Performance evaluation and comparison of fuzzy-based intelligent CAC Systems for wireless cellular networks

The mobile cellular systems are expected to support multiple services with guaranteed Quality of Service(QoS). But, the ability of wireless systems to accommodate expected growth of traffic load and broadband services is limited by available radio frequency spectrum. Call Admission Control (CAC) is one of the resource management functions, which regulates network access to ensure QoS provisioning. However, the decision for CAC is very challenging issue due to user mobility, limited radio spectrum, and multimedia traffic characteristics. To deal with these problems, we implemented a Fuzzy Admission Control System (FACS). We compared the performance of FACS with Shadow Cluster Concept (SCC). In another work, we extended FACS by considering the priority of the on-going connections. We called this system FACS-P. As priority parameter, we considered only one parameter (service request). In this work, we improve our previous system by adding different priorities. We call this system FACS-MP. We evaluate and compare the performance of implemented systems by simulations. From the simulations results, we conclude that the FACS-MP can differentiate better different services compared with previous systems.Peer ReviewedPostprint (published version

A survey of machine learning techniques applied to self organizing cellular networks

In this paper, a survey of the literature of the past fifteen years involving Machine Learning (ML) algorithms applied to self organizing cellular networks is performed. In order for future networks to overcome the current limitations and address the issues of current cellular systems, it is clear that more intelligence needs to be deployed, so that a fully autonomous and flexible network can be enabled. This paper focuses on the learning perspective of Self Organizing Networks (SON) solutions and provides, not only an overview of the most common ML techniques encountered in cellular networks, but also manages to classify each paper in terms of its learning solution, while also giving some examples. The authors also classify each paper in terms of its self-organizing use-case and discuss how each proposed solution performed. In addition, a comparison between the most commonly found ML algorithms in terms of certain SON metrics is performed and general guidelines on when to choose each ML algorithm for each SON function are proposed. Lastly, this work also provides future research directions and new paradigms that the use of more robust and intelligent algorithms, together with data gathered by operators, can bring to the cellular networks domain and fully enable the concept of SON in the near future

A fuzzy-based CAC scheme for wireless cellular networks considering different priorities

The mobile cellular systems are expected to support multiple services with guaranteed Quality of Service(QoS). But, the ability of wireless systems to accommodate expected growth of traffic load and broadband services is limited by available radio frequency spectrum. Call Admission Control (CAC) is one of the resource management functions, which regulates network access to ensure QoS provisioning. However, the decision for CAC is very challenging issue due to user mobility, limited radio spectrum, and multimedia traffic characteristics. In our previous work, we proposed a fuzzy-based CAC system by considering the priority of the on-going connections. As priority parameter, we considered only one parameter (service request). In this work, we extend our work by adding different priorities. We call this system FACS-MP. We evaluate by simulations the performance of the proposed system. From the simulations results, we conclude that the FACS-MP can differentiate better different services compared with previous system.Peer ReviewedPostprint (published version

Call admission control using cell breathing concept for wideband CDMA

This paper presents a Call Admission Control (CAC) algorithm based fuzzy logic to maintain the quality of service using cell breathing concept. When a new call is accepted by a cell, its current user is generally affected due to cell breathing. The proposed CAC algorithm accepts a new call only if the current users in the cell are not jeopardized. Performance evaluation is done for single-cell and multicell scenarios. In multicell scenario dynamic assignment of users to the neighboring cell, so called handoff, has been considered to achieve a lower blocking probability. Handoff and new call requests are assumed with handoff being given preference using a reserved channel scheme. CAC for different types of services are shown which depend upon the bandwidth requirement for voice, data and video. Distance, arrival rate, bandwidth and nonorthogonality factor of the signal are considered for making the call acceptance decision. The paper demonstrates that fuzzy logic with the cell breathing concept can be used to develop a CAC algorithm to achieve a better performance evaluation

Fuzzy-Logic Based Call Admission Control in 5G Cloud Radio Access Networks with Pre-emption

YesFifth generation (5G) cellular networks will be comprised of millions of connected devices like wearable devices, Androids, iPhones, tablets and the Internet of Things (IoT) with a plethora of applications generating requests to the network. The 5G cellular networks need to cope with such sky-rocketing tra c requests from these devices to avoid network congestion. As such, cloud radio access networks (C-RAN) has been considered as a paradigm shift for 5G in which requests from mobile devices are processed in the cloud with shared baseband processing. Despite call admission control (CAC) being one of radio resource management techniques to avoid the network congestion, it has recently been overlooked by the community. The CAC technique in 5G C-RAN has a direct impact on the quality of service (QoS) for individual connections and overall system e ciency. In this paper, a novel Fuzzy-Logic based CAC scheme with pre-emption in C-RAN is proposed. In this scheme, cloud bursting technique is proposed to be used during congestion, where some delay tolerant low-priority connections are pre-empted and outsourced to a public cloud with a penalty charge. Simulation results show that the proposed scheme has low blocking probability below 5%, high throughput, low energy consumption and up to 95% of return on revenue

Implementation and performance evaluation of two fuzzy-based handover systems for wireless cellular networks

Wireless mobile networks and devices are becoming increasingly popular to provide users the access anytime and anywhere. We are witnessing now an unprecedented demand for wireless networks to support both data and real-time multimedia traffic. The wireless mobile systems are based on cellular approach and the area is covered by cells that overlap each other. In mobile cellular systems the handover is a very important process. Many handover algorithms are proposed in the literature. However, to make a better handover and keep the QoS in wireless networks is very difficult task. For this reason, new intelligent algorithms should be implemented to deal with this problem. In this paper, we carried out a comparison study of two handover systems based on fuzzy logic. We implement two Fuzzy-Based Handover Systems (FBHS) called FBHS1 and FBHS2. The performance evaluation via simulations shows that FBHS2 has better behavior than FBHS1 and can avoid ping-pong effect in all simulation cases.Peer ReviewedPostprint (published version

Uncertainty and Congestion Elimination in 4G Network Call Admission Control using Interval Type-2 Intuitionistic Fuzzy Logic

The management and control of the global growth and complex nature of wireless Fourth Generation (4G) Networks elicits the need for Call Admission Control (CAC). However, CAC faces the challenge of network congestion, thereby deteriorating the network Quality of Service (QoS) due to inherent imprecision and uncertainties in the QoS data which leads to difficulties in measuring some objective and constraints of QoS using crisp values. Previous researches have shown the strength of Interval Type-2 Fuzzy Logic System (IT2FLS) in coping adequately with linguistic uncertainties. Intuitionistic fuzzy sets (IFSs) have indicated their ability to further reduce uncertainty by handling conflicting evaluation involving membership (M), nonmembership (NM) and hesitation. This paper applies the Interval Type-2 Intuitionistic Fuzzy Logic System (IT2IFLS) in solving CAC problem in order to achieve a better QoS in 4G Networks