Adaptive beamforming techniques for mitigating interference in wireless networks

Abstract

In this thesis, a single-input-multiple-output (SIMO) wireless antenna network is investigated in terms of its performance. We analyze the system with regard to the number of receive-transmit antennas (Rx-Tx) and other network parameters such as noise, interferences, channel taps and gain factors. We derive the diversity signal-to-interference-and-noise ratio (SINR) expression initially for each individual Rx and then for the whole system. Afterwards, four distributive adaptive beamforming techniques are proposed and described in detail. Each one uses a different gain selection combining (SC) rule, and we propose one of them as the most efficient, a technique that provides a satisfactory combined SINR (SINRC) with the least number of channel taps used. Then we use detection fundamentals and probability theory to derive an expression for the average probability of signal detection (dP) for asingle Rx. Considering two of our parameters (the channel tap vector and the gain factor) as being random variables (RVs), we perform a double averaging procedure over the two RVs’ probability density functions to derive dPformulas. Two cases are studied followed by their respective dP plots and comparisons. Finally, two modulation techniques are employed, and following the same averaging procedure, we derive bit error ratio (BER) formulas and plot various BER curves. This analysis provides quantitative results with regard to BER improvement techniques.