Energy Efficient Fractional Particle Swarm Optimization Based Power Allocation in MIMO-NOMA System
Shaik Khaleelahmed1, Nandhanavanam Venkateswararao2
1Shaik Khaleelahmed, ECE department, VR Siddhartha Engineering College, Acharya Ngarjuna University, Andhra Pradesh, India.
2Nandhanavanam Venkateswararao, ECE department, Bapatla Engineering College, Acharya Ngarjuna University, Andhra Pradesh, India.
Manuscript received on 22 August 2019. | Revised Manuscript received on 06 September 2019. | Manuscript published on 30 September 2019. | PP: 1933-1939 | Volume-8 Issue-11, September 2019. | Retrieval Number: K21350981119/2019©BEIESP | DOI: 10.35940/ijitee.K2135.0981119
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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: Non-Orthognal Multiple Access (NOMA) is a key technology used for improving the achievable rate in Multiple Input Multiple Output (MIMO) wireless networks of the next generation. In MIMO-NOMA systems the Energy Efficiency (EE) needs to be improved by a Fractional Particle Swarm Optimization Algorithm (FPSO) based on user ordering. To recommend capable energy and power allocation in the platform efficiently, the proposed optimization algorithm prioritizes the users based on satisfying the quality of service (QoS) and maximum power constraints. The FPSO algorithm prioritizes the users in optimal way by using objective function. The simulated results are analyze using the assessment metrics, like Bit Error Rate (BER), achievable rate, energy and spectral power. The performance of the FPSO-based power allocation approach is showing the higher spectral power, energy, achievable rate are 113.1915dB, 19.4898dB, 81.19153Mbps and lower BER of 0.0000152 respectively. Keywords :
Keywords: MIMO-NOMA, Energy Efficiency, Power Allocation, Fractional Particle Swarm Optimization Algorithm, Quality of Service.
Scope of the Article: Swarm Intelligence