Modern wireless communication systems are designed to operate in multipath environments where the transmitted information arrives at the receiver after reflecting of various obstacles. A superposition of multiple delayed, frequency-phase shifted copies of the original signal arrive at the receiver. Diversity in the multipath channels is a result of variation between the angle-of- arrivals(AOA), delays and Doppler shifts of the individual channel components. To take full advantage of this diversity, multipath communication channels should be accurately modeled. For this purpose, communication systems utilize antenna arrays and sophisticated signal processing techniques to produce estimates for multipath channel parameters. This book, therefore, provides several different novel array signal processing techniques for identification of multipath communication channels based on cross ambiguity function(CAF) calculation, swarm intelligence and compressed sensing (CS) theory. Performances of the proposed techniques are verified both on synthetic and real data. The analysis should help shed some light on accurate modeling of wireless communication channels.

Autorentext

Mehmet Burak Guldogan received his B.Sc, M.S and Ph.D degrees all in Electrical Engineering from Bilkent University, Ankara, Turkey. He is currently with the Electrical Engineering at the Linköping University.