SBIR Phase I: Non-Eigen Decomposition Beamforming for Smart Antenna Systems

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This Small Business Innovation Research (SBIR) Phase I project proposed the development and evaluation of a new class of adaptive interference mitigation techniques via smart antenna beamforming algorithms. Current blind (no user or interference information required) beamforming algorithms require computational complexity too high for many target applications; consequently, the proposed work focuses on a promising new technique for blind beamforming that does not rely on the eigenvalues and eigenvectors utilized by standard algorithms. Current blind interference mitigation research focuses on incrementally improving previous techniques fundamentally limited by unnecessary assumptions and their basis in Eigen Decomposition techniques. This new category of Non-Eigen Decomposition beamforming techniques achieves comparable performance (approaching theoretical maximums for SINR gain) to conventional blind algorithms in nulling interference sources while reducing computational requirements by an order of magnitude or more (order M instead of M2 or M3, where M is the number of antennas). Unlike most conventional techniques, the beamforming weight for this new technique does not require the weight at the previous snapshot because it is only a function of the cross correlation vector and initial guess. When the array autocorrelation matrix is known, the optimal solution is found with zero transition time, resulting in fast convergence and excellent tracking ability. If successful this SBIR Phase I project will have a significant impact on commercial applications and will foster a new field of scientific and technological understanding. By significantly reducing computational requirements for blind beamforming algorithms this work will make it feasible for low-cost commercial applications to eliminate co-channel interference signals despite limited computational resources. Current blind beamforming algorithms cannot be used in many applications due to their heavy computational loads and nonblind algorithms require significant overhead to obtain spatial information for the user and interference sources. If feedback is also required for non-blind beamforming techniques then significant throughput and bandwidth are wasted. Creation of a new class of adaptive blind interference mitigation techniques for smart antenna systems will enhance scientific and technological understanding. Published works over the past decade made incremental advances in blind beamforming algorithms, but those techniques are based on past works and do not have the potential for revolutionary improvements in this research area. Academia and Industry researchers will be able to evaluate the simulations and over-the-air measurement results from this work and adapt these algorithms for their purposes.