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Design of Nature Inspired Computing Approach for Estimation of Channel Coefficients in MIMO Networks

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Abstract

In this study, nature inspired computing (NIC) techniques are designed for estimation of channel co-efficients in multi-inputs multi-output (MIMO) networks. NIC methods based on recently introduced variants of swarm intelligence are exploited as optimization mechanism for MIMO channel co-efficients estimation. In MIMO systems there is m input matrix s multiplied with channel matrix H and there is some addition of noise ν and this whole is equivalent to output matrix r. In this research work, the goal is to achieve an optimized channel co-efficient matrix of different orders with the help of various NIC based optimization techniques. Such that MIMO networks give output exactly matching with the information sent by the transmitter. Comparative studies for the parameter estimation of MIMO networks against the true values of the parameters is evaluated by taking different cases, based on variations in the order of channel matrix and SNRs values. Performance analysis of the proposed NIC variants is conducted for single preferred run. NIC computing is done for equal number of antennas on transmitter and receiver end making a square channel matrix H. Four cases are taken in this research work for checking the trend of received signal for noisy channel like rayleigh fading channel. In each case channel estimation is developed by taking channel matrix of orders 2 × 2, 3 × 3, 4 × 4 and 8 × 8. In each case there are five sub cases which are without noise and for different values of SNR such as 70 db, 60 db, 50 db and 40 db.

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Authors and Affiliations

  1. School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an, Shaanxi, China

    Wasiq Ali & Yaan Li

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  1. Wasiq Ali
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  2. Yaan Li
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Correspondence to Wasiq Ali.

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Ali, W., Li, Y. Design of Nature Inspired Computing Approach for Estimation of Channel Coefficients in MIMO Networks. Wireless Pers Commun 107, 2047–2069 (2019). https://doi.org/10.1007/s11277-019-06372-4

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