Performance Evaluation of UWB Using Compressed Sensing in Multipath Channel Estimations

We consider the problem of channel estimation for ultrawideband communication in a multipath channel using compressed sensing techniques. The receiver when using a compressed sensing approach consists of a number of correlators processing the received signal with random projection vectors. The theory is based on Gaussian distributed vectors. We have compared the performance of using orthogonal Hadamard vectors with that of using a random projection matrix in compressed sensing procedures. We have also compared the performance of systems with different parameters for Gaussian and Hadamard projections vectors such as number of pilots, number of projection vectors and different coding schemes. Moreover, we are investigating different receiver structures resulting in different complexity of the receivers. We show that the sampling rate can be reduced significantly with only a slight degradation in the performance.