A low-complexity energy minimization based SCMA detector and its convergence analysis
A low-complexity energy minimization based SCMA detector and its convergence analysis
Sparse code multiple access (SCMA) has emerged as a promising non-orthogonal multiple access (NOMA) technique for next generation wireless communication systems. Since the signal of multiple users is mapped to the same resources in SCMA, its detection imposes a higher complexity than that of the orthogonal schemes, where each resource slot is dedicated to a single user. In this paper, we propose a low complexity receiver for SCMA systems based on the radical variational free energy framework. By exploiting the pairwise structure of the likelihood function, the Bethe approximation is utilized for estimating the data symbols. The complexity of the proposed algorithm only increases linearly with the number of users, which is much lower than that of the maximum a posteriori (MAP) detector associated with exponentially increased complexity. Furthermore, the convergence of the proposed algorithm is analyzed and its convergence conditions are derived. Simulation resultsdemonstrate that the proposed receiver is capable of approaching the error probability performance of the conventional message passing based receiver.
Bethe approximation, convergence analysis, Sparse code multiple access, variational free energy
Yuan, Weijie
f1d6dc8e-6e97-4c5b-bfc7-78f48efb93b7
Wu, Nan
b22977ef-fd11-4eb1-8c5c-2b108b58907b
Yan, Chaoxing
c7bc0d86-7445-4705-a830-2041c52d9b79
Li, Yonghui
3065a1c4-56db-4883-89c2-37b72b48f678
Huang, Xiaojing
dda503f6-c404-45f4-8129-dbf223d7cd1c
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
Yuan, Weijie
f1d6dc8e-6e97-4c5b-bfc7-78f48efb93b7
Wu, Nan
b22977ef-fd11-4eb1-8c5c-2b108b58907b
Yan, Chaoxing
c7bc0d86-7445-4705-a830-2041c52d9b79
Li, Yonghui
3065a1c4-56db-4883-89c2-37b72b48f678
Huang, Xiaojing
dda503f6-c404-45f4-8129-dbf223d7cd1c
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
Yuan, Weijie, Wu, Nan, Yan, Chaoxing, Li, Yonghui, Huang, Xiaojing and Hanzo, Lajos
(2018)
A low-complexity energy minimization based SCMA detector and its convergence analysis.
IEEE Transactions on Vehicular Technology, 12 (67).
(doi:10.1109/TVT.2018.2876121).
Abstract
Sparse code multiple access (SCMA) has emerged as a promising non-orthogonal multiple access (NOMA) technique for next generation wireless communication systems. Since the signal of multiple users is mapped to the same resources in SCMA, its detection imposes a higher complexity than that of the orthogonal schemes, where each resource slot is dedicated to a single user. In this paper, we propose a low complexity receiver for SCMA systems based on the radical variational free energy framework. By exploiting the pairwise structure of the likelihood function, the Bethe approximation is utilized for estimating the data symbols. The complexity of the proposed algorithm only increases linearly with the number of users, which is much lower than that of the maximum a posteriori (MAP) detector associated with exponentially increased complexity. Furthermore, the convergence of the proposed algorithm is analyzed and its convergence conditions are derived. Simulation resultsdemonstrate that the proposed receiver is capable of approaching the error probability performance of the conventional message passing based receiver.
This record has no associated files available for download.
More information
Accepted/In Press date: 11 October 2018
e-pub ahead of print date: 25 October 2018
Keywords:
Bethe approximation, convergence analysis, Sparse code multiple access, variational free energy
Identifiers
Local EPrints ID: 427736
URI: http://eprints.soton.ac.uk/id/eprint/427736
ISSN: 0018-9545
PURE UUID: 6c9f669b-4703-4b0d-a49d-a12aee13758e
Catalogue record
Date deposited: 25 Jan 2019 17:30
Last modified: 18 Mar 2024 02:36
Export record
Altmetrics
Contributors
Author:
Weijie Yuan
Author:
Nan Wu
Author:
Chaoxing Yan
Author:
Yonghui Li
Author:
Xiaojing Huang
Author:
Lajos Hanzo
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics