Journal
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
Volume 22, Issue 8, Pages 5240-5252Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TWC.2022.3232781
Keywords
Rateless codes; multiple access scheme; finite length analysis; maximum likelihood (ML) decoding; additive white Gaussian noise (AWGN) channels; decoding error probability
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In this paper, the maximum likelihood (ML) decoding performance of the RMA scheme in an AWGN channel with BPSK modulation is investigated. For the first time, the ensemble weight distribution of the RMA scheme is derived. An upper bound on the decoding error performance of the RMA scheme under ML decoding in an AWGN channel with BPSK modulation is also derived. The continuous genetic algorithm is then used to optimize the parameters of the RMA scheme, with simulation results showing the tightness of the derived bound and the superiority of the optimized degree distribution.
The rateless multiple access (RMA) scheme is a promising distributed multiple access scheme to achieve simultaneous high reliability, low latency and massive connectivity. In this paper, we investigate the maximum likelihood (ML) decoding performance of the RMA scheme in an Additive white Gaussian noise (AWGN) channel with binary phase-shift keying (BPSK) modulation. For the first time, this paper derives the ensemble weight distribution of the RMA scheme. We derive an upper bound on the decoding error performance of the RMA scheme under ML decoding in an AWGN channel with BPSK modulation. Using the derived bound as the fitness function, we adopt the continuous genetic algorithm to optimize the parameters of the RMA scheme. Simulation results show the tightness of the derived bound and the superiority of the optimized degree distribution over the conventional degree distributions.
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