Genetic algorithm-based joint Spectral-Energy efficiency optimisation for 5G heterogeneous network.

Carrier Aggregation (CA) technology, introduced in 3GPP release 10, aims at increasing Spectral Efficiency (SE) only, which may lead to huge undesirable circuit power consumption. Hence, not only SE, but also Energy Efficiency (EE), particularly the tradeoff between both the parameters, is crucial in the design of CA systems. In this work, a novel approach, using Genetic Algorithm (GA) is proposed to solve the SE-EE tradeoff problem for a 5 G heterogeneous network with intra-band contiguous Carrier Aggregation (CA). Complete physical layer simulation is performed for generating the CA waveform, with parameters set in accordance with practical deployment scenarios, as specified in 3GPP TS 38.104. Carrier aggregated waveform is generated in 5 G New Radio (NR) frequency band FR1, using frequency bands in India which are currently not allocated for licenced usage. From simulations, it is observed that the proposed technique ensures that neither SE nor EE is seriously degraded for improving the other, for any given value of transmit power. The proposed technique, which performs Multi Objective Optimisation (MOO) using SPEA-2 GA outperforms Single Objective Optimisation (SOO) methods providing a maximum of 37% improvement in SE and 43% improvement in EE. [ABSTRACT FROM AUTHOR]