The Wireless Systems Are Employed With More Number Of Antennas For Fulfilling The Demand For High Data Rates. In Telecommunication, Lte-A (Long Term EvolutionAdvanced) 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
Block Distributed Compressive Sensing-Based Doubly Selective Channel Estimation and Pilot Design for Large-Scale MIMO Systems
