Iterative Detection and Decoding for Clustered Cell-Free Massive MIMO Networks

TL;DR

This paper introduces an iterative interference cancellation method for clustered cell-free massive MIMO networks, improving interference mitigation and bit error rate performance through novel filtering and estimation techniques.

Contribution

It presents a new iterative detection and decoding scheme with a modified interference cancellation approach and OCL interference estimation, advancing interference mitigation in cell-free MIMO.

Findings

Enhanced interference mitigation compared to existing methods.

Improved bit error rate performance demonstrated through simulations.

Effective OCL interference estimation using least squares approach.

Abstract

In this letter, we propose an iterative soft interference cancellation scheme for intra-cluster (ICL) and out-of-cluster (OCL) interference mitigation in user-centric clustered cell-free massive multiple-antenna networks. We propose a minimum mean-square error receive filter with a novel modified parallel interference cancellation scheme to mitigate ICL and OCL interference. Unlike prior work, we model the OCL interference and devise a least squares estimator to perform OCL interference estimation. An iterative detection and decoding scheme that adopts low-density parity check codes and incorporates the OCL interference estimate is developed. Simulations assess the proposed scheme against existing techniques in terms of bit error rate performance.