Heterogeneous network selection algorithm for novel 5G services based on evolutionary game

Ma, Mingfang; Zhu, Anqi; Guo, Songtao; Wang, Xiaoqian; Liu, Bei; Su, Xin

doi:10.1049/iet-com.2018.6290

Cited by 8 publications

(2 citation statements)

References 41 publications

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“…To attain stable association, characteristic preference functions have been defined for both IoT devices and RATs that ensure improved energy efficiency, while respecting the RAT’s capacity and reduced cost of connectivity in an autonomic IoT environment. Authors in [ 8 ], leveraged the concept of evolutionary game theory to select a suitable network that ensures load balancing in 5G heterogeneous network. An enhanced network load balancing is achieved with a utility function defined as an aggregate function of available network capacity and parameters.…”

Section: Related Workmentioning

confidence: 99%

iMnet: Intelligent RAT Selection Framework for 5G Enabled IoMT Network

Priya¹,

Malhotra²

2022

Wireless Pers Commun

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The COVID-19 outburst has encouraged the adoption of Internet of Medical Things (IoMT) network to empower the antiquated healthcare system and alleviate the health care costs. To realise the functionalities of the IoMT network, 5G heterogeneous networks emerged as an exemplary connectivity solution as it facilitates diversified service provisioning in the service delivery model at more convenient care. However, the crucial challenge for 5G heterogeneous wireless connectivity solution is to facilitate agile differentiated service provisioning. Lately, considerable research endeavour has been noted in this direction but multiservice consideration and battery optimisation have not been addressed. Motivated by the gaps in the existing literature, an intelligent radio access technology selection approach has been proposed to ensure Quality of Service provisioning in a multiservice scenario on the premise of battery optimisation. In particular, the proposed approach leverages the concept of Double Deep Reinforcement Learning to attain an optimal network selection policy. Eventually, the proposed approach corroborated by the rigorous simulations demonstrated a substantial improvement in the overall system utility. Subsequently, the performance evaluation underlines the efficacy of the proposed scheme in terms of convergence and complexity.

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Section: Related Workmentioning

confidence: 99%

iMnet: Intelligent RAT Selection Framework for 5G Enabled IoMT Network

Priya¹,

Malhotra²

2022

Wireless Pers Commun

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“…With the development of artificial intelligence and communication technologies, the global mobile data traffic is expected to reach 77 exabytes per month by 2022 [1][2][3]. To meet these demands, various technologies have been proposed, such as full duplex (FD), millimetre wave (mmWave) communication, massive multiple-input multiple-output (MIMO), ultra-dense network (UDN), and intelligent reflecting surface (IRS) [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Joint active and passive beamforming optimization for multigroup multicast system aided by intelligent reflecting surface

2021

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An intelligent‐reflecting‐surface aided multigroup multicast communication system is investigated in this paper. We develop energy‐efficient designs for both the precoding matrix at the base station and passive reflecting beamforming at intelligent‐reflecting‐surface, subject to the minimum signal‐to‐interference‐plus‐noise ratio constraint of each user and the unit‐modulus constraint imposed by passive intelligent‐reflecting‐surface. This leads to a complex non‐convex problem for which to tackle we propose two novel algorithms based on alternating optimization techniques. Specifically, one algorithm employs semi‐definite relaxation to obtain the suboptimal reflection coefficient vector and suboptimal precoding vector for each group. In order to reduce the computational complexity, the second algorithm transforms this non‐convex problem into two second‐order cone programming problems. Numerical results show that intelligent‐reflecting‐surface can significantly reduce the power consumption of the base station.

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iRSL: Intelligent RAT selection framework for beyond 5G networks

Priya,

Malhotra

2023

Multimed Tools Appl

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Heterogeneous network selection algorithm for novel 5G services based on evolutionary game

Cited by 8 publications

References 41 publications

iMnet: Intelligent RAT Selection Framework for 5G Enabled IoMT Network

iMnet: Intelligent RAT Selection Framework for 5G Enabled IoMT Network

Joint active and passive beamforming optimization for multigroup multicast system aided by intelligent reflecting surface

iRSL: Intelligent RAT selection framework for beyond 5G networks

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