A new adaptive array algorithm for interference suppression in wireless communications

In the application of antenna arrays to wireless communications, a known signal preamble is used for estimating the array response at the beginning of each data frame. The estimated array response is then used in linear combining the array input for interference suppression and demodulation of the desired user's information data. Since the training preamble is usually very short, the conventional training methods, which estimate the array response based solely on the training preamble, may incur large estimation errors. We propose a subspace-based technique for array response estimation, which exploit the whole frame of the received signal. It is shown that as the length of the data frame tends to infinity, in the absence of noise, this method can recover the array response of the desired user exactly, given a small number of training symbols of that user. We also derive expressions for the subspace-based array combining weights based on zero-forcing and MMSE criteria. Simulation results show that the proposed method offers substantial performance gain over the conventional direct matrix inversion (DMI) method for adaptive arrays. The proposed technique can be readily extended to dispersive channels to combat both co-channel interference (CCI) and intersymbol interference (ISI).