Delay-Optimal Power and Precoder Adaptation for Multi-stream MIMO Systems

TL;DR

This paper develops delay-optimal precoding and power allocation strategies for multi-stream MIMO systems with heterogeneous traffic, using Markov Decision Processes to achieve near-optimal performance with reduced computational complexity.

Contribution

It introduces a low-complexity offline solution for delay-optimal MIMO precoding and power allocation using static eigenchannel sorting and problem decomposition.

Findings

Offline solution has complexity ${ m O}(NL)$

Close-to-optimal performance achieved

Decomposition simplifies the MDP problem

Abstract

In this paper, we consider delay-optimal MIMO precoder and power allocation design for a MIMO Link in wireless fading channels. There are $L$ data streams spatially multiplexed onto the MIMO link with heterogeneous packet arrivals and delay requirements. The transmitter is assumed to have knowledge of the channel state information (CSI) as well as the joint queue state information (QSI) of the $L$ buffers. Using $L$-dimensional Markov Decision Process (MDP), we obtain optimal precoding and power allocation policies for general delay regime, which consists of an online solution and an offline solution. The online solution has negligible complexity but the offline solution has worst case complexity ${\cal O}((N+1)^L)$ where $N$ is the buffer size. Using {\em static sorting} of the $L$ eigenchannels, we decompose the MDP into $L$ independent 1-dimensional subproblems and obtained low complexity offline solution with linear complexity order ${\cal O}(NL)$ and close-to-optimal performance.