An Optimal Receive Antenna Selection Algorithm using GA in MIMO Communication System 
Sasmita Padhy1, Satya Narayan Tripathy2, Sisira Kumar Kapat3, Susanta Kumar Das4
1Dr. Sasmita Padhy*, Associate professor, Department of CSE, Vignan Institute of Technology and Management, Berhampur, Ganjam, Odisha.
2Dr. Satya Narayan Tripathy, Assistant Proffessor, Department of Computer Science, Berhampur University, Odisha.
3Er. Sisira Kumar Kapat, Lecturer, Department of CSE/IT, Uma Charan Patnaik Engineering School, Berhampur, Odisha.
4Dr. Susanta Kumar Das , Reader, Department of Berhampur University, Odisha.
Manuscript received on February 10, 2020. | Revised Manuscript received on February 23, 2020. | Manuscript published on March 10, 2020. | PP: 630-633 | Volume-9 Issue-5, March 2020. | Retrieval Number: E2502039520/2020©BEIESP | DOI: 10.35940/ijitee.E2502.039520
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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: MIMO technology offers large improvements in data transfer and connection range no bandwidth extra or processing potential in wireless communication,. Multiple transmitters and receivers are used to simultaneously transfer enormous amounts of data. Using many antennas transmitting and receiving, efficiency can be enhanced for wireless communication systems operating in fading environments. But the key downside in the new MIMO scheme, due to multiple Radio Frequency chains, is increased complexity and high cost. A daunting incentive is the development of techniques to reduce hardware and computing costs of the systems with a huge amount of antennas. The optimum selection of the receiver antenna subset is a very effective approach to achieving this goal. Genetic algorithm is used in this paper to choose the receivers from the available set of antennas that would then be compared with an existing receiving antenna selection process.
Keywords: Antenna selection, MIMO System, Channel capacity, Cost, Complexity, Genetic Algorithm.
Scope of the Article: Parallel and Distributed Algorithms