SPARSE CODE MULTIPLE ACCESS CODEBOOK DESIGN USING SINGULAR VALUE DECOMPOSITION
Keyword(s):
Currently, sparse code multiple access (SCMA) is a commonly used multiple-access technique, and it is a strong candidate for implementation as part of the fifth generation (5G) of wireless mobile communications. Although several design methods are available for SCMA codebooks, we propose a new method that optimizes point-to-point distances within the same codeword and from codebook-to-codebook for the same carrier based on singular value decomposition (SVD). A neural network-based receiver is proposed for detecting and decoding SVD–SCMA codewords. The simulation results show an improvement in the bit error rate (BER) compared to that for methods such as low-density signatures (LDS), SCMA, and multidimensional SCMA (MD-SCMA).
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1993 ◽
Vol 140
(3)
◽
pp. 145
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Optimizing Image Compression Using Singular Value Decomposition Based on Structural Similarity Index
2017 ◽
Vol 7
(4)
◽
pp. 316
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