Particle Swarm Optimization Based Multi-Objective User Association for LTE-A Heterogeneous Networks

Summakieh, Mhd Amen; Tan, Chee Keong; Ng, Yin Hoe; El‐Saleh, Ayman A.

doi:10.21203/rs.3.rs-203015/v1

Cited by 2 publications

(3 citation statements)

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“…The updating expressions of LSTM are described in Equations ( 16) to (20). W Fy , W By signifies the weight of forward and backward LSTM.…”

Section: Deep Bidirectional Battle Royale Long Short Term Memory (Dee...mentioning

confidence: 99%

“…Both base stations are highly independent with two dimensional Poisson point process (PPPs) to imprison the irregular network structure. Summakieh et al 20 suggested particle swarm optimization using multiobjective in LTE-HetNet. The suggested multi objective user technique had enhanced the network throughput and network balance index (NBI).…”

Section: Literature Surveymentioning

confidence: 99%

“…Summakieh et al 20 suggested particle swarm optimization using multiobjective in LTE‐HetNet. The suggested multi objective user technique had enhanced the network throughput and network balance index (NBI).…”

Section: Literature Surveymentioning

confidence: 99%

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

Tejasvi

Manjaiah

2022

Trans Emerging Tel Tech

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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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“…The updating expressions of LSTM are described in Equations ( 16) to (20). W Fy , W By signifies the weight of forward and backward LSTM.…”

Section: Deep Bidirectional Battle Royale Long Short Term Memory (Dee...mentioning

confidence: 99%

Section: Literature Surveymentioning

confidence: 99%

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

Tejasvi

Manjaiah

2022

Trans Emerging Tel Tech

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On the usefulness of flying base stations in 5G and beyond scenarios

Cumino,

Luís,

Rosário

et al. 2023

Wireless Netw

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Considering that one of the goals of the future network generations is to provide ubiquitous communication in the most diverse scenarios to achieve high connection coverage, it is foreseen that the use of unmanned aerial vehicles as flying base stations (UAV-BSs) can potentially extend the network and communication range. UAVs as flying base station can bring the potential to assist user devices and vehicles by carrying communication resources that can accommodate clients that were not previously planned by the ground infrastructure design due to flash crowd events, sudden natural disasters, or any other event that let to an overloaded environment. Allocating UAVs as flying base station still poses significant challenges in their deployment and the effectiveness of information transmission through UAVs as flying base station in the context of wireless communication since it is necessary to deal with both wireless communication capability and interference in the presence of terrestrial infrastructures already present. Besides, it is essential to understand how communication resources affect network performance. This paper studies the feasibility of using UAVs as flying base station in the assistance of wireless communication in a scenario where there is a sudden demand for data transmission due to possible congestion of local infrastructure. We show how the number of communication resources provided by the UAV-BS, the interference caused by the presence of multiple next generation node Bs (gNBs), and the UAV as flying base station positioning affect the network performance. We also highlight the need for a better next generation node B (gNB) and UAVs placement criteria since the received signal power prevents the user equipments (UEs) from using most of the available resources.

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Particle Swarm Optimization Based Multi-Objective User Association for LTE-A Heterogeneous Networks

Cited by 2 publications

References 20 publications

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

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

On the usefulness of flying base stations in 5G and beyond scenarios

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