12 research outputs found

    Convergence of packet communications over the evolved mobile networks; signal processing and protocol performance

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    In this thesis, the convergence of packet communications over the evolved mobile networks is studied. The Long Term Evolution (LTE) process is dominating the Third Generation Partnership Project (3GPP) in order to bring technologies to the markets in the spirit of continuous innovation. The global markets of mobile information services are growing towards the Mobile Information Society. The thesis begins with the principles and theories of the multiple-access transmission schemes, transmitter receiver techniques and signal processing algorithms. Next, packet communications and Internet protocols are referred from the IETF standards with the characteristics of mobile communications in the focus. The mobile network architecture and protocols bind together the evolved packet system of Internet communications to the radio access network technologies. Specifics of the traffic models are shortly visited for their statistical meaning in the radio performance analysis. Radio resource management algorithms and protocols, also procedures, are covered addressing their relevance for the system performance. Throughout these Chapters, the commonalities and differentiators of the WCDMA, WCDMA/HSPA and LTE are covered. The main outcome of the thesis is the performance analysis of the LTE technology beginning from the early discoveries to the analysis of various system features and finally converging to an extensive system analysis campaign. The system performance is analysed with the characteristics of voice over the Internet and best effort traffic of the Internet. These traffic classes represent the majority of the mobile traffic in the converged packet networks, and yet they are simple enough for a fair and generic analysis of technologies. The thesis consists of publications and inventions created by the author that proposed several improvements to the 3G technologies towards the LTE. In the system analysis, the LTE showed by the factor of at least 2.5 to 3 times higher system measures compared to the WCDMA/HSPA reference. The WCDMA/HSPA networks are currently available with over 400 million subscribers and showing increasing growth, in the meanwhile the first LTE roll-outs are scheduled to begin in 2010. Sophisticated 3G LTE mobile devices are expected to appear fluently for all consumer segments in the following years

    Quality of service and channel-aware packet bundling for capacity improvement in cellular networks

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    Title from PDF of title page, viewed on May 26, 2011VitaIncludes bibliographical references (p. 76-84)Thesis (Ph.D.)--School of Computing and Engineering. University of Missouri--Kansas City, 2011We study the problem of multiple packet bundling to improve spectral efficiency in cellular networks. The packet size of real-time data, such as VoIP, is often very small. However, the common use of time division multiplexing limits the number of VoIP users supported, because a packet has to wait until it receives a time slot, and if only one small VoIP packet is placed in a time slot, capacity is wasted. Packet bundling can alleviate such a problem by sharing a time slot among multiple users. A recent revision of cdma2000 1xEV-DO introduced the concept of the multi-user packet (MUP) in the downlink to overcome limitations on the number of time slots. However, the efficacy of packet bundling is not well understood, particularly in the presence of time varying channels. We propose a novel QoS and channel-aware packet bundling algorithm that takes advantage of adaptive modulation and coding. We show that optimal algorithms are NP complete and recommend heuristic approaches. We also show that channel utilization can be significantly increased by slightly delaying some real-time packets within their QoS requirements while bundling those packets with like channel conditions. We validate our study through extensive OPNET simulations with a complete EV-DO implementation.Introduction -- Related work -- Background on wireless systems -- Multiple packet bundling -- Evaluation -- Conclusion

    Radio resource management and metric estimation for multicarrier CDMA systems

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

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    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

    Scheduling algorithms for next generation cellular networks

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    Next generation wireless and mobile communication systems are rapidly evolving to satisfy the demands of users. Due to spectrum scarcity and time-varying nature of wireless networks, supporting user demand and achieving high performance necessitate the design of efficient scheduling and resource allocation algorithms. Opportunistic scheduling is a key mechanism for such a design, which exploits the time-varying nature of the wireless environment for improving the performance of wireless systems. In this thesis, our aim is to investigate various categories of practical scheduling problems and to design efficient policies with provably optimal or near-optimal performance. An advantage of opportunistic scheduling is that it can effectively be incorporated with new communication technologies to further increase the network performance. We investigate two key technologies in this context. First, motivated by the current under-utilization of wireless spectrum, we characterize optimal scheduling policies for wireless cognitive radio networks by assuming that users always have data to transmit. We consider cooperative schemes in which secondary users share the time slot with primary users in return for cooperation, and our aim is to improve the primary systems performance over the non-cooperative case. By employing Lyapunov Optimization technique, we develop optimal scheduling algorithms which maximize the total expected utility and satisfy the minimum data rate requirements of the primary users. Next, we study scheduling problem with multi-packet transmission. The motivation behind multi-packet transmission comes from the fact that the base station can send more than one packets simultaneously to more than one users. By considering unsaturated queueing systems we aim to stabilize user queues. To this end, we develop a dynamic control algorithm which is able to schedule more than one users in a time slot by employing hierarchical modulation which enables multi-packet transmission. Through Lyapunov Optimization technique, we show that our algorithm is throughput-optimal. We also study the resulting rate region of developed policy and show that it is larger than that of single user scheduling. Despite the advantage of opportunistic scheduling, this mechanism requires that the base station is aware of network conditions such as channel state and queue length information of users. In the second part of this thesis, we turn our attention to the design of scheduling algorithms when complete network information is not available at the scheduler. In this regard, we study three sets of problems where the common objective is to stabilize user queues. Specifically, we first study a cellular downlink network by assuming that channels are identically distributed across time slots and acquiring channel state information of a user consumes a certain fraction of resource which is otherwise used for transmission of data. We develop a joint scheduling and channel probing algorithm which collects channel state information from only those users with su±ciently good channel quality. We also quantify the minimum number of users that must exist to achieve larger rate region than Max-Weight algorithm with complete channel state information. Next, we consider a more practical channel models where channels can be time-correlated (possibly non-stationary) and only a fixed number of channels can be probed. We develop learning based scheduling algorithm which tracks and predicts instantaneous transmission rates of users and makes a joint scheduling and probing decision based on the predicted rates rather than their exact values. We also characterize the achievable rate region of these policies as compared to Max-Weight policy with exact channel state information. Finally, we study a cellular uplink system and develop a fully distributed scheduling algorithm which can perform over general fading channels and does not require explicit control messages passing among the users. When continuous backoff time is allowed, we show that the proposed distributed algorithm can achieve the same performance as that of centralized Max-Weight algorithm in terms of both throughput and delay. When backoff time can take only discrete values, we show that our algorithm can perform well at the expense of low number of mini-slots for collision resolution

    DYNAMIC RESOURCE ALLOCATION FOR MULTIUSER VIDEO STREAMING

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    With the advancement of video compression technology and wide deployment of wired/wireless networks, there is an increasing demand of multiuser video communication services. A multiuser video transmission system should consider not only the reconstructed video quality in the individual-user level but also the service objectives among all users on the network level. There are many design challenges to support multiuser video communication services, such as fading channels, limited radio resources of wireless networks, heterogeneity of video content complexity, delay and decoding dependency constraints of video bitstreams, and mixed integer optimization. To overcome these challenges, a general strategy is to dynamically allocate resources according to the changing environments and requirements, so as to improve the overall system performance and ensure quality of service (QoS) for each user. In this dissertation, we address the aforementioned design challenges from a resource-allocation point of view and two aspects of system and algorithm designs, namely, a cross-layer design that jointly optimizes resource utilization from physical layer to application layer, and multiuser diversity that explores the source and channel heterogeneity among different users. We also address the impacts on systems caused by dynamic environment along time domain and consider the time-heterogeneity of video sources and time-varying characteristics of channel conditions. To achieve the desired service objectives, a general resource allocation framework is formulated in terms of constrained optimization problems to dynamically allocate resources and control the quality of multiple video bitstreams. Based on the design methodology of multiuser cross-layer optimization, we propose several systems to efficiently transmit multiple video streams, encoded by current and emerging video codecs, over major types of wireless networks such as 3G cellular system, Wireless Local Area Network, 4G cellular system, and future Wireless Metropolitan Area Networks. Owing to the integer nature of some system parameters, the formulated optimization problems are often integer or mixed integer programming problem and involve high computation to search the optimal solutions. Fast algorithms are proposed to provide real-time services. We demonstrate the advantages of dynamic and joint resource allocation for multiple video sources compared to static strategy. We also show the improvement of exploring diversity on frequency, time, and transmission path, and the benefits from multiuser cross-layer optimization

    Sustainable scheduling policies for radio access networks based on LTE technology

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    A thesis submitted to the University of Bedfordshire in partial fulfilment of the requirements for the degree of Doctor of PhilosophyIn the LTE access networks, the Radio Resource Management (RRM) is one of the most important modules which is responsible for handling the overall management of radio resources. The packet scheduler is a particular sub-module which assigns the existing radio resources to each user in order to deliver the requested services in the most efficient manner. Data packets are scheduled dynamically at every Transmission Time Interval (TTI), a time window used to take the user’s requests and to respond them accordingly. The scheduling procedure is conducted by using scheduling rules which select different users to be scheduled at each TTI based on some priority metrics. Various scheduling rules exist and they behave differently by balancing the scheduler performance in the direction imposed by one of the following objectives: increasing the system throughput, maintaining the user fairness, respecting the Guaranteed Bit Rate (GBR), Head of Line (HoL) packet delay, packet loss rate and queue stability requirements. Most of the static scheduling rules follow the sequential multi-objective optimization in the sense that when the first targeted objective is satisfied, then other objectives can be prioritized. When the targeted scheduling objective(s) can be satisfied at each TTI, the LTE scheduler is considered to be optimal or feasible. So, the scheduling performance depends on the exploited rule being focused on particular objectives. This study aims to increase the percentage of feasible TTIs for a given downlink transmission by applying a mixture of scheduling rules instead of using one discipline adopted across the entire scheduling session. Two types of optimization problems are proposed in this sense: Dynamic Scheduling Rule based Sequential Multi-Objective Optimization (DSR-SMOO) when the applied scheduling rules address the same objective and Dynamic Scheduling Rule based Concurrent Multi-Objective Optimization (DSR-CMOO) if the pool of rules addresses different scheduling objectives. The best way of solving such complex optimization problems is to adapt and to refine scheduling policies which are able to call different rules at each TTI based on the best matching scheduler conditions (states). The idea is to develop a set of non-linear functions which maps the scheduler state at each TTI in optimal distribution probabilities of selecting the best scheduling rule. Due to the multi-dimensional and continuous characteristics of the scheduler state space, the scheduling functions should be approximated. Moreover, the function approximations are learned through the interaction with the RRM environment. The Reinforcement Learning (RL) algorithms are used in this sense in order to evaluate and to refine the scheduling policies for the considered DSR-SMOO/CMOO optimization problems. The neural networks are used to train the non-linear mapping functions based on the interaction among the intelligent controller, the LTE packet scheduler and the RRM environment. In order to enhance the convergence in the feasible state and to reduce the scheduler state space dimension, meta-heuristic approaches are used for the channel statement aggregation. Simulation results show that the proposed aggregation scheme is able to outperform other heuristic methods. When the aggregation scheme of the channel statements is exploited, the proposed DSR-SMOO/CMOO problems focusing on different objectives which are solved by using various RL approaches are able to: increase the mean percentage of feasible TTIs, minimize the number of TTIs when the RL approaches punish the actions taken TTI-by-TTI, and minimize the variation of the performance indicators when different simulations are launched in parallel. This way, the obtained scheduling policies being focused on the multi-objective criteria are sustainable. Keywords: LTE, packet scheduling, scheduling rules, multi-objective optimization, reinforcement learning, channel, aggregation, scheduling policies, sustainable
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