NOMA Joint Channel Estimation and Signal Detection using Rotational Invariant Codes and GMM-based Clustering

TL;DR

This paper introduces a pilot-free joint channel estimation and signal detection method for uplink NOMA using rotational-invariant codes and GMM clustering, achieving near-optimal BER performance without pilot symbols.

Contribution

It proposes a novel pilot-free detection and estimation scheme combining rotational-invariant coding with GMM clustering for uplink NOMA systems.

Findings

Achieves BER performance comparable to conventional methods with full CSI

Eliminates the need for pilot symbols in channel estimation

Uses GMM clustering for automatic signal classification

Abstract

This paper studies the joint channel estimation and signal detection for the uplink power-domain non-orthogonal multiple access. The proposed technique performs both detection and estimation without the need of pilot symbols by using a clustering technique. We apply rotational-invariant coding to assist signal detection at the receiver without sending pilot symbols. We utilize Gaussian mixture model (GMM) to automatically cluster the received signals without supervision and optimize decision boundaries to improve the bit error rate (BER) performance. Simulation results show that the proposed scheme without using any pilot symbol achieves almost the same BER performance as that for the conventional maximum likelihood receiver with full channel state information.