Allocation of power in NOMA based 6G-enabled internet of things using multi-objective based genetic algorithm

Saraswat, Shelesh Krishna; Deolia, Vinay Kumar; Shukla, Aasheesh

doi:10.2478/jee-2023-0012

Abstract

Sixth generation (6G)-enabled internet of things (IoT) requires significant spectrum resources to deliver spectrum availability for massive IoT’s nodes. But the existing orthogonal multiple access limits the full utilization of limited spectrum resources. The non-orthogonal multiple access (NOMA) exploits the potential of power domain to improve the connectivity for 6G-enabled IoT. An efficient quality of service (QoS) aware power allocation approach is required to enhance the spectral efficiency and energy of NOMA based 6G-enabled IoT nodes. The multi-objective genetic algorithm (MOGA) is used to resolve the non-convex problem by considering the successive interference cancellation (SIC), QoS, and transmission power. Extensive experiments are drawn by using the Monte Carlo simulation to evaluate the significant improvement of the proposed model. Experimental results indicate that the proposed power allocation model provides good performance of the NOMA based IoT network.

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Allocation of power in NOMA based 6G-enabled internet of things using multi-objective based genetic algorithm

Abstract

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