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

Title: NOMA Joint Channel Estimation and Signal Detection using Rotational Invariant Codes and GMM-based Clustering
Creator: Salari, Ayoob; Shirvanimoghaddam, Mahyar; Shahab, Muhammad B.; Li, Yonghui; Johnson, Sarah
Relation: IEEE Communications Letters Vol. -, Issue 11 July 2022, p. 1-5
Publisher Link: http://dx.doi.org/10.1109/LCOMM.2022.3189652
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Resource Type: journal article
Date: 2022
Description: 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.
Subject: symbols; codes; channel estimation; modulation; receivers; signal detection
Identifier: http://hdl.handle.net/1959.13/1449255
Identifier: uon:43622
Identifier: ISSN:1089-7798
Language: eng
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