A Multistage Method for SCMA Codebook Design Based on MDS Codes

Silva, Bruno Fontana da; Silva, Danilo; Uchôa-Filho, Bartolomeu F.; Ruyet, Didier Le

doi:10.1109/lwc.2019.2925801

Cited by 20 publications

(9 citation statements)

References 11 publications

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“…Other codebook assignment strategies were proposed with the aim of assigning multiple codebooks for each user [72], [195], [196] or reusing the same codebook by different users [197]. For instance, the research work in [72] focus on the energy saving problem in the uplink and downlink SCMA systems based on a cross-layer approach which takes into account the user features, i.e.…”

Section: Sd Based Detectorsmentioning

confidence: 99%

Sparse Code Multiple Access: Potentials and Challenges

Rebhi

Hassan

Raoof

et al. 2021

IEEE Open J. Commun. Soc.

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The massive connectivity is among other unprecedented requirements which are expected to be satisfied in order to follow the perpetual increase of connected devices in the era of internet of things. In contrast to the family of conventional orthogonal multiple access schemes, the key distinguishing feature of non-orthogonal multiple access (NOMA) is its capacity to support the massive connectivity. Sparse code multiple access (SCMA) is one of the powerful schemes of code-domain NOMA (CD-NOMA) and is among the promising candidates of multiple access techniques to be employed in future generations of wireless communication systems thanks to the sparsity pattern of its codebooks. This technique has been actively investigated in recent years. In this paper, we provide a comprehensive survey of the state-of-the-art of SCMA. First, we will pinpoint SCMA place in the NOMA landscape including power-domain NOMA and CD-NOMA with the aim of justifying why SCMA is prominent. Then, its system architecture is highlighted and its basic principles are presented, afterwards a review of exiting codebook designs and available SCMA detectors is provided, before showing how resources are expected to be assigned, and how SCMA can be combined with other existing and emerging technologies. Finally, we present a range of future research trends and challenging open issues that should be addressed to optimize SCMA performance.

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Section: Sd Based Detectorsmentioning

confidence: 99%

Sparse Code Multiple Access: Potentials and Challenges

Rebhi

Hassan

Raoof

et al. 2021

IEEE Open J. Commun. Soc.

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show abstract

“…Both of [21] and [22] have declared that mutual information can be utilized in designing SCMA codebooks, they respectively proposed different optimization methods based on that. Other SCMA codebook optimization methods, including genetic algorithm [23], constellation segmentation [24], dimensional permutation switching [25], golden angle modulation [26] and maximum distance separable codes [27] have also been investigated.…”

Section: Related Workmentioning

confidence: 99%

A novel deep neural network based approach for sparse code multiple access

et al. 2020

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Sparse code multiple access (SCMA) has been one of non-orthogonal multiple access (NOMA) schemes aiming to support high spectral efficiency and ubiquitous access requirements for 5G wireless communication networks. Conventional SCMA approaches are confronting remarkable challenges in designing low complexity high accuracy decoding algorithm and constructing optimum codebooks. Fortunately, the recent spotlighted deep learning technologies are of significant potentials in solving many communication engineering problems. Inspired by this, we explore approaches to improve SCMA performances with the help of deep learning methods. We propose and train a deep neural network (DNN) called DL-SCMA to learn to decode SCMA modulated signals corrupted by additive white Gaussian noise (AWGN). Putting encoding and decoding together, an autoencoder called AE-SCMA is established and trained to generate optimal SCMA codewords and reconstruct original bits. Furthermore, by manipulating the mapping vectors, an autoencoder is able to generalize SCMA, thus a dense code multiple access (DCMA) scheme is proposed. Simulations show that the DNN SCMA decoder significantly outperforms the conventional message passing algorithm (MPA) in terms of bit error rate (BER), symbol error rate (SER) and computational complexity, and AE-SCMA also demonstrates better performances via constructing better SCMA codebooks. The performance of deep learning aided DCMA is superior to the SCMA.As depicted in Fig. 1, consider J users transmitting data bits over the same K sub-carriers of OFDM, here K < J such that overloading is provided. According to SCMA encoder, each user maps every m = log 2 (M ) bits into a K-dimensional complex codeword c with only N non-zero elements standing for QAM modulation and LDS spreading combination, here N < K. The overlapping degree is d f = JN K , and overloading ratio is λ = J K . There are M codewords forming a codebook for each user and each codebook is unique. The encoding procedure can be described by c = f (b), where b ∈ B log2(M ) and c ∈ C ⊂ C K with |C| = M . Function f is actually a mapping matrix which

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“…Entretanto, mesmo que um valor pequeno de q seja escolhido, o efeito exponencial de d f (k) ainda impõe um problema para valores altos de sobrecarga. Ainda, ao assumir q < M , a MSSD de X será menor do que N [6], o que pode causar uma degradação no desempenho em relaçãoà taxa de erro. Para contrapor esse efeito, codebooks com maior N podem ser projetados, mas isso causa um aumento nos graus de colisão médio, d f (k), e máximo, max k d f (k).…”

Section: Modelo Do Sistemaunclassified

“…O valor O ref correspondeà ordem de complexidade do MPA orginal para SCMA não-codificado, eé calculado com a Equação (3) usando (T o , T m ) = (1, 5). Codebooks LNCP foram projetados usando os métodos [6,16]. Algumas figuras de mérito desses codebooks são apresentadas na Tabela II.…”

Section: Modelo Do Sistemaunclassified

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Receptor SCMA de Baixa Complexidade Baseado em um MPA com Seleção Dinâmica de Arestas e Aproximação Gaussiana

Silva¹,

Uchôa-Filho²,

Ruyet³

2019

Anais De XXXVII Simpósio Brasileiro De Telecomunicações E Processamento De Sinais

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Resumo-Múltiplo acesso por códigos esparsos (SCMA)é uma proposta recente para futuras gerações de sistemas de comunicação, suportando sistemas sobrecarregados e colisões de usuários nos recursos compartilhados. Para lidar com a nãoortogonalidade gerada pela sobrecarga, SCMA explora a característica de esparsidade através do uso do algoritmo messagepassing (MPA) na detecção conjunta dos símbolos multidimensionais. Neste trabalho, apresentamos uma melhoria de um algoritmo MPA baseado em seleção de arestas e aproximação Gaussiana de interferência. Nossa proposta inclui uma seleção baseada em um limiar sobre o ganho de canal mais forte em cada recurso. Com esse limiar, o número de vizinhos considerados no cálculo das mensagens do MPA se torna uma variável aleatória. Nós derivamos a probabilidade de seleção de um certo número de arestas, em cada recurso, demonstrando que nosso método tem baixa probabilidade de complexidade alta no cálculo das mensagens do MPA. Por fim, mostramos que a proposta com limiar resulta em um melhor compromisso entre ordem de complexidade e desempenho em termos de taxa de erro. Palavras-Chave-SCMA, algoritmo message-passing, aproximação Gaussiana, seleção por limiar. Abstract-Sparse Code Multiple Access (SCMA) has been proposed for the newest generation of communication systems, considering overloaded non-orthogonal multiple access. To deal with the overload, SCMA exploits the sparsity feature with the aid of receivers based on the messsage-passing algorithm (MPA). In this paper, we review a low-complexity MPA receiver based on edge-selection and gaussian approximation. We improve this receiver by proposing a threshold-based criteria for the edge selection. With the threshold, the number of interfering neighbors considered in the calculation of each message of the MPA becomes a random variable. We derive the probability of a function node selecting a given number of edges, showing that our strategy results in a low probability of high complexity during the message calculation of the MPA in each resource. We also show that the proposed threshold results in a better trade-off between complexity and error-rate performance.

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A Multistage Method for SCMA Codebook Design Based on MDS Codes

Cited by 20 publications

References 11 publications

Sparse Code Multiple Access: Potentials and Challenges

Sparse Code Multiple Access: Potentials and Challenges

A novel deep neural network based approach for sparse code multiple access

Receptor SCMA de Baixa Complexidade Baseado em um MPA com Seleção Dinâmica de Arestas e Aproximação Gaussiana

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