Energy and spectral efficient resource allocation in 5G HetNet using optimized deep bi‐BRLSTM model

Abstract

The heterogeneous deployment of ultra‐dense femto cell dispenses an enhanced coverage and capacity for the users in the 5G wireless communication system. Due to the substantial growth in wireless data traffic and the inflation of energy consumption, the design of energy and spectrum efficient wireless network is seems to be an extreme concern. Therefore, there is a need to develop an energy and spectrum efficient resource allocation model. The joint contribution of the maximization of energy efficiency (EE) and spectral efficiency (SE) with its constraints is formulated as a multiobjective optimization problem. The resource allocation (RA) issue in the network is handled by the hybrid deep bidirectional battle royale long short term memory (Deep bi‐BRLSTM) model. The loss function in the network model is taken as a consideration to optimize the SE and EE. Fuzzy based energy efficient adaptive atom search optimizer (FEEAAS) is instigated to optimize the trade‐off of EE and SE consecutively. It is embedded with high convergence rate with maximum efficiency which is suitable for power optimization with maximum resource allocation. The performance of the proposed model is implemented in Matlab Simulink platform. The simulation result reveals that the presented model attains an optimal trade‐off between the EE and SE and also improves the overall throughput and delay when compared with existing solutions.

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