Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  presents and investigates a simple constrained based adaptive null steering algorithm. In the environment where the desired signal is stronger or not significantly aker than the interferences, nulling in the direction of interest becomes a problem for conventional zero tracking algorithm. With the proposed algorithm in this paper, the null positions can be selectively tracked one after another without affecting other null positions so that the interference signals can be rejected while the desired signal preserves. The main advantage of the proposed algorithm is its simplicity. When compared with conventional LMS based Linear Constrained Minimum Variance (LCMV) beamforming algorithm, the proposed method converges in a faster manner; and compared with QR-RLS based Minimum Variance Distortionless Response (MVDR) beamformer, the proposed algorithm has lor complexity. Furthermore, due to its cascade configuration, the steering vector error problem can be resolved by using the new method.
['S. Leng', 'Wee Ser', 'Chi Chung Ko']
I am writing a research paper on a idea A simple constrained based adaptive null steering algorithm
[{"from": "human", "value": "I am writing a research paper on a idea A simple constrained based adaptive null steering algorithm"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  presents and investigates a simple constrained based adaptive null steering algorithm. In the environment where the desired signal is stronger or not significantly aker than the interferences, nulling in the direction of interest becomes a problem for conventional zero tracking algorithm. With the proposed algorithm in this paper, the null positions can be selectively tracked one after another without affecting other null positions so that the interference signals can be rejected while the desired signal preserves. The main advantage of the proposed algorithm is its simplicity. When compared with conventional LMS based Linear Constrained Minimum Variance (LCMV) beamforming algorithm, the proposed method converges in a faster manner; and compared with QR-RLS based Minimum Variance Distortionless Response (MVDR) beamformer, the proposed algorithm has lor complexity. Furthermore, due to its cascade configuration, the steering vector error problem can be resolved by using the new method."}]