Efficient radio resource management in next generation wireless networks

The current decade has witnessed a phenomenal growth in mobile wireless communication networks and subscribers. In 2015, mobile wireless devices and connections were reported to have grown to about 7.9 billion, exceeding human population. The explosive growth in mobile wireless communication network subscribers has created a huge demand for wireless network capacity, ubiquitous wireless network coverage, and enhanced Quality of Service (QoS). These demands have led to several challenging problems for wireless communication networks operators and designers. The Next Generation Wireless Networks (NGWNs) will support high mobility communications, such as communication in high-speed rails. Mobile users in such high mobility environment demand reliable QoS, however, such users are plagued with a poor signal-tonoise ratio, due to the high vehicular penetration loss, increased transmission outage and handover information overhead, leading to poor QoS provisioning for the networks' mobile users. Providing a reliable QoS for high mobility users remains one of the unique challenges for NGWNs. The increased wireless network capacity and coverage of NGWNs means that mobile communication users at the cell-edge should have enhanced network performance. However, due to path loss (path attenuation), interference, and radio background noise, mobile communication users at the cell-edge can experience relatively poor transmission channel qualities and subsequently forced to transmit at a low bit transmission rate, even when the wireless communication networks can support high bit transmission rate. Furthermore, the NGWNs are envisioned to be Heterogeneous Wireless Networks (HWNs). The NGWNs are going to be the integration platform of diverse homogeneous wireless communication networks for a convergent wireless communication network. The HWNs support single and multiple calls (group calls), simultaneously. Decision making is an integral core of radio resource management. One crucial decision making in HWNs is network selection. Network selection addresses the problem of how to select the best available access network for a given network user connection. For the integrated platform of HWNs to be truly seamless and efficient, a robust and stable wireless access network selection algorithm is needed. To meet these challenges for the different mobile wireless communication network users, the NGWNs will have to provide a great leap in wireless network capacity, coverage, QoS, and radio resource utilization. Moving wireless communication networks (mobile hotspots) have been proposed as a solution to providing reliable QoS to high mobility users. In this thesis, an Adaptive Thinning Mobility Aware (ATMA) Call Admission Control (CAC) algorithm for improving the QoS and radio resource utilization of the mobile hotspot networks, which are of critical importance for communicating nodes in moving wireless networks is proposed. The performance of proposed ATMA CAC scheme is investigated and compare it with the traditional CAC scheme. The ATMA scheme exploits the mobility events in the highspeed mobility communication environment and the calls (new and handoff calls) generation pattern to enhance the QoS (new call blocking and handoff call dropping probabilities) of the mobile users. The numbers of new and handoff calls in wireless communication networks are dynamic random processes that can be effectively modeled by the Continuous Furthermore, the NGWNs are envisioned to be Heterogeneous Wireless Networks (HWNs). The NGWNs are going to be the integration platform of diverse homogeneous wireless communication networks for a convergent wireless communication network. The HWNs support single and multiple calls (group calls), simultaneously. Decision making is an integral core of radio resource management. One crucial decision making in HWNs is network selection. Network selection addresses the problem of how to select the best available access network for a given network user connection. For the integrated platform of HWNs to be truly seamless and efficient, a robust and stable wireless access network selection algorithm is needed. To meet these challenges for the different mobile wireless communication network users, the NGWNs will have to provide a great leap in wireless network capacity, coverage, QoS, and radio resource utilization. Moving wireless communication networks (mobile hotspots) have been proposed as a solution to providing reliable QoS to high mobility users. In this thesis, an Adaptive Thinning Mobility Aware (ATMA) Call Admission Control (CAC) algorithm for improving the QoS and radio resource utilization of the mobile hotspot networks, which are of critical importance for communicating nodes in moving wireless networks is proposed

The Design and Implementation of an Over-the-top Cloud-based Vertical Handover Decision Service for Heterogeneous Wireless Networks

The widespread availability of heterogeneous wireless networks (hetnets) presents a resource allocation challenge to network operators and administrators. Overlapping network coverage should be utilized to its fullest extent, providing users with a fair share of bandwidth while maximizing the efficient use of the operator\u27s resources. Currently, network selection occurs locally at the mobile device and does not take into account factors such as the state of other networks that might be available in the device\u27s location. The local decision made by the device can often result in underutilization of network resources and a degraded user experience. This type of selfish network selection might not result in optimal bandwidth allocation when compared to approaches that make use of a centralized resource controller \cite{gpf}. The decision making process behind the selection of these networks continues to be an open area of research, and a variety of algorithms have been proposed to solve this problem. An over-the-top handover decision service treats each wireless access network in a hetnet as a black box, assuming detailed network topology and state information is unavailable to the handover decision algorithm. The algorithm then uses network data gathered empirically from users to provide them with a network selection service that considers the current conditions of available networks in a given location. This is a departure from past designs of vertical handover decision algorithms, which tend to approach the problem from the perspective of individual network operators. The wide range of radio access technologies operated by different network operators that are available to a device within a hetnet, coupled with the mobile data offload effort, is the primary motivator behind our novel choice in direction. This thesis documents the design and implementation of such an over-the-top vertical handover decision service

From cellular decision making to adaptive handoff in heterogeneous wireless networks

Handoff decision making is critical for mobile users to reap potential benefits from heterogeneous wireless networks. This letter proposes a biologically inspired handoff decisionmaking method by mimicking the dynamics which govern the adaptive behavior of an Escherichia coli cell in a time-varying environment.With the goal of guaranteeing the Quality of Service (QoS), we formulate a utility function that covers the demands of a user’s diverse applications and the time-varying network conditions. With this utility function, we map the dynamic heterogeneous environment to a cellular decision-making space, such that the user is induced by a cellular attractor selection mechanism to make distributed and robust handoff decisions. Furthermore, we also present a multi-attribute decision-making network selection algorithm for any user to determine an access network, which is integrated with the proposed bio-inspired decision-making mechanism. Simulation results are supplemented to show that the proposed method can achieve better QoS and fairness when it is compared with conventional methods

Modeling Seamless Vertical Handovers in Heterogeneous Wireless Networks

Vertical handover in heterogeneous wireless networks provides customers with better Quality of Service (QoS) experience. For seamless handover, timely initiation of handover process plays a key role. Various vertical handover management protocols have been proposed and standardized to support mobility across heterogeneous networks. In Media Independent Handover (MIH) based schemes, distributed handover decision is made via certain predefined triggers that consider user context. In this paper, we present a comprehensive review of the modeling techniques used during management of vertical handover. We have also defined a novel architecture, HRPNS: Handoff Resolving and Preferred Network Selection module enabling vertical handover that ensures QoS. The construction of HRPNS module involves integration of fuzzy logic and Markov Decision Process (MDP) for providing precise decision of handover

Network Selection in Wireless Heterogeneous Networks: a Survey, Journal of Telecommunications and Information Technology, 2018, nr 4

Heterogeneous wireless networks is a term referring to networks combining different radio access technologies with the aim of establishing the best connection possible. In this case, users with multi-mode terminals can connect via different wireless technologies, such as 802.16, 802.11, UMTS, HSPA and LTE, all at the same time. The problem consists in the selection of the most suitable from all radio access technologies available. The decision process is called network selection, and depends on several parameters, such as quality of service, mobility, cost, energy, battery life, etc. Several methods and approaches have been proposed in this context, with their objective being to offer the best QoS to the users, and/or to maximize re-usability of the networks. This paper represents a survey of the network selection methods used. Multiple attribute-dependent decision-making methods are presented. Furthermore, the game theory concept is illustrated, the use of the fuzzy logic is presented, and the utility functions defining the network selection process are discussed