Optimum Weighting for Adaptive Array Antennas under Spectrum Sharing Environments

We use the method of Lagrange multipliers to derive the optimum weighting for adaptive array antennas in a spectrum-sharing environment. The formula proposed for calculating the weights yields the structure of the special cases of conventional models as described by Frost and Applebaum. An evaluation of performance is given in terms of the signal to interference power ratio and the results are compared with those of a matched filter, a null-space based method, and a linearly constraint adaptive array. We also show the transmit power control based on the residual interference level works well and reveal the relationship between the channel estimation accuracy and achievable channel capacity under the spectrum sharing environments.