Symbol-by-symbol maximum likelihood (ML) detection with reduced complexity over multicarrier systems

Shang-Ho Tsai; Xiaoli Yu; C. C.Jay Kuo

doi:10.1117/12.541979

Symbol-by-symbol maximum likelihood (ML) detection with reduced complexity over multicarrier systems

Shang-Ho Tsai^*, Xiaoli Yu, C. C.Jay Kuo

^*Corresponding author for this work

Department of Electrical and Computer Engineering

Research output: Contribution to journal › Conference article › peer-review

Abstract

A symbol-by-symbol maximum likelihood (ML) detection scheme for multicarrier (MC) systems is proposed in this work. When the number of subchannels is sufficiently large, the received symbols across all subchannels are approximately uncorrelated. Then, the proposed symbol-by-symbol ML detection, which is obtained by minimizing the symbol error probability, is nearly optimal. Furthermore, we will show how to reduce the complexity of the symbol-by-symbol ML detection when the constellation size is large. Simulation results show that the proposed symbol-by-symbol ML detection scheme outperforms the symbol-by-symbol minimum distance (MD) detection scheme by up to 2 dB in a noisy environment with crosstalk such as the DMT-ADSL system.

Original language	English
Article number	21
Pages (from-to)	228-238
Number of pages	11
Journal	Proceedings of SPIE - The International Society for Optical Engineering
Volume	5440
DOIs	https://doi.org/10.1117/12.541979
State	Published - 1 Dec 2004
Event	Digital Wireless Communications VI - Orlando, FL, United States Duration: 12 Apr 2004 → 13 Apr 2004

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title = "Symbol-by-symbol maximum likelihood (ML) detection with reduced complexity over multicarrier systems",

abstract = "A symbol-by-symbol maximum likelihood (ML) detection scheme for multicarrier (MC) systems is proposed in this work. When the number of subchannels is sufficiently large, the received symbols across all subchannels are approximately uncorrelated. Then, the proposed symbol-by-symbol ML detection, which is obtained by minimizing the symbol error probability, is nearly optimal. Furthermore, we will show how to reduce the complexity of the symbol-by-symbol ML detection when the constellation size is large. Simulation results show that the proposed symbol-by-symbol ML detection scheme outperforms the symbol-by-symbol minimum distance (MD) detection scheme by up to 2 dB in a noisy environment with crosstalk such as the DMT-ADSL system.",

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AU - Tsai, Shang-Ho

AU - Yu, Xiaoli

AU - Kuo, C. C.Jay

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N2 - A symbol-by-symbol maximum likelihood (ML) detection scheme for multicarrier (MC) systems is proposed in this work. When the number of subchannels is sufficiently large, the received symbols across all subchannels are approximately uncorrelated. Then, the proposed symbol-by-symbol ML detection, which is obtained by minimizing the symbol error probability, is nearly optimal. Furthermore, we will show how to reduce the complexity of the symbol-by-symbol ML detection when the constellation size is large. Simulation results show that the proposed symbol-by-symbol ML detection scheme outperforms the symbol-by-symbol minimum distance (MD) detection scheme by up to 2 dB in a noisy environment with crosstalk such as the DMT-ADSL system.

AB - A symbol-by-symbol maximum likelihood (ML) detection scheme for multicarrier (MC) systems is proposed in this work. When the number of subchannels is sufficiently large, the received symbols across all subchannels are approximately uncorrelated. Then, the proposed symbol-by-symbol ML detection, which is obtained by minimizing the symbol error probability, is nearly optimal. Furthermore, we will show how to reduce the complexity of the symbol-by-symbol ML detection when the constellation size is large. Simulation results show that the proposed symbol-by-symbol ML detection scheme outperforms the symbol-by-symbol minimum distance (MD) detection scheme by up to 2 dB in a noisy environment with crosstalk such as the DMT-ADSL system.

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Symbol-by-symbol maximum likelihood (ML) detection with reduced complexity over multicarrier systems

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