Techniques for Adaptive Array Beamforming under Non-ideal Environment
Date Issued
2015
Date
2015
Author(s)
Peng, Chien-Lun
Abstract
In many applications of communications, adaptive array beamforming is widely used to improve the output signal to interference and noise ratio (SINR). This technique can suppress interference and noise automatically, in the meanwhile, capture the desired signal. The a priori information of beamforming is the direction of the desired signal, for example linearly constrained minimum variance beamformer (LCMV). The main purpose of this thesis is to solve the degradation of the system performance when the system is under non-ideal environment. This thesis has proposed two robust methods used to improve system performance. First method has modified the architecture of the conventional generalized side-lobe canceller (GSC). It adds two noise block matrics to reduce the influence of mismatch. The second method is to catch the advantage from lots of algorithms, and it also reduces the influence of mismatch. Otherwise, for the non-ideal environments, this thesis discusses steering vector mismatch, mutual coupling effect and coherent environment. The part of steering vector mismatch also separates to three types of model, include: fixed type, random type and additive type. Finally, we will present the simulation results to show the performance of the former proposed methods.
Subjects
Beamforming
Generalized side-lobe canceller (GSC)
Steering vector mismatch
Mutual Coupling Effect
Coherent Environment
Type
thesis
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ntu-104-R02942123-1.pdf
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