Adaptive Iterative Decision Feedback Detection Algorithms for Multi-User MIMO Systems

TL;DR

This paper introduces an adaptive iterative decision feedback detection algorithm with constellation constraints for multi-user MIMO systems, improving interference cancellation and reducing complexity while maintaining near-optimal performance.

Contribution

It proposes a novel adaptive iterative detection scheme with constellation constraints and complexity reduction for multi-user MIMO systems.

Findings

Achieves near-maximum likelihood detection performance

Maintains low complexity comparable to conventional detectors

Effectively cancels interference in multi-user MIMO channels

Abstract

An adaptive iterative decision multi-feedback detection algorithm with constellation constraints is proposed for multiuser multi-antenna systems. An enhanced detection and interference cancellation is performed by introducing multiple constellation points as decision candidates. A complexity reduction strategy is developed to avoid redundant processing with reliable decisions along with an adaptive recursive least squares algorithm for time-varying channels. An iterative detection and decoding scheme is also considered with the proposed detection algorithm. Simulations show that the proposed technique has a complexity as low as the conventional decision feedback detector while it obtains a performance close to the maximum likelihood detector.