LLMS adaptive beamforming algorithm implemented with finite precision
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This paper studies the influence of the use of finite wordlength on the operation of the LLMS adaptive beamforming algorithm. The convergence behavior of LLMS algorithm, based on the minimum mean square error (MSE), is analyzed for operation with finite precision. Computer simulation results verify that a wordlength of eight bits is sufficient for the LLMS algorithm to achieve performance close to that provided by full precision. Based on the simulation results, it is shown that the LLMS algorithm outperforms least mean square (LMS) in addition to other earlier algorithms, such as, modified robust variable step size (MRVSS) and constrained stability LMS (CSLMS).
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Adaptive antenna array beamforming using a concatenation of recursive least square and least mean square algorithmsSrar, Jalal Abdulsayed (2011)In recent years, adaptive or smart antennas have become a key component for various wireless applications, such as radar, sonar and cellular mobile communications including worldwide interoperability for microwave ...
Srar, Jalal; Chung, Kah-Seng; Mansour, Ali (2010)A new adaptive algorithm, called least mean square- least mean square (LLMS) algorithm, which employs an array image factor, , sandwiched in between two least mean square (LMS) algorithm sections, is proposed for different ...
Srar, Jalal Abdulsayed; Chung, Kah-Seng; Mansour, Ali (2010)A new adaptive algorithm, called LLMS, which employs an array image factor, AI, sandwiched in between two Least Mean Square (LMS) sections, is proposed for different applications of array beamforming. The convergence of ...