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On Capacity-Based Codebook Design and Advanced Decoding for Sparse Code Multiple Access Systems

delete2018-06-01
delete45
PRE
AI
B
Bin Xia *
陈
陈智勇 (Zhiyong Chen)
D
Dageng Chen
S
Shaodan Ma
DOI:10.1109/TWC.2018.2816929delete
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Abstract

Abstract

En 中文
Sparse code multiple access (SCMA) is a promising non-orthogonal air-interface technology for its ability to support massive connections. In this paper, we design the multiuser codebook and the advanced decoding from the perspective of the theoretical capacity and the system feasibility. First, different from the lattice-based constellation in point-to-point channels, we propose a novel codebook for maximizing the constellation constrained capacity. We optimize a series of 1-D superimposed constellations to construct multi-dimensional codewords. An effective dimensional permutation switching algorithm is proposed to further obtain the capacity gain. Consequently, it shows that the performance of the proposed codebook approaches the Shannon limit and achieves significant gains over the other existing ones. Furthermore, we provide a symbol-based extrinsic information transfer tool to analyze the convergence of SCMA iterative detection, where the complex codewords are considered in modeling the a priori probabilities instead of assuming the binary inputs in previous literature. Finally, to approach the capacity, we develop a low-density parity-check code-based SCMA receiver. Most importantly, by utilizing the EXIT charts, we propose an iterative joint detection and decoding scheme with only partial inner iterations, which exhibits significant performance gain over the traditional one with separate detection and decoding.
Keywords:
Sparse code multiple access
multi-dimensional codebook
converge analysis
iterative decoding

Journal

IEEE Transactions on Wireless Communications cover
IEEE Transactions on Wireless Communications
IF:
10.7
Papers:
1.3W
Citations:
6.3W

Organization

H
huawei technologies
Scholars:
43
Papers: 24
Citations: 1.2K
Shanghai Jiao Tong University cover
Shanghai Jiao Tong University
Scholars:
9.9K
Papers: 2.9K
Citations: 4.5W
U
University of Macau
Scholars:
1.1K
Papers: 541
Citations: 5.9K
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