Hybrid spectrum management using integrated fuzzy and femtocells in cognitive domain

2021 ◽  
pp. 1-10
Author(s):  
K. Revathy ◽  
K. Thenmozhi ◽  
Padmapriya Praveenkumar ◽  
Rengarajan Amirtharajanr
Keyword(s):  
Service Providers ◽  
Spectrum Management ◽  
Cognitive Domain ◽  
Critical Conditions ◽  
Management Technique ◽  
Femtocell Networks ◽  
Inference System ◽  
Access Points ◽  
Indoor Coverage ◽  
Cognitive Femtocell

In Today’s pandemic situation, ‘Spectrum accessing and smart usage’ is the sacred Mantra uttered by every individual citizen in the world. Work from home for techies, online classes for students, games for kids, webinar for teaching fraternity etc., are going almost on indoor coverage without any limit in pace because of the smart spectrum coverage by the network service providers. This paper provides an add-on facility to the existing wireless infrastructure to provide a better user experience in this highly regrettable routine. In this paper, a cognitive domain unused spectrum holes are efficiently handled by (i) adaptive spectrum management technique; (ii) Fuzzy Inference System based spectrum administration and (iii) Hybrid Cognitive Femtocell approaches based on the user demand and their applications. The proposed integrated cognitive femtocell and Fuzzy-based approach reduces the indoor coverage problems and enhances the throughput of the macrocell users by allowing adaptive spectrum management based on the demand, thereby eliminating spectrum underlay and overlay problems during critical conditions. In cognitive femtocell networks, the access points are prepared and installed with Cognitive Radio which can determine spectrum dynamically by macrocells and nearby Femto Access Points. It adjusts its radiating parameters to evade the macrocells’ interferences and the neighbouring femtocells, thereby maximising the spectrum band’s overall utility.

Femtocell Selection Scheme for Reducing Unnecessary Handover and Enhancing Downlink QoS in Cognitive Femtocell Networks

2017 ◽  
Author(s):  
Hoang Nhu Dong ◽  
Hoang Nam Nguyen ◽  
Hoang Trong Minh ◽  
Takahiko Saba
Keyword(s):  
Cellular Networks ◽  
Estimation Methods ◽  
Mobility Prediction ◽  
Capacity Estimation ◽  
Femtocell Networks ◽  
Selection Scheme ◽  
Indoor Communications ◽  
Performance Results ◽  
Cognitive Femtocell

Femtocell networks have been proposed for indoor communications as the extension of cellular networks for enhancing coverage performance. Because femtocells have small coverage radius, typically from 15 to 30 meters, a femtocell user (FU) walking at low speed can still make several femtocell-to-femtocell handovers during its connection. When performing a femtocell-to-femtocell handover, femtocell selection used to select the target handover femtocell has to be able not only to reduce unnecessary handovers and but also to support FU’s quality of service (QoS). In the paper, we propose a femtocell selection scheme for femtocell-tofemtocell handover, named Mobility Prediction and Capacity Estimation based scheme (MPCE-based scheme), which has the advantages of the mobility prediction and femtocell’s available capacity estimation methods. Performance results obtained by computer simulation show that the proposed MPCE-based scheme can reduce unnecessary femtocell-tofemtocell handovers, maintain low data delay and improve the throughput of femtocell users. DOI: 10.32913/rd-ict.vol3.no14.536

scholarly journals Estimating PQoS of Video Streaming on Wi-Fi Networks Using Machine Learning

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 621
Author(s):  
Maghsoud Morshedi ◽  
Josef Noll
Keyword(s):  
Machine Learning ◽  
Video Streaming ◽  
Network Performance ◽  
Service Providers ◽  
Perceived Quality ◽  
Internet Service Providers ◽  
Performance Parameters ◽  
Internet Service ◽  
Access Points

Video on demand (VoD) services such as YouTube have generated considerable volumes of Internet traffic in homes and buildings in recent years. While Internet service providers deploy fiber and recent wireless technologies such as 802.11ax to support high bandwidth requirement, the best-effort nature of 802.11 networks and variable wireless medium conditions hinder users from experiencing maximum quality during video streaming. Hence, Internet service providers (ISPs) have an interest in monitoring the perceived quality of service (PQoS) in customer premises in order to avoid customer dissatisfaction and churn. Since existing approaches for estimating PQoS or quality of experience (QoE) requires external measurement of generic network performance parameters, this paper presents a novel approach to estimate the PQoS of video streaming using only 802.11 specific network performance parameters collected from wireless access points. This study produced datasets comprising 802.11n/ac/ax specific network performance parameters labelled with PQoS in the form of mean opinion scores (MOS) to train machine learning algorithms. As a result, we achieved as many as 93–99% classification accuracy in estimating PQoS by monitoring only 802.11 parameters on off-the-shelf Wi-Fi access points. Furthermore, the 802.11 parameters used in the machine learning model were analyzed to identify the cause of quality degradation detected on the Wi-Fi networks. Finally, ISPs can utilize the results of this study to provide predictable and measurable wireless quality by implementing non-intrusive monitoring of customers’ perceived quality. In addition, this approach reduces customers’ privacy concerns while reducing the operational cost of analytics for ISPs.

scholarly journals Efficiency Evaluation for Femtocell Spectrum Access in LTE-Advanced

2015 ◽  
Vol 1 (1) ◽  
pp. 96-111
Author(s):  
Omar Arafat ◽  
Mark A Gregory
Keyword(s):  
Performance Analysis ◽  
Low Cost ◽  
Limited Area ◽  
Femtocell Networks ◽  
Indoor Coverage ◽  
Lte Advanced ◽  
Femtocell Network ◽  
Increasing Demand ◽  
Resource Allocation Scheme

Femtocells are considered one of the ultimate solutions for the ever increasing demand in LTE-Advance. Recently, wireless industries have resorted to femtocell networks in order to enhance indoor coverage and quality of service since macro-antennas fail to reach these objectives. In enabling indoor home or enterprise users with mobile broadband solutions, role of femtocells are crucially important. While considering low cost solutions for higher coverage and data rate, femtocells apparently have one of the best potentials for indoor users. Due to the dense self-deployment of femtocells in a limited area, serious inter-femtocell interference (IFI) may cause, which consequently results in severe performance degradation. To mitigate the IFI and utilize spectrum resource more efficiently, this paper proposes a cluster based femtocell deployments along with a capacity based cognitive resource allocation scheme .Three different channel configurations in a hybrid access femtocell network are considered for performance analysis. The results of a performance analysis of the cluster based femtocell configurations in a priority based users’ network are presented.

Spectrum Handover Strategies for Cognitive Femtocell Networks

2012 ◽  
pp. 85-102 ◽  
Author(s):  
Saba Al-Rubaye ◽  
Anwer Al-Dulaimi ◽  
John Cosmas
Keyword(s):  
Base Stations ◽  
Handover Management ◽  
Spectrum Utilization ◽  
Femtocell Networks ◽  
Data Rates ◽  
Switching Unit ◽  
Geographical Cluster ◽  
Service Coordinator ◽  
Cognitive Femtocell

Cognitive femtocell is a promising technology for the next generation wireless networks to improve the efficiency of spectrum utilization, coverage, and to attain higher data rates for indoor communications. In this chapter, the new Cognitive Femtocell Switching Unit (CFSU) is proposed to support handover management for 10-20 cognitive femtocells as a local geographical cluster. Thus, CFSU acts as a service coordinator between femtocells and macrocell areas to improve spectrum utilization and coexistence. Then, the chapter presents solutions for spectrum handover to achieve guaranteed quality of radio service, spectrum utilization, and enable an excellent local handover management to reduce unnecessary handovers between femtocell base stations. The challenges and solutions that are presented in this chapter have the ability to maintain services by evaluating the requested quality of services.

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