CUED Publications database

Capacity-achieving Sparse Superposition Codes via Approximate Message Passing Decoding

Rush, C and Greig, A and Venkataramanan, R (2016) Capacity-achieving Sparse Superposition Codes via Approximate Message Passing Decoding. IEEE Transactions on Information Theory, 63. pp. 1476-1500.

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Abstract

Sparse superposition codes were recently introduced by Barron and Joseph for reliable communication over the additive white Gaussian noise (AWGN) channel at rates approaching the channel capacity. The codebook is defined in terms of a Gaussian design matrix, and codewords are sparse linear combinations of columns of the matrix. In this paper, we propose an approximate message passing decoder for sparse superposition codes, whose decoding complexity scales linearly with the size of the design matrix. The performance of the decoder is rigorously analyzed and it is shown to asymptotically achieve the AWGN capacity with an appropriate power allocation. Simulation results are provided to demonstrate the performance of the decoder at finite blocklengths. We introduce a power allocation scheme to improve the empirical performance, and demonstrate how the decoding complexity can be significantly reduced by using Hadamard design matrices.

Item Type: Article
Uncontrolled Keywords: compressed sensing sparse regression codes capacity-achieving codes AWGN channel coded modulation low-complexity decoding
Subjects: UNSPECIFIED
Divisions: Div F > Signal Processing and Communications
Depositing User: Cron Job
Date Deposited: 17 Jul 2017 20:02
Last Modified: 14 Nov 2017 02:21
DOI: