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Optimized Phase Noise Compensation Technique using Neural Network
Objectives: The paper designs a technique to optimize the phase noise compensation in the multiple inputs multiple output orthogonal frequency division multiplexing by using the neural network. Methods/Statistical Analysis: The phase noise compensation in the orthogonal frequency division multiplexing consists of two parts, one is the inter-carrier interference and other is the common phase error. This paper represents a neural network and Jaya algorithm based technique for the estimation of phase noise. The neural network has been used to remove the common phase error while inter-carrier interference has been removed by the Jaya algorithm. Findings: The proposed technique has been compared with three states of art techniques on different block size by using bit error rate. The reduced bit error rate can be identified for each block size. The effectiveness of the technique can be recognized by analyzing the results. Application/Improvements: The proposed technique can be used to facilitate the high data rate with better QoS during transmission.
Artificial Neural Network, Bit Error Rate, Back Propagation, OFDM, Phase Noise Compensation.
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