Analytical modeling of HSUPA-enabled UMTS networks for capacity planning

In recent years, mobile communication networks have experienced significant evolution. The 3G mobile communication system, UMTS, employs WCDMA as the air interface standard, which leads to quite different mobile network planning and dimensioning processes compared with 2G systems. The UMTS system capacity is limited by the received interference at NodeBs due to the unique features of WCDMA, which is denoted as `soft capacity'. Consequently, the key challenge in UMTS radio network planning has been shifted from channel allocation in the channelized 2G systems to blocking and outage probabilities computation under the `cell breathing' effects which are due to the relationship between network coverage and capacity. The interference characterization, especially for the other-cell interference, is one of the most important components in 3G mobile networks planning. This monograph firstly investigates the system behavior in the operation of UMTS uplink, and develops the analytic techniques to model interference and system load as fully-characterized random variables, which can be directly applicable to the performance modeling of such networks. When the analysis progresses from single-cell scenario to multi-cell scenario, as the target SIR oriented power control mechanism is employed for maximum capacity, more sophisticated system operation, `feedback behavior', has emerged, as the interference levels at different cells depend on each other. Such behaviors are also captured into the constructed interference model by iterative and approximation approaches. The models are then extended to cater for the features of the newly introduced HSUPA, which provides enhanced dedicated channels for the packet switched data services such that much higher bandwidth can be achieved for best-effort elastic traffic, which allows network operators to cope with the coexistence of both circuit-switched and packet-switched traffic and guarantee the QoS requirements. During the derivation, we consider various propagation models, traffic models, resource allocation schemes for many possible scenarios, each of which may lead to different analytical models. All the suggested models are validated with either Monte-Carlo simulations or discrete event simulations, where excellent matches between results are always achieved. Furthermore, this monograph studies the optimization-based resource allocation strategies in the UMTS uplink with integrated QoS/best-effort traffic. Optimization techniques, both linear-programming based and non-linear-programming based, are used to determine how much resource should be assigned to each enhanced uplink user in the multi-cell environment where each NodeB possesses full knowledge of the whole network. The system performance under such resource allocation schemes are analyzed and compared via Monte-Carlo simulations, which verifies that the proposed framework may serve as a good estimation and optimal reference to study how systems perform for network operators

Analytical modeling of HSUPA-enabled UMTS networks for capacity planning

In recent years, mobile communication networks have experienced significant evolution. The 3G mobile communication system, UMTS, employs WCDMA as the air interface standard, which leads to quite different mobile network planning and dimensioning processes compared with 2G systems. The UMTS system capacity is limited by the received interference at NodeBs due to the unique features of WCDMA, which is denoted as `soft capacity'. Consequently, the key challenge in UMTS radio network planning has been shifted from channel allocation in the channelized 2G systems to blocking and outage probabilities computation under the `cell breathing' effects which are due to the relationship between network coverage and capacity. The interference characterization, especially for the other-cell interference, is one of the most important components in 3G mobile networks planning. This monograph firstly investigates the system behavior in the operation of UMTS uplink, and develops the analytic techniques to model interference and system load as fully-characterized random variables, which can be directly applicable to the performance modeling of such networks. When the analysis progresses from single-cell scenario to multi-cell scenario, as the target SIR oriented power control mechanism is employed for maximum capacity, more sophisticated system operation, `feedback behavior', has emerged, as the interference levels at different cells depend on each other. Such behaviors are also captured into the constructed interference model by iterative and approximation approaches. The models are then extended to cater for the features of the newly introduced HSUPA, which provides enhanced dedicated channels for the packet switched data services such that much higher bandwidth can be achieved for best-effort elastic traffic, which allows network operators to cope with the coexistence of both circuit-switched and packet-switched traffic and guarantee the QoS requirements. During the derivation, we consider various propagation models, traffic models, resource allocation schemes for many possible scenarios, each of which may lead to different analytical models. All the suggested models are validated with either Monte-Carlo simulations or discrete event simulations, where excellent matches between results are always achieved. Furthermore, this monograph studies the optimization-based resource allocation strategies in the UMTS uplink with integrated QoS/best-effort traffic. Optimization techniques, both linear-programming based and non-linear-programming based, are used to determine how much resource should be assigned to each enhanced uplink user in the multi-cell environment where each NodeB possesses full knowledge of the whole network. The system performance under such resource allocation schemes are analyzed and compared via Monte-Carlo simulations, which verifies that the proposed framework may serve as a good estimation and optimal reference to study how systems perform for network operators

Resource allocation in cellular CDMA systems with cross- layer Optimization

Ph.DDOCTOR OF PHILOSOPH

이동통신 네트워크에서의 QoS 패킷 스케줄러 설계 및 고정 릴레이 관련 주파수 재사용 관리 기법 연구

학위논문 (박사)-- 서울대학교 대학원 공과대학 전기·컴퓨터공학부, 2017. 8. 박세웅.The main interest of this paper is to understand a basic approach to provide more efficient method to allocate radio resources in the mobile communication systems, especially in which radio resources could be allocated by both frequency and time division multiple access. So, we consider OFDMA system and the ideas described in this paper could be easily applied to the current and next generation mobile communication systems. This paper studies two basic research themesa QoS packet scheduler design and fixed relay resource management policies based on frequency reuse in mobile networks. This paper considers novel scheduler structures that are executable in the environments of multiple traffic classes and multiple frequency channels. To design a scheduler structure for multiple traffic classes, we first propose a scheduler selection rule that uses the priority of traffic class and the urgency level of each packet. Then we relax the barrier of traffic class priority when a high priority packet has some room in waiting time. This gives us a chance to exploit multiuser diversity, thereby giving more flexibility in scheduling. Our considered scheduler can achieve higher throughput compared to the simple extension of conventional modified largest weighted delay first (MLWDF) scheduler while maintaining the delay performance for QoS class traffic. We also design a scheduler structure for multiple frequency channels that chooses a good channel for each user whenever possible to exploit frequency diversity. The simulation results show that our proposed scheduler increases the total system throughput by up to 50% without degrading the delay performance. This paper also introduces radio resource management schemes based on frequency reuse for fixed relay stations in mobile cellular networks. Mobile stations in the cell boundary experience poor spectral efficiency due to the path loss and interference from adjacent cells. Therefore, satisfying QoS requirements of each MS at the cell boundary has been an important issue. To resolve this spectral efficiency problem at the cell boundary, deploying fixed relay stations has been actively considered. In this paper, we consider radio resource management policies based on frequency reuse for fixed relays that include path selection rules, frequency reuse pattern matching, and frame transmission pattern matching among cells. We evaluate performance of each policy by varying parameter values such as relay stations position and frequency reuse factor. Through Monte Carlo simulations and mathematical analysis, we suggest some optimal parameter values for each policy and discuss some implementation issues that need to be considered in practical deployment of relay stations. We also surveyed further works that many researchers have been studied to tackle the similar problems of QoS scheduling and resource management for relay with our proposed work. We expect that there would be more future works by priority-based approach and energy-aware approach for QoS scheduling. Also current trends such as the rising interest in IoT system, discussion of densification of cells and D2D communications in 5G systems make us expect that the researches in these topics related with relays would be popular in the future. We also think that there are many interesting problems regarding QoS support and resource management still waiting to be tackled, especially combined with recent key topics in mobile communication systems such as 5G standardization, AI and NFV/SDN.Chapter 1 Introduction 1 1.1 QoS Packet Scheduler 4 1.2 Fixed Relay Frequency Reuse Policies 6 Chapter 2 Scheduler Design for Multiple Traffic Classes in OFDMA Networks 10 2.1 Proposed Schedulers 10 2.1.1 Scheduler Structures 12 2.1.2 MLWDF scheduler for Multiple Traffic Classes 13 2.1.3 Joint Scheduler 13 2.2 System Model 18 2.3 Performance Evaluation 19 2.3.1 Schedulers for Multiple Traffic Classes 20 2.3.2 Impact of Scheduler Selection Rule 25 2.3.3 Frame Based Schedulers 27 2.3.4 Impact of Partial Feedback 30 2.3.5 Adaptive Threshold Version Schedulers 33 2.4 Conclusion 36 Chapter 3 Frequency Reuse Policies for Fixed Relays in Cellular Networks 40 3.1 System Model 40 3.1.1 Frame Transmission and Frequency Reuse Patterns among RSs 42 3.1.2 Positioning of RSs and Channel Capacity 44 3.1.3 Area Spectral Efficiency 45 3.2 Radio Resource Management Policies Based on Frequency Reuse 46 3.2.1 Path Selection Rule 46 3.2.2 Frequency Reuse and Frame Transmission Pattern Matchings among Cells 52 3.3 Monte Carlo Simulation and Results 53 3.4 Consideration of Practical Issues 80 3.5 Conclusion 81 Chapter 4 Surveys of Further Works 83 4.1 Further Works on QoS Schedulers 83 4.1.1 WiMAX Schedulers 85 4.1.2 LTE Schedulers 92 4.2 Further Works on Radio Resource Management in Relay Systems 98 4.3 Future Challenges 100 Chapter 5 Conclusion 104 Bibliography 107 초록 127Docto

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

Resource management for virtualized networks

Network Virtualization has emerged as a promising approach that can be employed to efficiently enhance the resource management technologies. In this work, the goal is to study how to automate the bandwidth resource management, while deploying a virtual partitioning scheme for the network bandwidth resources. Works that addressed the resource management in Virtual Networks are many, however, each has some limitations. Resource overwhelming, poor bandwidth utilization, low profits, exaggeration, and collusion are types of such sort of limitations. Indeed, the lack of adequate bandwidth allocation schemes encourages resource overwhelming, where one customer may overwhelm the resources that supposed to serve others. Static resource partitioning can resist overwhelming but at the same time it may result in poor bandwidth utilization, which means less profit rates for the Internet Service Providers (ISPs). However, deploying the technology of autonomic management can enhance the resource utilization, and maximize the customers’ satisfaction rates. It also provides the customers with a kind of privilege that should be somehow controlled as customers, always eager to maximize their payoffs, can use such a privilege to cheat. Hence, cheating actions like exaggeration and collusion can be expected. Solving the aforementioned limitations is addressed in this work. In the first part, the work deals with overcoming the problems of low profits, poor utilization, and high blocking ratios of the traditional First Ask First Allocate (FAFA) algorithm. The proposed solution is based on an Autonomic Resource Management Mechanism (ARMM). This solution deploys a smarter allocation algorithm based on the auction mechanism. At this level, to reduce the tendency of exaggeration, the Vickrey-Clarke-Groves (VCG) is proposed to provide a threat model that penalizes the exaggerating customers, based on the inconvenience they cause to others in the system. To resist the collusion, the state-dependent shadow price is calculated, based on the Markov decision theory, to represent a selling price threshold for the bandwidth units at a given state. Part two of the work solves an expanded version of the bandwidth allocation problem, but through a different methodology. In this part, the bandwidth allocation problem is expanded to a bandwidth partitioning problem. Such expansion allows dividing the link’s bandwidth resources based on the provided Quality of Service (QoS) classes, which provides better bandwidth utilization. In order to find the optimal management metrics, the problem is solved through Linear Programming (LP). A dynamic bandwidth partitioning scheme is also proposed to overcome the problems related to the static partitioning schemes, such as the poor bandwidth utilization, which can result in having under-utilized partitions. This dynamic partitioning model is deployed in a periodic manner. Periodic partitioning provides a new way to reduce the reasoning of exaggeration, when compared to the threat model, and eliminates the need of the further computational overhead. The third part of this work proposes a decentralized management scheme to solve aforementioned problems in the context of networks that are managed by Virtual Network Operators (VNOs). Such decentralization allows deploying a higher level of autonomic management, through which, the management responsibilities are distributed over the network nodes, each responsible for managing its outgoing links. Compared to the centralized schemes, such distribution provides higher reliability and easier bandwidth dimensioning. Moreover, it creates a form of two-sided competition framework that allows a double-auction environment among the network players, both customers and node controllers. Such competing environment provides a new way to reduce the exaggeration beside the periodic and threat models mentioned before. More important, it can deliver better utilization rates, lower blocking, and consequently higher profits. Finally, numerical experiments and empirical results are presented to support the proposed solutions, and to provide a comparison with other works from the literature

Energy-efficient wireless communication

In this chapter we present an energy-efficient highly adaptive network interface architecture and a novel data link layer protocol for wireless networks that provides Quality of Service (QoS) support for diverse traffic types. Due to the dynamic nature of wireless networks, adaptations in bandwidth scheduling and error control are necessary to achieve energy efficiency and an acceptable quality of service. In our approach we apply adaptability through all layers of the protocol stack, and provide feedback to the applications. In this way the applications can adapt the data streams, and the network protocols can adapt the communication parameters

Radio Resource Allocation in Wireless OFDM Systems

Ph.DDOCTOR OF PHILOSOPH

Radio Resource Management Optimization For Next Generation Wireless Networks

The prominent versatility of today’s mobile broadband services and the rapid advancements in the cellular phones industry have led to a tremendous expansion in the wireless market volume. Despite the continuous progress in the radio-access technologies to cope with that expansion, many challenges still remain that need to be addressed by both the research and industrial sectors. One of the many remaining challenges is the efficient allocation and management of wireless network resources when using the latest cellular radio technologies (e.g., 4G). The importance of the problem stems from the scarcity of the wireless spectral resources, the large number of users sharing these resources, the dynamic behavior of generated traffic, and the stochastic nature of wireless channels. These limitations are further tightened as the provider’s commitment to high quality-of-service (QoS) levels especially data rate, delay and delay jitter besides the system’s spectral and energy efficiencies. In this dissertation, we strive to solve this problem by presenting novel cross-layer resource allocation schemes to address the efficient utilization of available resources versus QoS challenges using various optimization techniques. The main objective of this dissertation is to propose a new predictive resource allocation methodology using an agile ray tracing (RT) channel prediction approach. It is divided into two parts. The first part deals with the theoretical and implementational aspects of the ray tracing prediction model, and its validation. In the second part, a novel RT-based scheduling system within the evolving cloud radio access network (C-RAN) architecture is proposed. The impact of the proposed model on addressing the long term evolution (LTE) network limitations is then rigorously investigated in the form of optimization problems. The main contributions of this dissertation encompass the design of several heuristic solutions based on our novel RT-based scheduling model, developed to meet the aforementioned objectives while considering the co-existing limitations in the context of LTE networks. Both analytical and numerical methods are used within this thesis framework. Theoretical results are validated with numerical simulations. The obtained results demonstrate the effectiveness of our proposed solutions to meet the objectives subject to limitations and constraints compared to other published works