A MAP-Based Layered Detection Algorithm and Outage Analysis over MIMO Channels

TL;DR

This paper introduces a MAP-based layered detection algorithm called M-BLAST for MIMO channels, demonstrating improved error performance and providing a rigorous outage analysis that matches simulation results.

Contribution

The paper proposes a new M-BLAST detection algorithm with superior error performance and develops an analytical framework for outage analysis in MIMO systems.

Findings

M-BLAST outperforms V-BLAST with up to 2 dB SNR gain.

Analytical outage results match simulation data across various SNRs.

Framework potentially extendable to multiple antennas and larger constellations.

Abstract

Efficient symbol detection algorithms carry critical importance for achieving the spatial multiplexing gains promised by multi-input multi-output (MIMO) systems. In this paper, we consider a maximum a posteriori probability (MAP) based symbol detection algorithm, called M-BLAST, over uncoded quasi-static MIMO channels. Relying on the successive interference cancellation (SIC) receiver, M-BLAST algorithm offers a superior error performance over its predecessor V-BLAST with a signal-to-noise ratio (SNR) gain of as large as 2 dB under various settings of recent interest. Performance analysis of the M-BLAST algorithm is very complicated since the proposed detection order depends on the decision errors dynamically, which makes an already complex analysis of the conventional ordered SIC receivers even more difficult. To this end, a rigorous analytical framework is proposed to analyze the outage behavior of the M-BLAST algorithm over binary complex alphabets and two transmitting antennas, which has a potential to be generalized to multiple transmitting antennas and multidimensional constellation sets. The numerical results show a very good match between the analytical and simulation data under various SNR values and modulation alphabets.