Two-Tier Precoding for FDD Multi-cell Massive MIMO Time-Varying Interference Networks (Full Version)

TL;DR

This paper introduces a low-complexity, iterative two-tier precoding method for multi-cell massive MIMO networks that effectively tracks channel variations, reducing computational load while maintaining high performance.

Contribution

It proposes a novel online iterative algorithm for outer precoder tracking in time-varying channels, formulated on the Grassmann manifold, with proven convergence and compensation techniques.

Findings

Significant complexity reduction compared to existing methods

Effective outer precoder tracking in time-varying channels

Achieves good performance with theoretical guarantees

Abstract

Massive MIMO is a promising technology in future wireless communication networks. However, it raises a lot of implementation challenges, for example, the huge pilot symbols and feedback overhead, requirement of real-time global CSI, large number of RF chains needed and high computational complexity. We consider a two-tier precoding strategy for multi-cell massive MIMO interference networks, with an outer precoder for inter-cell/inter-cluster interference cancellation, and an inner precoder for intra-cell multiplexing. In particular, to combat with the computational complexity issue of the outer precoding, we propose a low complexity online iterative algorithm to track the outer precoder under time-varying channels. We follow an optimization technique and formulate the problem on the Grassmann manifold. We develop a low complexity iterative algorithm, which converges to the global optimal solution under static channels. In time-varying channels, we propose a compensation technique to offset the variation of the time-varying optimal solution. We show with our theoretical result that, under some mild conditions, perfect tracking of the target outer precoder using the proposed algorithm is possible. Numerical results demonstrate that the two-tier precoding with the proposed iterative compensation algorithm can achieve a good performance with a significant complexity reduction compared with the conventional two-tier precoding techniques in the literature.