Particle swarm optimization for SAGE maximization step in channel parameter estimation
IET Seminar Digest
Item Usage Stats
MetadataShow full item record
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).
Particle swarm optimization.
Space alternating generalized expectation maximization
Particle swarm optimization (PSO)
Published Version (Please cite this version)http://dx.doi.org/10.1049/ic.2007.1226
Showing items related by title, author, creator and subject.
Gursoy, M.C.; Gezici, S. (2011)Cognitive radio transmissions in the presence of channel uncertainty are considered. In practical scenarios, cognitive secondary users need to perform both channel sensing in order to identify whether the channel is being ...
Arikan, E. (IEEE, 2002)We determine the reliability exponent E(R) of the Anantharam-Verdú exponential server timing channel with service rate μ for all rates R between a critical rate R c = (μ/4) log 2 and the channel capacity C = e -1μ. For ...
Cırpan, H. A.; Panayırcı, E.; Doğan, H. (Institute of Electrical and Electronics Engineers, 2006)This paper proposes a computationally efficient nondata-aided maximum a posteriori (MAP) channel-estimation algorithm focusing on the space-frequency (SF) transmit diversity orthogonal frequency division multiplexing (OFDM) ...