Abstract:
OFDM has become a popular technique for transmission of signals over wireless channels. It converts a frequency-selective channel into a parallel collection of frequency flat sub channels, which makes the receiver simpler. A MIMO system takes advantage of the spatial diversity obtained by spatially separated antennas in a dense multipath scattering environment. For high data-rate transmission, the multipath characteristic of the environment causes the MIMO channel to be frequency-selective. OFDM can transform such a frequency-selective MIMO channel into a set of parallel frequency-flat MIMO channels, and therefore decrease receiver 'complexity. The combination of the two powerful techniques, MIMO and OFDM, is very attractive, and has become a most promising broadband wireless access scheme. For detection of OFDM signals, channel must be known at the receiver. Channel estimation is a challenging problem in wireless systems.
The expectation-maximization (EM)-algorithm provides an iterative approach to likelihood-based parameter estimation. when direct maximization of the likelihood function may not be feasible. The EM algorithm consists of hvo major steps: an expectation step, followed by a.maximization step..
In this dissertation work, we consider EM and EM-MMSE based channel estimation techniques for OFDM systems. EM-MMSE technique is computationally simpler than EM technique. Following this, hard VBLAST-EM based channel estimation for MIMO-OFDM systems will be discussed. In this approach a plain VBLAST algorithm is used for data -detection. Finally, soft VBLAST-EM based channel estimation for MIMO-OFDM systems is considered. Soft VBLAST algorithm is an improved VBLAST, which takes the error propagation effect into account. IDD (Iterative Detection and Decoding) block is used to further improve the performance of MIMO-OFDM system. Simulation results are also presented
