Soft-Information Assisted Near-Optimum Nonlinear Detection for BLAST-type Space Division Multiplexing OFDM Systems
Soft-Information Assisted Near-Optimum Nonlinear Detection for BLAST-type Space Division Multiplexing OFDM Systems
In this contribution, a nonlinear hybrid detection scheme based on a novel soft-information assisted Genetic Algorithm (GA) is proposed for a Turbo Convolutional (TC) coded Space Division Multiplexing (SDM) aided Orthogonal Frequency Division Multiplexing (OFDM) system. Our numerical results show that the performance of the currently known GA-assisted system can be improved by about 2dB with the aid of the GA’s population-based soft solution, approaching the optimum performance of the soft-information assisted Maximum Likelihood (ML) detection, while exhibiting a lower complexity, especially in high-throughput scenarios. Furthermore, the proposed scheme is capable of achieving a good performance even in the so-called overloaded systems, where the number of transmit antennas is higher than the number of receiver antennas. Index Terms—Genetic algorithm, orthogonal frequency division multiplexing, soft information, space division multiplexing,
1230-1234
Jiang, Ming
0f3c0781-ba1f-456a-88b1-b39ec938264f
Akhtman, Jos
6f612df7-9c17-4351-8340-5171fd174330
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
April 2007
Jiang, Ming
0f3c0781-ba1f-456a-88b1-b39ec938264f
Akhtman, Jos
6f612df7-9c17-4351-8340-5171fd174330
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
Jiang, Ming, Akhtman, Jos and Hanzo, Lajos
(2007)
Soft-Information Assisted Near-Optimum Nonlinear Detection for BLAST-type Space Division Multiplexing OFDM Systems.
IEEE Transactions on Wireless Communications, 6 (4), .
Abstract
In this contribution, a nonlinear hybrid detection scheme based on a novel soft-information assisted Genetic Algorithm (GA) is proposed for a Turbo Convolutional (TC) coded Space Division Multiplexing (SDM) aided Orthogonal Frequency Division Multiplexing (OFDM) system. Our numerical results show that the performance of the currently known GA-assisted system can be improved by about 2dB with the aid of the GA’s population-based soft solution, approaching the optimum performance of the soft-information assisted Maximum Likelihood (ML) detection, while exhibiting a lower complexity, especially in high-throughput scenarios. Furthermore, the proposed scheme is capable of achieving a good performance even in the so-called overloaded systems, where the number of transmit antennas is higher than the number of receiver antennas. Index Terms—Genetic algorithm, orthogonal frequency division multiplexing, soft information, space division multiplexing,
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mj-ja-lh-april07-TWC.pdf
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Published date: April 2007
Organisations:
Southampton Wireless Group
Identifiers
Local EPrints ID: 264038
URI: http://eprints.soton.ac.uk/id/eprint/264038
PURE UUID: 68b112ae-eb2b-4a55-9186-d907a623668a
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Date deposited: 22 May 2007
Last modified: 18 Mar 2024 02:34
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Contributors
Author:
Ming Jiang
Author:
Jos Akhtman
Author:
Lajos Hanzo
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