An Optimal Filter to Reduce BER Utilizing RLS and Firefly
Swati Katwal1, Vinay Bhatia2
1Swati Katwal, Department of Electronics and Communication Engineering, Baddi University of Emerging Sciences and Technology, Makhnumajra, Baddi, Solan (H.P), India.
2Vinay Bhatia, Department of Electronics and Communication Engineering, Chandigarh Engineering College, Landran, Mohali (Punjab), India.
Manuscript received on 02 July 2019 | Revised Manuscript received on 09 July 2019 | Manuscript published on 30 August 2019 | PP: 2550-2556 | Volume-8 Issue-10, August 2019 | Retrieval Number: J10300881019/19©BEIESP | DOI: 10.35940/ijitee.J1030.0881019
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Data communication network suffers due to symbol interference and un-optimized channel response. In recent years faster communication architectures like OFDM were designed to transmit the data as fast as and compatible with modern day communication devices. In order to utilize the channel efficiently, data should be filtered and precise. Swarm Intelligence based recursive least square algorithm has been developed utilizing Extended Firefly Algorithm for the geometric transformation of the data. The optimized filtered data has been cross-verified using Support Vector Machine approach. The permutation matrix of proposed work has been compared with results obtained using Kalman filtering. Results demonstrate that if a filter is designed significantly relative to the single objective function of the optimization algorithm, it generates quite good estimates. The performance of the proposed structure is evaluated using Bit Error Rate and Average Logarithmic Error measures
Index Terms: Data Communication, OFDM, RLS, SVM, SI
Scope of the Article: Distributed Mobile Applications Utilizing IoT