An Error Rate Comparison of Power Domain Non-Orthogonal Multiple Access and Sparse Code Multiple Access

Luo, Qu; Gao, Pengyu; Liu, Zilong; Xiao, Lixia; Mheich, Zeina; Xiao, Pei; Maaref, Amine

doi:10.1109/ojcoms.2021.3064504

Cited by 55 publications

(32 citation statements)

References 38 publications

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“…In [13], theoretical analysis and experimental validation are done for multi-user downlink. Arbitrary users analysis is considered in [14]- [16], [21]. Imperfect SIC modeling is done in [15], [17], [22], and [10] by considering different approaches for the error propagation phenomenon.…”

Section: Introductionmentioning

confidence: 99%

“…To the best of our knowledge, sufficient power spacing between users is generally assumed to avoid unnecessary interference. Traditionally, the usage of SIC in scenarios where interference is significant results in error floor [15], [20], [21], in which inadequate power allocation between users can increase the error propagation in SIC decoding [14]. In particular, results from [21] suggest that the usage a neural network-based decoding is capable of decisively outperforming the traditional SIC decoding.…”

Section: Introductionmentioning

confidence: 99%

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Successive Interference Cancellation Decoding With Adaptable Decision Regions for NOMA Schemes

et al. 2022

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In this work, we propose adaptable decision regions in the successive interference cancellation (SIC) decoder for the three-user uplink/downlink non-orthogonal multiple access (NOMA) scheme by exploiting the knowledge of the channel gains. We present scenarios in which the modified SIC decoder outperforms the traditional one and is able to replicate the performance achieved by a deep learning-based decoder. We present analytical symbol error rate (SER) expressions for the three users, compare them to simulation results, and discuss possible consequences of our analysis, such as the optimal power allocation. We also employ heatmaps to analyze the joint influence on the SER of some system parameters, such as signal-to-noise ratio and channel gains.INDEX TERMS Non-orthogonal multiple access, successive interference cancellation, symbol error rate, decision regions.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Successive Interference Cancellation Decoding With Adaptable Decision Regions for NOMA Schemes

et al. 2022

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“…In a NOMA system, multiple users are able to communicate simultaneously to achieve overloading factor larger than 1. Existing NOMA techniques can be largely categorized into two classes: powerdomain NOMA and code-domain NOMA (CD-NOMA) [1], [2]. In this paper, we focus on an emerging CD-NOMA scheme called sparse code multiple access (SCMA) in which multiple users are separated by adopting different sparse codebooks [3], [4].…”

Section: Introductionmentioning

confidence: 99%

A Novel Multi-Task Learning Empowered Codebook Design for Downlink SCMA Networks

Luo¹,

Liu²,

Chen³

et al. 2022

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Sparse code multiple access (SCMA) is a promising code-domain non-orthogonal multiple access (NOMA) scheme for the enabling of massive machine-type communication. In SCMA, the design of good sparse codebooks and efficient multiuser decoding have attracted tremendous research attention in the past few years. This paper aims to leverage deep learning to jointly design the downlink SCMA encoder and decoder with the aid of autoencoder. We introduce a novel end-to-end learning based SCMA (E2E-SCMA) design framework, under which improved sparse codebooks and low-complexity decoder are obtained. Compared to conventional SCMA schemes, our numerical results show that the proposed E2E-SCMA leads to significant improvements in terms of error rate and computational complexity.

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“…Em sistemas NOMA, o fenômeno de patamar de erro é reportado na literatura [4]- [6], em que a alocação inadequada de potência entre os usuários pode potencializar a propagação de erros na decodificação SIC [7]. Em especial, os resultados de [4] sugerem que ao utilizar símbolos piloto e considerar diferenças pequenas para os parâmetros de ganhos do canal, um modelo baseado em rede neural é capaz de superar decisivamente a decodificação SIC tradicional.…”

Section: Introductionunclassified

Decodificação via Cancelamento Sucessivo de Interferência Generalizado para Sistemas de Acesso Múltiplo Não Ortogonal

Silva¹,

Souza²,

Pimentel³

et al. 2021

Anais Do XXXIX Simpósio Brasileiro De Telecomunicações E Processamento De Sinais

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Resumo-Neste trabalho é apresentado um decodificador com regiões de decisão adaptáveis para sistemas de acesso múltiplo não ortogonal uplink com três usuários que faz uso do pressuposto de conhecimento dos ganhos do canal. São apresentados cenários em que o desempenho do decodificador proposto supera o método de cancelamento sucessivo de interferência tradicional e é capaz de replicar resultados obtidos por métodos de aprendizagem profunda propostos recentemente na literatura.Palavras-Chave-Acesso múltiplo não ortogonal, cancelamento sucessivo de interferência, taxa de erro de símbolo, regiões de decisão.

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An Error Rate Comparison of Power Domain Non-Orthogonal Multiple Access and Sparse Code Multiple Access

Cited by 55 publications

References 38 publications

Successive Interference Cancellation Decoding With Adaptable Decision Regions for NOMA Schemes

Successive Interference Cancellation Decoding With Adaptable Decision Regions for NOMA Schemes

A Novel Multi-Task Learning Empowered Codebook Design for Downlink SCMA Networks

Decodificação via Cancelamento Sucessivo de Interferência Generalizado para Sistemas de Acesso Múltiplo Não Ortogonal

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