English

Variable-Length Sparse Feedback Codes for Point-to-Point, Multiple Access, and Random Access Channels

Information Theory 2023-12-12 v3 math.IT

Abstract

This paper investigates variable-length stop-feedback codes for memoryless channels in point-to-point, multiple access, and random access communication scenarios. The proposed codes employ LL decoding times n1,n2,,nLn_1, n_2, \dots, n_L for the point-to-point and multiple access channels and KL+1KL + 1 decoding times for the random access channel with at most KK active transmitters. In the point-to-point and multiple access channels, the decoder uses the observed channel outputs to decide whether to decode at each of the allowed decoding times n1,,nLn_1, \dots, n_L, at each time telling the encoder whether or not to stop transmitting using a single bit of feedback. In the random access scenario, the decoder estimates the number of active transmitters at time n0n_0 and then chooses among decoding times nk,1,,nk,Ln_{k, 1}, \dots, n_{k, L} if it believes that there are kk active transmitters. In all cases, the choice of allowed decoding times is part of the code design; given fixed value LL, allowed decoding times are chosen to minimize the expected decoding time for a given codebook size and target average error probability. The number LL in each scenario is assumed to be constant even when the blocklength is allowed to grow; the resulting code therefore requires only sparse feedback. The central results are asymptotic approximations of achievable rates as a function of the error probability, the expected decoding time, and the number of decoding times. A converse for variable-length stop-feedback codes with uniformly-spaced decoding times is included for the point-to-point channel.

Keywords

Cite

@article{arxiv.2103.09373,
  title  = {Variable-Length Sparse Feedback Codes for Point-to-Point, Multiple Access, and Random Access Channels},
  author = {Recep Can Yavas and Victoria Kostina and Michelle Effros},
  journal= {arXiv preprint arXiv:2103.09373},
  year   = {2023}
}

Comments

29 Pages. Presented at ISIT 2021. Accepted for publication at IEEE Transactions on Information Theory Dec. 2023

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