Space-time coding and orthogonal frequency division multiplexing in cooperative wireless relays

This thesis examines a number of issues in mobile wireless communications. Small scale fading is a key factor that limits the system performance if the channel state varies too fast to be known to the transmitter. One way to overcome this problem is to exploit the diversity of antennas when a transmitter and/or receiver carries multiple antennas. However, many practical wireless devices are so small that multiple antennas are not practical. In this case, virtual antenna diversity can be obtained via cooperative schemes for distributed relaying nodes. In this thesis, two cooperative schemes are considered. One is non-regenerative, and the other is regenerative. For the non-regenerative scheme, space-time block coding is applied to raw symbols received at the relays. The impact of both large scale fading and small scale fading on the non-regenerative scheme is analyzed, and a significant power saving is observed. For the regenerative scheme, space-time block coding is applied to the reconstructed noiseless symbols at the relays. A significant power saving is also observed in the regenerative case.; Synchronization is important for all cooperative schemes. A simple method utilizing space-time block coding is shown to be very effective to reduce the impact of synchronization errors. Two space-time block codes are considered: time-reverse space-time code, and orthogonal frequency division multiplexing (OFDM) space-time code.; In OFDM systems, unknown frequency offset could destroy the orthogonality among OFDM sub-carriers, and hence cause serious performance degradation. Methods for frequency offset estimation are revisited in this thesis, which include both blind methods and non-blind methods. All methods are extended to the case of fractionally sampled data. The impact of fractional sampling on all these methods is studied.; Finally, the thesis examines a robust version of the zero-forcing equalizer and the minimum mean squared error equalizer. The robust equalizers are designed to minimize the symbol errors in the worse case of channel state information. However, the robust equalizers do not reduce the symbol errors averaged over a set of channel state information.