Low Complexity Iterative Receiver Design for Sparse Code Multiple Access

Sparse code multiple access (SCMA) is one of the most promising methods among all the non-orthogonal multiple access techniques in the future 5G communication. Compared with some other non-orthogonal multiple access techniques, such as low density signature, SCMA can achieve better performance due t...

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Bibliographic Details
Published in:IEEE transactions on communications Vol. 65; no. 2; pp. 621 - 634
Main Authors: Wei, Fan, Chen, Wen
Format: Journal Article
Language:English
Published: New York IEEE 01.02.2017
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithms
Binary system
Codes
Complexity
Complexity theory
Computer simulation
Decoding
Iterative decoding
Lattices
list sphere decoding
Maximum likelihood decoding
Message passing
message passing algorithm
node pruning
NOMA
Non-orthogonal multiple access
Nonorthogonal multiple access
Redundancy
SCMA
Search algorithms
ISSN:0090-6778, 1558-0857
Online Access:Get full text
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Summary:Sparse code multiple access (SCMA) is one of the most promising methods among all the non-orthogonal multiple access techniques in the future 5G communication. Compared with some other non-orthogonal multiple access techniques, such as low density signature, SCMA can achieve better performance due to the shaping gain of the SCMA code words. However, despite the sparsity of the code words, the decoding complexity of the current message passing algorithm utilized by SCMA is still prohibitively high. In this paper, by exploring the lattice structure of SCMA code words, we propose a low-complexity decoding algorithm based on list sphere decoding (LSD). The LSD avoids the exhaustive search for all possible hypotheses and only considers signal within a hypersphere. As LSD can be viewed a depth-first tree search algorithm, we further propose several methods to prune the redundancy-visited nodes in order to reduce the size of the search tree. Simulation results show that the proposed algorithm can reduce the decoding complexity substantially while the performance loss compared with the existing algorithm is negligible.
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ISSN:0090-6778
1558-0857
DOI:10.1109/TCOMM.2016.2631468