Efficient Soft-Input Soft-Output Detection of Dual-Layer MIMO Systems

TL;DR

This paper introduces a computationally efficient soft-input soft-output detection method for dual-layer MIMO systems that achieves exact max-log MAP performance with linear complexity, outperforming existing approximate methods.

Contribution

The paper presents an exact max-log MAP detection algorithm for dual-layer MIMO systems with linear complexity, improving efficiency over previous approximate solutions.

Findings

The proposed method's complexity grows linearly with constellation size.

It matches the performance of brute-force exhaustive search.

It outperforms existing approximate detection methods.

Abstract

A dual-layer multiple-input multiple-output (MIMO) system with multi-level modulation is considered. A computationally efficient soft-input soft-output receiver based on the exact max-log maximum a posteriori (max-log-MAP) principle is presented in the context of iterative detection and decoding. We show that the computational complexity of our exact max-log-MAP solution grows linearly with the constellation size and is, furthermore, less than that of the best known methods of Turbo-LORD that only provide approximate solutions. Using decoder feedback to change the decision thresholds of the constellation symbols, we show that the exhaustive search operation boils down to a simple slicing operation. For various simulation parameters, we verify that our solution performs identically to the brute-force exhaustive search max-log MAP solution.