Open AccessSPARSE CODE MULTIPLE ACCESS CODEBOOK DESIGN USING SINGULAR VALUE DECOMPOSITION
Author(s) -
S. Vidal-Beltrán,
Ricardo Carreño Aguilera,
José Luis López Bonilla
Publication year - 2020
Publication title -
fractals
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.654
H-Index - 44
eISSN - 1793-6543
pISSN - 0218-348X
DOI - 10.1142/s0218348x21500213
Subject(s) - codebook , code word , singular value decomposition , computer science , code (set theory) , decoding methods , algorithm , set (abstract data type) , programming language
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).