Near ML detection using Dijkstra's algorithm with bounded list size over MIMO channels

TL;DR

This paper introduces a modified Dijkstra's algorithm with bounded list size for MIMO channel detection, reducing computational complexity while maintaining near-ML detection performance.

Contribution

The paper presents a novel Dijkstra-based detection algorithm with bounded list size, improving efficiency over existing QRD-MLD methods in MIMO systems.

Findings

Proposed algorithm achieves similar SER to QRD-MLD

Lower average computational complexity with bounded list size

Effective for near-ML detection in MIMO channels

Abstract

We propose Dijkstra's algorithm with bounded list size after QR decomposition for decreasing the computational complexity of near maximum-likelihood (ML) detection of signals over multiple-input-multiple-output (MIMO) channels. After that, we compare the performances of proposed algorithm, QR decomposition M-algorithm (QRD-MLD), and its improvement. When the list size is set to achieve the almost same symbol error rate (SER) as the QRD-MLD, the proposed algorithm has smaller average computational complexity.