Particle swarm optimization for SAGE maximization step in channel parameter estimation
IET Seminar Digest
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Please cite this item using this persistent URLhttp://hdl.handle.net/11693/27048
This paper presents an application of particle swarm optimization (PSO) in space alternating generalized expectation maximization (SAGE) algorithm. SAGE algorithm is a powerful tool for estimating channel parameters like delay, angles (azimuth and elevation) of arrival and departure, Doppler frequency and polarization. To demonstrate the improvement in processing time by utilizing PSO in SAGE algorithm, the channel parameters are estimated from a synthetic data and the computational expense of SAGE algorithm with PSO is discussed. (4 pages).
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