Efficient joint call admission control and bandwidth management schemes for QoS provisioning in heterogeneous wireless networks

Includes abstract.Includes bibliographical references (leaves 150-157).Next generation wireless network (NGWN) will be heterogeneous where different radio access technologies (RATs) coexist. This coexistence of different RATs necessitates joint radio resource management (JRRM) for enhanced QoS provisioning and efficient radio resource utilization. Joint call admission control (JCAC) algorithm is one of the joint radio resource management algorithms. The basic functions of a JCAC algorithm are to decide whether or not an incoming call can be accepted into a heterogeneous wireless network, and to determine which of the available RATs is most suitable to admit the incoming call. The objective of a JCAC algorithm is to guarantee the QoS requirements of all accepted calls and at the same time make the best use of the available radio resources. Traditional call admission control algorithms designed for homogeneous wireless networks do not provide a single solution to address the heterogeneous architecture, which characterizes NGWN. Consequently, there is need to develop JCAC algorithms for heterogeneous wireless networks. The thesis proposes three JCAC schemes for improving QoS and radio resource utilization, which are of primary concerns, in heterogeneous wireless networks. The first scheme combines adaptive bandwidth management and joint call admission control. The objectives of the first scheme are to enhance average system utilization, guarantee QoS requirements of all accepted calls, and reduce new call blocking probability and handoff call dropping probability in heterogeneous wireless networks. The scheme consists of three components namely: joint call admission controller, bandwidth reservation unit, and bandwidth adaptation unit. Using Markov decision process, an analytical model is developed to evaluate the performance of the proposed scheme considering three performance metrics, which are new call blocking probability, handoff call dropping probability, and system utilization. Numerical results show that the proposed scheme improves system utilization and reduces both new call blocking probability and handoff call dropping probability. The second proposed JCAC scheme minimizes call blocking probability by determining the optimal call allocation policy among the available RATs. The scheme measures the arrival rates of different classes of calls into the heterogeneous wireless network. Using linear programming technique, the JCAC scheme determines the call allocation policy that minimizes call-blocking probability in the heterogeneous network. Numerical results show that the proposed scheme reduces call-blocking probability in the heterogeneous wireless network

Congestion control in multi-serviced heterogeneous wireless networks using dynamic pricing

Includes bibliographical references.Service providers, (or operators) employ pricing schemes to help provide desired QoS to subscribers and to maintain profitability among competitors. An economically efficient pricing scheme, which will seamlessly integrate users’ preferences as well as service providers’ preferences, is therefore needed. Else, pricing schemes can be viewed as promoting social unfairness in the dynamically priced network. However, earlier investigations have shown that the existing dynamic pricing schemes do not consider the users’ willingness to pay (WTP) before the price of services is determined. WTP is the amount a user is willing to pay based on the worth attached to the service requested. There are different WTP levels for different subscribers due to the differences in the value attached to the services requested and demographics. This research has addressed congestion control in the heterogeneous wireless network (HWN) by developing a dynamic pricing scheme that efficiently incentivises users to utilize radio resources. The proposed Collaborative Dynamic Pricing Scheme (CDPS), which identifies the users and operators’ preference in determining the price of services, uses an intelligent approach for controlling congestion and enhancing both the users’ and operators’ utility. Thus, the CDPS addresses the congestion problem by firstly obtaining the users WTP from users’ historical response to price changes and incorporating the WTP factor to evaluate the service price. Secondly, it uses a reinforcement learning technique to illustrate how a price policy can be obtained for the enhancement of both users and operators’ utility, as total utility reward obtained increases towards a defined ‘goal state’

A source-destination based dynamic pricing scheme to optimize resource utilization in heterogeneous wireless networks

Mobile wireless resources demand is rapidly growing due to the proliferation of bandwidth-hungry mobile devices and applications. This has resulted in congestion in mobile wireless networks (MWN) especially during the peak hours when user traffic can be as high as tenfold the average traffic. Mobile network operators (MNOs) have been trying to solve this problem in various ways. First, MNOs have tried to expand the network capacity but have still been unable to meet the peak hour demand. Focus has then shifted to economic and behavioral mechanisms. The widely used of these economic mechanisms is dynamic pricing which varies the MWN resources' price according to the congestion level in the MWN. This encourages users to shift their non-critical traffic from the busy hour, when the MWN is congested, to off-peak hours when the network is under-utilized. As a result, congestion of the MWN during the peak hours is reduced. At the same time, the MWN utilization during the off-peak hours is also increased. The current dynamic pricing schemes, however, only consider the congestion level in the call-originating cell and neglect the call-destination cell when computing the dynamic price. Due to this feature, we refer the current dynamic pricing schemes as source–based dynamic pricing (SDP) schemes in this work. The main problem with these schemes is that, when the majority of the users in a congested cell are callees, dynamic pricing is ineffective because callers and not callees pay for network services, and resources used by callers and callees are the same for symmetric services. For example, application of dynamic pricing does not deter a callee located in a congested cell from receiving a call, which originates from a caller located in an uncongested cell. Also, when the distribution of prospective callees is higher than that of callers in an underutilized cell, SDP schemes are ineffective as callees do not pay for a call and therefore low discounts do not entice them to increase utilization. In this distribution, dynamic pricing entices prospective callers to make calls but since their distribution is low, the MWN resource utilization does not increase by any significant margin. To address these problems, we have developed a source-destination based dynamic pricing (SDBDP) scheme, which considers congestion levels in both the call-originating and calldestination cells to compute the dynamic price to be paid by a caller. This SDBDP scheme is integrated with a load-based joint call admission control (JCAC) algorithm for admitting incoming service requests in to the least utilized radio access technology (RAT). The load-based JCAC algorithm achieves uniform traffic distribution in the heterogeneous wireless network (HWN). To test the SDBDP scheme, we have developed an analytical model based on M/M/m/m queuing model. New or handoff service requests, arriving when all the RATs in the HWN are fully utilized, lead to call blocking for new calls and call dropping for handoff calls. The call blocking probability, call dropping probability and percentage MWN utilization are used as the performance metrics in evaluating the SDBDP scheme. An exponential demand model is used to approximate the users' response to the presented dynamic price. The exponential demand model captures both the price elasticity of demand and the demand shift constant for different users. The matrix laboratory (MATLAB) tool has been used to carry out the numerical simulations. An evaluation scenario consisting of four groups of co-located cells each with three RATs is used. Both SDP and the developed SDBDP schemes have been subjected under the evaluation scenario. Simulation results show that the developed SDBDP scheme reduces both the new call blocking and handoff call dropping probabilities during the peak hours, for all callercallee distributions. On the other hand, the current SDP scheme only reduces new call blocking and handoff call dropping probabilities only under some caller –callee distributions (When the callers were the majority in the HWN). Also, the SDBDP scheme increases the percentage MWN utilization during the off-peak for all the caller-callee distributions in the HWN. On the other hand, the SDP scheme is found to increase the percentage MWN utilization only when the distribution of callers is higher than that of callees in the HWN. From analyzing the simulations results, we conclude that the SDBDP scheme achieves better congestion control and MWN resource utilization than the existing SDP schemes, under arbitrary caller-callee distribution

사용자 중심의 밀리미터파 통신 시스템을 위한 이동성 인식 분석 프레임워크 및 네트워크 관리 기법

학위논문 (박사) -- 서울대학교 대학원 : 공과대학 전기·정보공학부, 2021. 2. 박세웅.Millimeter wave (mmWave) communication enables high rate transmission, but its network performance may be degraded significantly due to blockages between the transmitter and receiver. There have been two approaches to overcome the blockage effect and enhance link reliability: multi-connectivity and ultra-dense network (UDN). Particularly, multi-connectivity under a UDN environment facilitates user-centric communication. It requires dynamic configuration of serving base station groups so that each user experiences high quality services. This dissertation studies a mathematical framework and network manament schemes for user-centric mmWave communication systems. First, we models user mobility and mobility-aware performance in user-centric mmWave communication systems with multi-connectivity, and proposes a new analytical framework based on the stochastic geometry. To this end, we derive compact mathematical expressions for state transitions and probabilities of various events that each user experiences. Then we investigate mobility-aware performance in terms of network overhead and downlink throughput. This helps us to understand network operation in depth, and impacts of network density and multi-connection capability on the probability of handover related events. Numerical results verify the accuracy of our analysis and illustrate the correlation between mobility-aware performance and user speed. Next, we propose user-oriented configuration rules and price based association algorithms for user-centric mmWave networks with fully/partially wired backhauls. We develop a fair association algorithm by solving the optimization problem that we formulate for mmWave UDNs. The algorithm includes an access price based per-user request decision method and a price adjustment rule for load balancing. Based on insights from the algorithm, we develop path-aware access pricing policy for mmWave integrated access and backhaul networks. Numerical evaluations show that our proposed methods are superior to other comparative schemes. Our findings from analysis and optimization provide useful insights into the design of user-centric mmWave communication systems.밀리미터파 통신은 고속 전송을 가능하게 하지만 송신기와 수신기 사이의 장애물로 인해 네트워크 성능이 크게 저하될 수 있다. 장애물 효과를 극복하고 링크 안정성을 향상시키는 다중 연결 및 네트워크 초고밀화 두가지 접근법이 있다. 특히 각 사용자가 고품질의 서비스를 경험할 수 있도록 서빙 기지국 그룹의 동적 구성이 필요하므로 초고밀도 네트워크 환경에서 다중 연결은 사용자 중심 통신을 용이하게 한다. 본 논문은 사용자 중심의 밀리미터파 통신 시스템을 위한 수학적 프레임워크와 네트워크 관리 체계를 연구한다. 먼저 다중 연결을 사용하여 사용자 중심의 밀리미터파 통신 시스템에서 사용자 이동성과 이동성 인식 성능 지표를 모델링하고 확률기하분석을 기반으로 하는 새로운 분석 프레임워크를 제안한다. 이를 위해 각 사용자가 경험하는 다양한 이벤트의 상태 전이 확률에 대한 수학적 표현을 도출한다. 그런 다음 네트워크 오버헤드 및 다운 링크 수율 측면에서 이동성 인식 성능을 연구한다. 이를 통해 네트워크 운영에 대한 깊이있는 이해와 네트워크 밀도 및 다중 연결 기능이 핸드 오버와 관련된 이벤트의 확률에 미치는 영향을 이해할 수 있다. 시뮬레이션 결과는 분석의 정확성을 검증하고 이동성 인식 성능과 사용자 속도 간의 상관 관계를 보여준다. 다음으로 완전 또는 부분 유선 백홀이 있는 사용자 중심 밀리미터파 네트워크를 위한 사용자 중심 구성 규칙 및 접속 가격 기반 연결 알고리즘을 제안한다. 밀리미터파 초고밀도 네트워크에 대한 최적화 문제를 해결하여 공정한 연결 알고리즘을 개발한다. 이 알고리즘에는 접속 가격 기반 사용자 별 요청 결정 방법과 로드 밸런싱을 위한 가격 조정 규칙이 포함된다. 위 알고리즘 개발을 통해 얻은 통찰력을 기반으로 밀리미터파 통합 액세스 및 백홀 네트워크를 위한 경로 인식 접속 요금 정책을 개발한다. 수치 평가에 따르면 제안된 방법이 다른 비교 기법보다 우수하다. 분석 및 최적화 결과는 사용자 중심의 밀리미터파 통신 시스템 설계에 대한 유용한 통찰력을 제공할 것 이다.Abstract i Contents iii List of Tables vi List of Figures vii 1 Introduction 1 1.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Outline and Contributions . . . . . . . . . . . . . . . . . . . . . . . . 3 2 Mobility-Aware Analysis of MillimeterWave Communication Systems with Blockages 5 2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2.1.1 Related Work . . . . . . . . . . . . . . . . . . . . . . . . . . 6 2.1.2 Contributions . . . . . . . . . . . . . . . . . . . . . . . . . . 8 2.2 System Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 2.2.1 Network Model . . . . . . . . . . . . . . . . . . . . . . . . . 9 2.2.2 Connectivity Model . . . . . . . . . . . . . . . . . . . . . . 10 2.2.3 Mobility Model . . . . . . . . . . . . . . . . . . . . . . . . . 11 2.3 Mobility-Aware Analysis . . . . . . . . . . . . . . . . . . . . . . . . 13 2.3.1 Analytical Framework . . . . . . . . . . . . . . . . . . . . . 13 2.3.2 Urban Scenario with Ultra-Densely Deployed BSs . . . . . . 18 2.3.3 Handover Analysis for Macrodiversity . . . . . . . . . . . . . 22 2.3.4 Normalized Network Overhead and Mobility-Aware Downlink Throughput with Greedy User Association . . . . . . . . 24 2.4 Numerical Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 2.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 3 Association Control for User-Centric Millimeter Wave Communication Systems 34 3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34 3.2 System Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 3.2.1 Network Model . . . . . . . . . . . . . . . . . . . . . . . . . 37 3.2.2 Channel Model and Achievable Rate . . . . . . . . . . . . . . 39 3.2.3 User Centric mmWave Communication Framework . . . . . . 39 3.3 Traffic Load Management . . . . . . . . . . . . . . . . . . . . . . . . 44 3.3.1 Optimal Association and Admission Control . . . . . . . . . 45 3.3.2 Outage Analysis . . . . . . . . . . . . . . . . . . . . . . . . 51 3.4 Performance Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . 53 3.4.1 Evaluation Environments . . . . . . . . . . . . . . . . . . . . 53 3.4.2 Performance Comparison . . . . . . . . . . . . . . . . . . . . 55 3.5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 4 Path Selection and Path-Aware Access Pricing Policy in Millimeter Wave IAB Networks 60 4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60 4.2 System Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62 4.2.1 Geographic and Pathloss Models . . . . . . . . . . . . . . . . 62 4.2.2 IAB Network Model . . . . . . . . . . . . . . . . . . . . . . 63 4.3 Path Selection Strategies . . . . . . . . . . . . . . . . . . . . . . . . 66 4.4 Path-Aware Access Pricing Policy . . . . . . . . . . . . . . . . . . . 69 4.5 Performance Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . 72 4.6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78 5 Conclusion 80 5.1 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 5.2 Limitations and Future Work . . . . . . . . . . . . . . . . . . . . . . 82 Abstract (In Korean) 90Docto

Review on Radio Resource Allocation Optimization in LTE/LTE-Advanced using Game Theory

Recently, there has been a growing trend toward ap-plying game theory (GT) to various engineering fields in order to solve optimization problems with different competing entities/con-tributors/players. Researches in the fourth generation (4G) wireless network field also exploited this advanced theory to overcome long term evolution (LTE) challenges such as resource allocation, which is one of the most important research topics. In fact, an efficient de-sign of resource allocation schemes is the key to higher performance. However, the standard does not specify the optimization approach to execute the radio resource management and therefore it was left open for studies. This paper presents a survey of the existing game theory based solution for 4G-LTE radio resource allocation problem and its optimization

A price based load balancing scheme for multi-operator wireless access networks

We study a load balancing strategy, based on the price offered by the base stations to the end-users who are willing to establish a connection. The proposed scheme is compared with a pure load balancing procedure, in a scenario comprising two different operators.We study the impact of modifying the price offered by the base stations, in terms of the achieved load balancing, as well as considering the revenue obtained by the operators. Furthermore, we also enhance the two former access selection schemes, by incorporating the willingness of reducing the number of handovers, so as to analyze the impact over this particular parameter, and over all the previous results. The whole work is conducted over a proprietary event-based simulation tool, which offers the required degree of flexibility and low computational overhead.Preprin

Dynamic Pricing in Heterogeneous Wireless Cellular Networks

Smart communications devices are giving users instant access to applications that consume large amounts of data. These applications have different requirements on the network for delivery of data. In order to support these different applications, operators are required to support multiple service classes. Given the regulatory and technology constraints and the relatively high cost associated with wireless spectrum licensing and utilization, demand will exceed supply leading to congestion and overload conditions. In addition to new broadband radio technologies offering higher data rates, operators are looking at deploying alternate heterogeneous technologies, such as WLAN, to provide additional bandwidth for serving customers. It is expected that this will still fall short of providing enough network resources to meet the ITU requirement for 1% new call blocking probability. An economic mechanism that offers incentives to individuals for rational behavior is required in order in order to reduce the demand for network resources and resolve the congestion problem. The research in this dissertation demonstrates that the integration of a dynamic pricing with connection admission control mechanism for an operator deploying cooperative heterogeneous networks (e.g., LTE and WLAN) offering multiple QoS service classes reduces the new call blocking probability to the required 1% level. The experimental design consisted, first, of an analytical model of the CAC algorithm with dynamic pricing in a heterogeneous environment. The analytical model was subsequently validated through discrete-event simulation using Matlab

A Taxonomy for Management and Optimization of Multiple Resources in Edge Computing

Edge computing is promoted to meet increasing performance needs of data-driven services using computational and storage resources close to the end devices, at the edge of the current network. To achieve higher performance in this new paradigm one has to consider how to combine the efficiency of resource usage at all three layers of architecture: end devices, edge devices, and the cloud. While cloud capacity is elastically extendable, end devices and edge devices are to various degrees resource-constrained. Hence, an efficient resource management is essential to make edge computing a reality. In this work, we first present terminology and architectures to characterize current works within the field of edge computing. Then, we review a wide range of recent articles and categorize relevant aspects in terms of 4 perspectives: resource type, resource management objective, resource location, and resource use. This taxonomy and the ensuing analysis is used to identify some gaps in the existing research. Among several research gaps, we found that research is less prevalent on data, storage, and energy as a resource, and less extensive towards the estimation, discovery and sharing objectives. As for resource types, the most well-studied resources are computation and communication resources. Our analysis shows that resource management at the edge requires a deeper understanding of how methods applied at different levels and geared towards different resource types interact. Specifically, the impact of mobility and collaboration schemes requiring incentives are expected to be different in edge architectures compared to the classic cloud solutions. Finally, we find that fewer works are dedicated to the study of non-functional properties or to quantifying the footprint of resource management techniques, including edge-specific means of migrating data and services.Comment: Accepted in the Special Issue Mobile Edge Computing of the Wireless Communications and Mobile Computing journa

Traffic-Driven Energy Efficient Operational Mechanisms in Cellular Access Networks

Recent explosive growth in mobile data traffic is increasing energy consumption in cellular networks at an incredible rate. Moreover, as a direct result of the conventional static network provisioning approach, a significant amount of electrical energy is being wasted in the existing networks. Therefore, in recent time, the issue of designing energy efficient cellular networks has drawn significant attention, which is also the foremost motivation behind this research. The proposed research is particularly focused on the design of self-organizing type traffic-sensitive dynamic network reconfiguring mechanisms for energy efficiency in cellular systems. Under the proposed techniques, radio access networks (RANs) are adaptively reconfigured using less equipment leading to reduced energy utilization. Several energy efficient cellular network frameworks by employing inter-base station (BS) cooperation in RANs are proposed. Under these frameworks, based on the instantaneous traffic demand, BSs are dynamically switched between active and sleep modes by redistributing traffic among them and thus, energy savings is achieved. The focus is then extended to exploiting the availability of multiple cellular networks for extracting energy savings through inter-RAN cooperation. Mathematical models for both of these single-RAN and multi-RAN cooperation mechanisms are also formulated. An alternative energy saving technique using dynamic sectorization (DS) under which some of the sectors in the underutilized BSs are turned into sleep mode is also proposed. Algorithms for both the distributed and the centralized implementations are developed. Finally, a two-dimensional energy efficient network provisioning mechanism is proposed by jointly applying both the DS and the dynamic BS switching. Extensive simulations are carried out, which demonstrate the capability of the proposed mechanisms in substantially enhancing the energy efficiency of cellular networks

Load balancing in heterogeneous wireless communications networks. Optimized load aware vertical handovers in satellite-terrestrial hybrid networks incorporating IEEE 802.21 media independent handover and cognitive algorithms.

Heterogeneous wireless networking technologies such as satellite, UMTS, WiMax and WLAN are being used to provide network access for both voice and data services. In big cities, the densely populated areas like town centres, shopping centres and train stations may have coverage of multiple wireless networks. Traditional Radio Access Technology (RAT) selection algorithms are mainly based on the ¿Always Best Connected¿ paradigm whereby the mobile nodes are always directed towards the available network which has the strongest and fastest link. Hence a large number of mobile users may be connected to the more common UMTS while the other networks like WiMax and WLAN would be underutilised, thereby creating an unbalanced load across these different wireless networks. This high variation among the load across different co-located networks may cause congestion on overloaded network leading to high call blocking and call dropping probabilities. This can be alleviated by moving mobile users from heavily loaded networks to least loaded networks. This thesis presents a novel framework for load balancing in heterogeneous wireless networks incorporating the IEEE 802.21 Media Independent Handover (MIH). The framework comprises of novel load-aware RAT selection techniques and novel network load balancing mechanism. Three new different load balancing algorithms i.e. baseline, fuzzy and neural-fuzzy algorithms have also been presented in this thesis that are used by the framework for efficient load balancing across the different co-located wireless networks. A simulation model developed in NS2 validates the performance of the proposed load balancing framework. Different attributes like load distribution in all wireless networks, handover latencies, packet drops, throughput at mobile nodes and network utilization have been observed to evaluate the effects of load balancing using different scenarios. The simulation results indicate that with load balancing the performance efficiency improves as the overloaded situation is avoided by load balancing