Modern wireless transceivers use multiple transmit and/or receive antennas, higher order modulation and large bandwidth to satisfy the high data rate requirements of voice, data and multimedia applications. As wireless systems become more complex, the need to make wireless transceivers more efficient, compact and cost effective becomes challenging. It is partly due to the impairments resulting from imperfections in analog radio frequency (RF) components that reduce the efficiency of wireless transceivers. Two of the most common impairments that significantly limit the performance of wireless transceivers are in phase and quadrature (IQ) imbalance and phase noise. These are caused by the mismatch in oscillator output and random frequency fluctuations at the I and Q branches of IQ transceivers, respectively. Low-complexity estimation and compensation techniques that can jointly remove the effect of these impairments are highly desirable.
The degrading effect of RF impairments is more pronounced in multi-input-multi-output orthogonal frequency division multiplexing (MIMO-OFDM) systems. As many of the modern and future wireless systems employ MIMO-OFDM, studying the effect of and addressing the techniques to mitigate RF impairments in these systems are essential to meet the stringent requirements of modern wireless applications.
In this thesis, a simple joint estimation and compensation technique to estimate multi-path channel, phase noise and IQ-Imbalance parameters in MIMO-OFDM systems under slow fading is proposed. A subcarrier multiplexed (SM) preamble structure to estimate the channel and impairment parameters with minimum overhead is introduced and used in the estimation of IQ-Imbalance parameters as well as the initial estimation of effective channel matrix including common phase error (CPE). We then use a novel tracking method based on the second order statistics of the inter-carrier interference (ICI) and noise to update the effective channel matrix throughout an OFDM frame. Simulation results for a variety of scenarios show that the proposed low-complexity estimation and compensation technique can efficiently improve the performance of MIMO-OFDM systems in terms of bit-error-rate (BER).