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Title: Decision Boundary for Underwater Acoustic Communication with Generalized Gaussian Noise Model
Authors: Bhuyan, S
Deshmukh, S
Keywords: Underwater Acoustic Communication
Generalized Gaussian Statistics
Expectation Maximization Algorithm
Detector Design
Issue Date: Jun-2016
Publisher: IEEE
Citation: International Conference on Signal Processing and Communications (SPCOM), Bangalore, India, 12-15 Jun 2016
Abstract: In this paper, we consider Generalized Gaussian (GG) distribution to model the additive noise source in underwater acoustic (UWA) communication. Since communication in oceanic medium is dominated by both prevailing and spontaneous noise sources, we model the resultant noise distribution as mixture of GG distribution. Owing to the complexity in optimal detector design with GG noise model, we apply expectation maximization (EM) algorithm to decompose the resultant channel distribution in terms of weighted sum of Gaussian density functions. By having multiple antennas at the receiver, we also exploit spatial diversity to improve error performance at the receiver. In this context, we compute decision boundary for detecting the binary phase shift keying (BPSK) modulated signal. In addition, we also discuss variation in decision boundary under various signal to noise ratio (SNR) levels observed at receiverfront end. Finally, we compare the detector performance under new decision boundary with traditional detectors and validate the approach by showing improvement in symbol error rate performance.
Description: Copyright belongs to proceeding publisher
Appears in Collections:Conference Papers

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