Particle swarm optimization for SAGE maximization step in channel parameter estimation
IET Seminar Digest
MetadataShow full item record
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).
- Conference Paper 2294
Showing items related by title, author, creator and subject.
Efficient channel estimation for reconfigurable MIMO antennas: Training techniques and performance analysis Bahceci I.; Hasan M.; Duman T.M.; Cetiner B.A. (Institute of Electrical and Electronics Engineers Inc., 2017)Multifunctional and reconfigurable multiple-input multiple-output (MR-MIMO) antennas are capable of dynamically changing the operation frequencies, polarizations, and radiation patterns, and can remarkably enhance system ...
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 ...
Robust adaptive algorithms for underwater acoustic channel estimation and their performance analysis Kari D.; Marivani I.; Khan F.; Sayin M.O.; Kozat S.S. (Elsevier Inc., 2017)We introduce a novel family of adaptive robust channel estimators for highly challenging underwater acoustic (UWA) channels. Since the underwater environment is highly non-stationary and subjected to impulsive noise, we ...