Access point selection in beyond 5G hybrid MmWave/Wi-Fi/Li-Fi network

Nor, Ahmed M.

doi:10.1016/j.phycom.2021.101299

Cited by 14 publications

(9 citation statements)

References 18 publications

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“…This collection represents the most related studies to our work, which are [ 21 , 59 , 60 , 61 , 62 , 63 ]. They all worked on the APA using the FL method similar to the DM method for APA in different hybrid networks.…”

Section: Related Work and Research Gapmentioning

confidence: 99%

A Multicriteria Decision-Making Framework for Access Point Selection in Hybrid LiFi/WiFi Networks Using Integrated AHP–VIKOR Technique

Badeel

Subramaniam

Muhammed

et al. 2023

Sensors

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Since light fidelity (LiFi) and wireless fidelity (WiFi) do not interfere with one another, a LiFi/WiFi hybrid network may provide superior performance to existing wireless options. With many users and constant changes, a network can easily become overloaded, leading to slowdowns and fluctuations in data transfer speeds. Access point assignment (APA) is required with the increase of users, which can negatively impact the system performance and quality-of-service (QoS) due to mobility and line-of-sight (LOS) blockage. Many variables could influence the APA process; these variables are considered as criteria, such as the network capacity, the degree of blockage, the speed of the connected user, etc. Unlike conditional APA methods, recent studies have considered treating these variables as “evaluation criteria”. Considering these criteria can offer better and more accurate results, eventually enhancing the APA process and QoS. However, the variety of these criteria, the conflict amongst them, their weights (importance), and priority have not been addressed so far. Moreover, treating the criteria equally might result in inaccurate outcomes. Therefore, to solve this issue, it is essential to investigate the impact of each criterion on the APA process. In this work, a multicriteria decision-making (MCDM) problem is formulated to determine a network-level selection for each user over a period of time The decision problem is modeled as a hierarchy that fragments a problem into a hierarchy of simple and small subproblems, and the selection of the AP network among various alternatives is a considered as an MCDM problem. Based on the previous works, we are not aware of any previous research attempts using MCDM methods in the LiFi research area for network selection. Therefore, this work proposes an access point assignment framework using an MCDM approach for users in a hybrid LiFi/WiFi network. The experiment was conducted based on four phases: (i) Five criteria were identified and evaluated with eleven APs (alternatives). The outcome of this phase was used to build the decision matrix and an MCDM was developed and built based on user mobility and blockages with various scenarios using all the criteria; (ii) The analytic hierarchy process (AHP) was employed to identify the criterion of the subjective weights of each criterion and to determine the degree of importance supported by experts’ judgement. Determining the weights in the AHP process considered various investigations, including the consistency ratio (CR) and the AHP consensus indicator, which is calculated using the rank-based maximum likelihood method (RGMM) and Shannon entropy techniques. The VIekriteri-Jumsko KOmpromisno Rangiranje (VIKOR) method is adopted in the selection of the optimal AP for the proper selection of whether a LiFi or WiFi AP must serve the users. The integrated AHP–VIKOR was effective for solving the APA and was the best solution based on using weighted criteria simultaneously. Moreover, the ranking outcomes of the developed integrated AHP–VIKOR approach were evaluated using sensitivity analysis. The result of this work takes the APA for hybrid LiFi networks to a new perspective.

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Section: Related Work and Research Gapmentioning

confidence: 99%

A Multicriteria Decision-Making Framework for Access Point Selection in Hybrid LiFi/WiFi Networks Using Integrated AHP–VIKOR Technique

Badeel

Subramaniam

Muhammed

et al. 2023

Sensors

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“…The speed of the UAVs is between 360 and 460 km/h, which results in several communication challenges in the design (Faid et al , 2022). Depending on the degree of mobility, changes in FANET topology are often more significant than the ones that occur in MANET and VANET (Nor, 2021). The failure of application platforms is unaffected by network topology in addition to the mobility of FANET nodes.…”

Section: Problem Statementmentioning

confidence: 99%

Cluster selection for load balancing in flyingad hocnetworks using an optimal low-energy adaptive clustering hierarchy based on optimization approach

Sefati

Halunga

Farkhady

2022

AEAT

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Purpose Flying ad hoc networks (FANETs) have a major effect in various areas such as civil projects and smart cities. The facilities of installation and low cost of unmanned aerial vehicles (UAVs) have created a new challenge for researchers. Cluster head (CH) selection and load balancing between the CH are the most critical issues in the FANETs. For CH selection and load balancing in FANETs, this study used efficient clustering to address both problems and overcome these challenges. This paper aims to propose a novel CH selection and load balancing scheme to solve the low energy consumption and low latency in the FANET system. Design/methodology/approach This paper tried to select the CH and load balancing with the help of low-energy adaptive clustering hierarchy (LEACH) algorithm and bat algorithm (BA). Load balancing and CH selection are NP-hard problems, so the metaheuristic algorithms can be the best answer for these issues. In the LEACH algorithm, UAVs randomly generate numerical, and these numbers are sorted according to those values. To use the load balancing, the threshold of CH has to be considered; if the threshold is less than 0.7, the BA starts working and begins to find new CH according to the emitted pulses. Findings The proposed method compares with three algorithms, called bio-inspired clustering scheme FANETs, Grey wolf optimization and ant colony optimization in the NS3 simulator. The proposed algorithm has a good efficiency with respect to the network lifetime, energy consumption and cluster building time. Originality/value This study aims to extend the UAV group control concepts to include CH selection and load balancing to improve UAV energy consumption and low latency.

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“…The concept of functional split between the control (C) plane and the user (U) plane has been widely adopted for 5G networks in heterogenous network (HetNet) paradigm [ 18 , 19 , 20 , 21 , 22 ], where controlling signals can be guaranteed by a low frequency band due to its wide and robust coverage, e.g., Wi-Fi band, while communication is provided using mmWave band. This HetNet architecture can still be considered the ideal candidate for indoors beyond 5G networks deployment, because a sub 6 GHz band can be used to relax some issues facing multi IRS aided wireless communication systems such as active-passive BF process and IRSs-UEs assignment problems.…”

Section: Introductionmentioning

confidence: 99%

“…Recently, artificial intelligent (AI) techniques have been widely employed in wireless communication system based on users CI for several problems, e.g., association [ 19 ], beam management [ 21 , 23 ], spectrum management, resource allocation [ 24 ], and user positioning [ 25 ], because of their power in solving complicated problems in an energy efficient manner. For example, neural networks (NNs) have used sub-6 GHz measurements as input features to determine the best beam pairs for mmWave transmission [ 11 ].…”

Section: Introductionmentioning

confidence: 99%

Neural Network Based IRSs-UEs Association and IRSs Optimal Placement in Multi IRSs Aided Wireless System

Nor

Halunga

2022

Sensors

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Implementing intelligent reflecting surfaces (IRSs), in high frequency based beyond 5G networks, has become a necessity to overcome the harsh blockage issues that exist in these bands. IRSs can supply user equipment (UEs) with multi alternative virtual line of sight (LOS) links, hence enhancing the spectral efficiency (SE) of the system. As a result of deploying multi IRSs as communication assistants, the step of IRSs-UEs association is required to optimally assign each UE to its best IRS; consideration of the interference between different links is needed, to maximize the system performance. However, this process will be a time and power consuming problem, if conventional schemes, which exhaustively search all possible association patterns to find the optimum one for communication, is adapted. Although iterative search based schemes can reduce this complexity, they still need feedback signaling in real time. Hence, they will be inefficient in terms of power consumption and delay. Moreover, optimal placement of the multi-IRSs in the network, to enlarge the system performance, is still an open issue and needs to be studied. Consequently, in this paper, to handle the IRSs-UEs association problem, we propose a neural network (NN) based scheme using a multi-IRSs aided multi input multi output (MIMO) system. In this system, the estimated angles of arrival (AoAs) of UEs are used as input features for the NN, which is trained to associate each UE to its best IRS based on this information; then, within each IRS, passive beamforming is performed. Adapting this NN in online mode guarantees obtaining better performance while relaxing the complexity of association and increasing response time, giving a performance comparable to the exhaustive and iterative search based schemes. The proposed NN based scheme determines the association pattern without searching or feedback signals. Moreover, the proposed approach maintains the system SE nearly similar to the optimum performance obtained by the conventional scheme. Secondly, a criterion is suggested for optimal deployment of multi IRSs in the network, depending on maximizing the average summation UEs signal-to-interference-plus-noise ratio (SINR). Numerical results prove that this strategy outperforms a reference one, which aims to guarantee certain performance by maximizing minimum UE SINR. In contrast the proposed strategy achieves better system and per UE spectral efficiency.

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Access point selection in beyond 5G hybrid MmWave/Wi-Fi/Li-Fi network

Cited by 14 publications

References 18 publications

A Multicriteria Decision-Making Framework for Access Point Selection in Hybrid LiFi/WiFi Networks Using Integrated AHP–VIKOR Technique

A Multicriteria Decision-Making Framework for Access Point Selection in Hybrid LiFi/WiFi Networks Using Integrated AHP–VIKOR Technique

Cluster selection for load balancing in flyingad hocnetworks using an optimal low-energy adaptive clustering hierarchy based on optimization approach

Neural Network Based IRSs-UEs Association and IRSs Optimal Placement in Multi IRSs Aided Wireless System

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