Proceedings of the International Conference on Advances in Mechanical Engineering and Industrial Informatics

Power Allocation by PSO in MAC

Authors
Jingxi Zhang
Corresponding Author
Jingxi Zhang
Available Online April 2015.
DOI
10.2991/ameii-15.2015.206How to use a DOI?
Keywords
AWGN; MAC; Sigma Mapping; Channel Capacity; PSO; UEP
Abstract

The capacity of Additive White Gaussian Noise (AWGN) Multiple Access Channel (MAC) can be approached by means of power allocation. The MAC can be regarded as single user multiple level coding and modulation system by applying pulse amplitude modulation to the individual signal and superimposing the weighted signal. Sigma mapping is applied such that the mutual information is as close as possible to the channel capacity. In the design of sigma mapping, every individual signal is weighted by the appropriate power which is optimized by means of Particle Swarm Optimization (PSO). In the respect of approaching MAC capacity and computational complexity, the proposed optimization method is superior to that of Interior Point Method (IPM) and differential evolution. The optimized power can facilitate approaching MAC capacity in practical communication system.

Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the International Conference on Advances in Mechanical Engineering and Industrial Informatics
Series
Advances in Engineering Research
Publication Date
April 2015
ISBN
978-94-62520-69-1
ISSN
2352-5401
DOI
10.2991/ameii-15.2015.206How to use a DOI?
Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Jingxi Zhang
PY  - 2015/04
DA  - 2015/04
TI  - Power Allocation by PSO in MAC
BT  - Proceedings of the International Conference on Advances in Mechanical Engineering and Industrial Informatics
PB  - Atlantis Press
SP  - 1115
EP  - 1121
SN  - 2352-5401
UR  - https://doi.org/10.2991/ameii-15.2015.206
DO  - 10.2991/ameii-15.2015.206
ID  - Zhang2015/04
ER  -