Design and performance analysis of live model of Bessel beamformer for adaptive array system

What is it about?

The objective of our work is to investigate and design adaptive beamforming algorithms in order to improve the performance of wireless cellular technology with spatial domain. For this purpose, blind and non-blind beamforming concepts and related algorithms are investigated which also include Least Mean square (LMS) and Constant Modulus Algorithm (CMA). Both these algorithms suffer from optimization problems like gain enhancement towards desired user, interference rejection, high power transmission, bit error rate (BER), minimization of mean square error (MSE) and rate of convergence which undermines their performance in the application of smart antenna array system. In light of these deficiencies, we analyze initially non-blind technique using LMS and MUSIC algorithms for selection of parameters for further analysis. A new algorithm namely Bessel Least Mean Square (BLMS) is proposed and its performance is then evaluated with LMS in order to determine its efficiency in terms of array gain, MSE, BER and convergence performance based on the chosen parameters. Performance improvement is achieved by proposed algorithm over the conventional LMS algorithm. The improvement in BLMS is attributed by introducing non-uniform step size. This non-uniform step size is obtained from the interaction of Bessel and step size functions. The Bessel function of the first kind has inherent monotonically decreasing property which generates coefficients equal to the number of elements that helps the proposed BLMS algorithm in convergence effectively as compared to LMS algorithm that is based on constant step size.

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Why is it important?

Further, the analysis of blind technique using CMA and MUSIC algorithms has similarly been investigated for the same selected parameters as above. For blind beamforming, novel algorithms named as Kaiser Constant Modulus Algorithm (KCMA) and Hamming CMA (HAMCMA) using window techniques are proposed and implemented. Their performance is then compared with CMA in terms of array gain, MSE and BER. The KCMA has shown improved performance where this improvement in KCMA is justified in terms of facilitating independent control of the main lobe width and ripple ratio. The HAMCMA, based on fixed type window function has shown better results in terms of array gain and sidelobe level (SLL) but lacks in BER performance as compared to CMA. The reduction in SLL by these blind beamforming algorithms signifies that using the proposed methods the interferences are very low. Finally, BLMS with Automatic Gain Control (AGC) is proposed to make it variable step size algorithm which can update itself from signal array vector. The live model of BLMS is also developed. The performance is tested for its efficiency in terms of signal recovery, directive gain by minimizing MSE using the “wavrecord” function to bring live audio data in WAV format into the MATLAB workspace and compared with live model of LMS in terms of gain and MSE. From the results obtained in the thesis, it has been concluded that the proposed algorithms lead to improve in performance with the LMS and CMA algorithms and can be utilized efficiently for further enhancement of wireless cellular technology.

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