| Summary: | 碩士 === 國立臺灣科技大學 === 電子工程系 === 93 === Adaptive beamforming, which can dynamically adjust its beampattern to
enhance the desired signal and null out or reduce the interferences, is of importance in various disciplines of signal processing applications. In this thesis, we focus on that the inherent setback of subband generalized sidelobe canceller (GSC), as the traditional GSC, is the nonzero error signal, which consists of both the desireed
signal and the noise signal, in the output of the GSC. In addition, the practically imperfect subband decomposition also increases this error signal due to the aliasing between subbands. Such a nonzero error signal will retaliate the convergence rate of GSC.
To alleviate this shortcoming, the thesis proposes a decision feedback subband GSC, in which the design of the statistically optimum filter bank decomposition of the signals passing through the lower branch of the GSC as well as the signal after the decision feedback based on the minimum mean-square error criterion is addressed. The new beamformer not only renders superior interference cancellation capability, but also possesses a fast convergence rate due to the subband processing scheme and the removal of the desired signal subband component in the output of the GSC via the decision feedback. Furthermore, to mitigate the computational overhead in the determination of the subband filter coefficients, an iterative procedure is also addressed.
To provide further insights into the proposed approach, the analytic expressions of the output signal-to-interference-plus-noise ratio (SINR) of the decision feedback subband GSC is derived. The convergence behavior of the proposed beamformer is analyzed as well to justify the advantages of the new scheme. Furnished simulations show that the proposed beamformer can yield superior performance
with faster convergence characteristics compated with previous works.
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