2005Unpublished venueRequires access

Maximum likelihood detection of phase shift keying modulated signal with self-organized clustering assistant

Somkiat Lerkvaranyu, Yoshikazu Miyanaga

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Abstract

For the detection of phase shift keying (PSK) modulated signal in the presence of phase error and Gaussian noise, the maximum likelihood detection with self-organized clustering assistant (ML-SOCA) is proposed in this paper. When the training data available, the system use the training sequences which are transmitted within each burst to adapt the decision region by SOCA. Simulation results were obtained with 4PSK and 8PSK in an additive white Gaussian noise (AWGN) channel.

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What this paper is about

For the detection of phase shift keying (PSK) modulated signal in the presence of phase error and Gaussian noise, the maximum likelihood detection with self-organized clustering assistant (ML-SOCA) is proposed in this paper. When the training data available, the system use the training sequences which are transmitted within each burst to adapt the decision region by SOCA. Simulation results were obtained with 4PSK and 8PSK in an additive white Gaussian noise (AWGN) channel.

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Available abstract

For the detection of phase shift keying (PSK) modulated signal in the presence of phase error and Gaussian noise, the maximum likelihood detection with self-organized clustering assistant (ML-SOCA) is proposed in this paper. When the training data available, the system use the training sequences which are transmitted within each burst to adapt the decision region by SOCA. Simulation results were obtained with 4PSK and 8PSK in an additive white Gaussian noise (AWGN) channel.

Key concepts: Additive white Gaussian noise, Phase-shift keying, Keying, Cluster analysis, Computer science, White noise, Gaussian noise, Signal-to-noise ratio (imaging)

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