GWO Based Optimal Channel Estimation Technique for Large Scale Mimo in LTE Network
Rajashree A. Patil1, P. Kavipriya2, B. P. Patil3
1Rajashree A. Patil, Ph.D. Scholar, Electronics Dept., Sathyabama Institute of Science & Technology, Chennai Asst. Professor, Dept of E&TC, Army Institute of Technology, Pune, India.
2P. Kavipriya, Associate Professor. Dept. of ECE, Sathyabama Institute of Science & Technology, Chennai, India.
3B. P. Patil, Principal, Army Institute of Technology, Pune, India.
Manuscript received on September 16, 2019. | Revised Manuscript received on 24 September, 2019. | Manuscript published on October 10, 2019. | PP: 5306-5314 | Volume-8 Issue-12, October 2019. | Retrieval Number: L37331081219/2019©BEIESP | DOI: 10.35940/ijitee.L3733.1081219
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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: The Wireless Systems Are Employed With More Number Of Antennas For Fulfilling The Demand For High Data Rates. In Telecommunication, Lte-A (Long Term Evolution Advanced) Is A Well-Known Technology Intended For Wireless Broadband Communication Aimed At Data Terminals And Mobile Devices. Multiple Input Multiple Output (Mimo) Technology Is Used By Lte Which Is Also Known As Fourth Generation Mobile Networks To Attain Very High Data Rates In Downlink And Uplink Channels. Though The Mimo Systems In Massive Mimo Are Provided By Multiple Antennas, The Design Of The Appropriate Non-Erroneous Detection Algorithm Is A Major Challenge. Also, With The Increase In Quantity Of Antennas, The System’s Spectral Efficiency Begins To Degrade. So As To Deal With This Issue, A Proper Algorithm Has To Be Utilized For Channel Estimation. The Bio Inspired Algorithms Have Shown Potential In Handling These Issues In Communication And Signal Processing. So, Grey Wolf Optimization (Gwo) Algorithm Is Used In This Approach To Estimate The Most Optimal Communication Channel. Also, The Spectral Efficiency And Data Capacity Are Enhanced Using The Presented Approach. The Proposed Approach’s Performance Is Compared With The Existing Approaches. The Simulation Result Exposes That The Presented Channel Estimation Approach Is Far Better Than Existing Channel Estimation Approaches In Performance Metrics Such As Bit Error Rate, Minimum Delay, Papr, Spectral Efficiency, Uplink Throughput, Downlink Throughput And Mean-Squared-Error.
Keywords: Channel Estimation, Large Scale MIMO, LTE, Channel Matrix, Wireless Communication, Antenna, Grey Wolf Optimization, Mean-Squared-Error and Spectral Efficiency.
Scope of the Article: Communication