Adaptive Decision Feedback Detection with Parallel Interference Cancellation and Constellation Constraints for Multi-Antenna Systems

TL;DR

This paper introduces a low-complexity adaptive decision feedback detection method with parallel interference cancellation and constellation constraints for multi-antenna MIMO systems, improving performance with manageable complexity.

Contribution

It proposes a novel P-DFCC scheme with constellation constraints and reliability checking, enhancing interference cancellation and detection accuracy in multiuser MIMO systems.

Findings

Achieves near-ML performance at low to medium SNRs

Maintains low complexity comparable to conventional detectors

Improves interference cancellation through constellation constraints

Abstract

In this paper, a novel low-complexity adaptive decision feedback detection with parallel decision feedback and constellation constraints (P-DFCC) is proposed for multiuser MIMO systems. We propose a constrained constellation map which introduces a number of selected points served as the feedback candidates for interference cancellation. By introducing a reliability checking, a higher degree of freedom is introduced to refine the unreliable estimates. The P-DFCC is followed by an adaptive receive filter to estimate the transmitted symbol. In order to reduce the complexity of computing the filters with time-varying MIMO channels, an adaptive recursive least squares (RLS) algorithm is employed in the proposed P-DFCC scheme. An iterative detection and decoding (Turbo) scheme is considered with the proposed P-DFCC algorithm. Simulations show that the proposed technique has a complexity comparable to the conventional parallel decision feedback detector while it obtains a performance close to the maximum likelihood detector at a low to medium SNR range.