This thesis focuses on advanced signal processing techniques for multicarrier modulation, in particular, orthogonal frequency division multiplexing (OFDM). OFDM promises a substantial increase in data rate and robustness against the frequency selectivity of multipath channels. For coherent detection, channel estimation is essential for receiver design. In this thesis, we will present a receiver design where the channel estimator exploits the sparse nature of the physical channel. We present the most popular subspace algorithm from the array processing literature, namely root-MUSIC, recent sparse identication algorithms in the form of orthogonal matching pursuit (OMP) and basis pursuit (BP), and a hybrid method called path identication (PI) algorithm which is the main contribution of this thesis. We also compare the performance of these estimators with that of the conventional estimators such as least-squares (LS) estimator and linear minimum-mean-squares estimator (LMMSE).
Advisor: Professor Milica Stojanovic
Professor Milica Stojanovic
Professor Hanoch Lev-Ari
Professor Jennifer Dy