion with Imperfect CSIT

TL;DR

This paper provides a large system analysis of multi-cell downlink systems with cooperative base stations using regularized zero-forcing precoding, accounting for imperfect channel information and spatial correlations, leading to optimal parameter and feedback strategies.

Contribution

It derives a deterministic equivalent of the ergodic sum-rate for large systems, enabling efficient optimization of regularization and feedback bit allocation.

Findings

Deterministic expression for ergodic sum-rate in large systems

Optimal regularization parameter for RZF precoding derived

Proposed feedback bit allocation scheme reduces search complexity

Abstract

In this paper, we analyze the ergodic sum-rate of a multi-cell downlink system with base station (BS) cooperation using regularized zero-forcing (RZF) precoding. Our model assumes that the channels between BSs and users have independent spatial correlations and imperfect channel state information at the transmitter (CSIT) is available. Our derivations are based on large dimensional random matrix theory (RMT) under the assumption that the numbers of antennas at the BS and users approach to infinity with some fixed ratios. In particular, a deterministic equivalent expression of the ergodic sum-rate is obtained and is instrumental in getting insight about the joint operations of BSs, which leads to an efficient method to find the asymptotic-optimal regularization parameter for the RZF. In another application, we use the deterministic channel rate to study the optimal feedback bit allocation among the BSs for maximizing the ergodic sum-rate, subject to a total number of feedback bits constraint. By inspecting the properties of the allocation, we further propose a scheme to greatly reduce the search space for optimization. Simulation results demonstrate that the ergodic sum-rates achievable by a subspace search provides comparable results to those by an exhaustive search under various typical settings.