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Multipath channel identification by using global optimization in ambiguity function domain
Authors:Mehmet Burak Guldogan  Orhan Arikan
Affiliation:a Department of Electrical Engineering, Linköping University, Linköping SE-58183, Sweden
b Department of Electrical and Electronics Engineering, Bilkent University, Ankara TR-06800, Turkey
Abstract:A new transform domain array signal processing technique is proposed for identification of multipath communication channels. The received array element outputs are transformed to delay-Doppler domain by using the cross-ambiguity function (CAF) for efficient exploitation of the delay-Doppler diversity of the multipath components. Clusters of multipath components can be identified by using a simple amplitude thresholding in the delay-Doppler domain. Particle swarm optimization (PSO) can be used to identify parameters of the multipath components in each cluster. The performance of the proposed PSO-CAF technique is compared with the space alternating generalized expectation maximization (SAGE) technique and with a recently proposed PSO based technique at various SNR levels. Simulation results clearly quantify the superior performance of the PSO-CAF technique over the alternative techniques at all practically significant SNR levels.
Keywords:Cross ambiguity function (CAF)   Particle swarm optimization (PSO)   Channel identification   Maximum likelihood (ML)
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