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The capability of adaptive antenna array lies in forming higher gain in the user directions and lower gain in the interferer directions. The technique used to produce such radiation pattern by calculating the excitation weights are called the adaptive beamforming techniques. It tries to minimize the error between the desired and actual signal and maximize the signal to noise ratio (SNR). But in severe interference environment when the actual signal is weak, the effect of SNR on the radiation pattern needs to be considered. This paper describes the effect of SNR on different adaptive beamforming techniques such as non-blind Least mean Square (LMS), blind Constant Modulus Algorithm (CMA) and evolutionary Particle Swarm Optimization (PSO). The performance and validation of beamforming algorithms are studied through MATLAB simulation by varying SNR parameter for different desired and interference direction. Different weights are obtained using this beamforming algorithm to optimize the radiation pattern. The parameters for comparison are the main beam and null placement for different angles of user and interferer. The mean SLL and directivity are also studied.
Ved Vyas Dwivedi. 2017. \u201cEffect of Signal to Noise Ratio on Adaptive Beamforming Techniques\u201d. Global Journal of Research in Engineering - J: General Engineering GJRE-J Volume 17 (GJRE Volume 17 Issue J2): .
Crossref Journal DOI 10.17406/gjre
Print ISSN 0975-5861
e-ISSN 2249-4596
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Total Score: 102
Country: India
Subject: Global Journal of Research in Engineering - J: General Engineering
Authors: Smita Banerjee, Ved Vyas Dwivedi (PhD/Dr. count: 0)
View Count (all-time): 244
Total Views (Real + Logic): 3487
Total Downloads (simulated): 1743
Publish Date: 2017 08, Thu
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The capability of adaptive antenna array lies in forming higher gain in the user directions and lower gain in the interferer directions. The technique used to produce such radiation pattern by calculating the excitation weights are called the adaptive beamforming techniques. It tries to minimize the error between the desired and actual signal and maximize the signal to noise ratio (SNR). But in severe interference environment when the actual signal is weak, the effect of SNR on the radiation pattern needs to be considered. This paper describes the effect of SNR on different adaptive beamforming techniques such as non-blind Least mean Square (LMS), blind Constant Modulus Algorithm (CMA) and evolutionary Particle Swarm Optimization (PSO). The performance and validation of beamforming algorithms are studied through MATLAB simulation by varying SNR parameter for different desired and interference direction. Different weights are obtained using this beamforming algorithm to optimize the radiation pattern. The parameters for comparison are the main beam and null placement for different angles of user and interferer. The mean SLL and directivity are also studied.
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