Precoding optimization for the sparse MC-CDMA downlink communication

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionResearchpeer-review

Abstract

We introduce a novel Multi-Carrier Code Division Multiple Access (MC-CDMA) system, where random sparse signatures are deployed in the frequency domain. Data symbols transmitted from base station (BS) to mobile stations (MSs) are drawn from discrete finite alphabets, such as M-QAM constellations. Transmitter-based precoding is introduced so as to allow simple despreading followed by single-user detection at MSs. A power-efficient non-linear precoding optimization problem is formulated by imposing minimum Symbol Error Probability (SEP) targets at MSs. We first elaborate on how to translate the SEP targets into exact constraint regions on noiseless received components at MSs. With relaxation on the exact regions, a tractable convex problem is obtained. A dual-decomposition-based algorithm is then developed to accommodate parallel processors to perform precoding calculation. The signature sparsity turns out to be vital to reduce interprocessor communication overhead and computational complexity for pre-coding. The scheme proposed offers considerable transmit power reduction compared with the conventional zero-forcing precoder.

LanguageEnglish
Title of host publication2014 IEEE International Conference on Communications, ICC 2014
Place of PublicationPiscataway, NJ
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages2106-2111
Number of pages6
ISBN (Print)9781479920037
DOIs
Publication statusPublished - 2014
Event2014 1st IEEE International Conference on Communications, ICC 2014 - Sydney, NSW, Australia
Duration: 10 Jun 201414 Jun 2014

Other

Other2014 1st IEEE International Conference on Communications, ICC 2014
CountryAustralia
CitySydney, NSW
Period10/06/1414/06/14

Fingerprint

Code division multiple access
Communication
Quadrature amplitude modulation
Base stations
Transmitters
Computational complexity
Decomposition
Error probability

Cite this

Li, M., & Hanly, S. V. (2014). Precoding optimization for the sparse MC-CDMA downlink communication. In 2014 IEEE International Conference on Communications, ICC 2014 (pp. 2106-2111). [6883634] Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/ICC.2014.6883634
Li, Min ; Hanly, Stephen V. / Precoding optimization for the sparse MC-CDMA downlink communication. 2014 IEEE International Conference on Communications, ICC 2014. Piscataway, NJ : Institute of Electrical and Electronics Engineers (IEEE), 2014. pp. 2106-2111
@inproceedings{6ebdfa55a9884d7f8c5a39c6e16added,
title = "Precoding optimization for the sparse MC-CDMA downlink communication",
abstract = "We introduce a novel Multi-Carrier Code Division Multiple Access (MC-CDMA) system, where random sparse signatures are deployed in the frequency domain. Data symbols transmitted from base station (BS) to mobile stations (MSs) are drawn from discrete finite alphabets, such as M-QAM constellations. Transmitter-based precoding is introduced so as to allow simple despreading followed by single-user detection at MSs. A power-efficient non-linear precoding optimization problem is formulated by imposing minimum Symbol Error Probability (SEP) targets at MSs. We first elaborate on how to translate the SEP targets into exact constraint regions on noiseless received components at MSs. With relaxation on the exact regions, a tractable convex problem is obtained. A dual-decomposition-based algorithm is then developed to accommodate parallel processors to perform precoding calculation. The signature sparsity turns out to be vital to reduce interprocessor communication overhead and computational complexity for pre-coding. The scheme proposed offers considerable transmit power reduction compared with the conventional zero-forcing precoder.",
author = "Min Li and Hanly, {Stephen V.}",
year = "2014",
doi = "10.1109/ICC.2014.6883634",
language = "English",
isbn = "9781479920037",
pages = "2106--2111",
booktitle = "2014 IEEE International Conference on Communications, ICC 2014",
publisher = "Institute of Electrical and Electronics Engineers (IEEE)",
address = "United States",

}

Li, M & Hanly, SV 2014, Precoding optimization for the sparse MC-CDMA downlink communication. in 2014 IEEE International Conference on Communications, ICC 2014., 6883634, Institute of Electrical and Electronics Engineers (IEEE), Piscataway, NJ, pp. 2106-2111, 2014 1st IEEE International Conference on Communications, ICC 2014, Sydney, NSW, Australia, 10/06/14. https://doi.org/10.1109/ICC.2014.6883634

Precoding optimization for the sparse MC-CDMA downlink communication. / Li, Min; Hanly, Stephen V.

2014 IEEE International Conference on Communications, ICC 2014. Piscataway, NJ : Institute of Electrical and Electronics Engineers (IEEE), 2014. p. 2106-2111 6883634.

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionResearchpeer-review

TY - GEN

T1 - Precoding optimization for the sparse MC-CDMA downlink communication

AU - Li, Min

AU - Hanly, Stephen V.

PY - 2014

Y1 - 2014

N2 - We introduce a novel Multi-Carrier Code Division Multiple Access (MC-CDMA) system, where random sparse signatures are deployed in the frequency domain. Data symbols transmitted from base station (BS) to mobile stations (MSs) are drawn from discrete finite alphabets, such as M-QAM constellations. Transmitter-based precoding is introduced so as to allow simple despreading followed by single-user detection at MSs. A power-efficient non-linear precoding optimization problem is formulated by imposing minimum Symbol Error Probability (SEP) targets at MSs. We first elaborate on how to translate the SEP targets into exact constraint regions on noiseless received components at MSs. With relaxation on the exact regions, a tractable convex problem is obtained. A dual-decomposition-based algorithm is then developed to accommodate parallel processors to perform precoding calculation. The signature sparsity turns out to be vital to reduce interprocessor communication overhead and computational complexity for pre-coding. The scheme proposed offers considerable transmit power reduction compared with the conventional zero-forcing precoder.

AB - We introduce a novel Multi-Carrier Code Division Multiple Access (MC-CDMA) system, where random sparse signatures are deployed in the frequency domain. Data symbols transmitted from base station (BS) to mobile stations (MSs) are drawn from discrete finite alphabets, such as M-QAM constellations. Transmitter-based precoding is introduced so as to allow simple despreading followed by single-user detection at MSs. A power-efficient non-linear precoding optimization problem is formulated by imposing minimum Symbol Error Probability (SEP) targets at MSs. We first elaborate on how to translate the SEP targets into exact constraint regions on noiseless received components at MSs. With relaxation on the exact regions, a tractable convex problem is obtained. A dual-decomposition-based algorithm is then developed to accommodate parallel processors to perform precoding calculation. The signature sparsity turns out to be vital to reduce interprocessor communication overhead and computational complexity for pre-coding. The scheme proposed offers considerable transmit power reduction compared with the conventional zero-forcing precoder.

UR - http://www.scopus.com/inward/record.url?scp=84906997233&partnerID=8YFLogxK

U2 - 10.1109/ICC.2014.6883634

DO - 10.1109/ICC.2014.6883634

M3 - Conference proceeding contribution

SN - 9781479920037

SP - 2106

EP - 2111

BT - 2014 IEEE International Conference on Communications, ICC 2014

PB - Institute of Electrical and Electronics Engineers (IEEE)

CY - Piscataway, NJ

ER -

Li M, Hanly SV. Precoding optimization for the sparse MC-CDMA downlink communication. In 2014 IEEE International Conference on Communications, ICC 2014. Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE). 2014. p. 2106-2111. 6883634 https://doi.org/10.1109/ICC.2014.6883634