22 research outputs found

    Uplink blocking probabilities in priority-based cellular CDMA networks with finite source population

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    Fast proliferation of mobile Internet and high-demand mobile applications necessitates the introduction of different priority classes in next-generation cellular networks. This is especially crucial for efficient use of radio resources in the heterogeneous and virtualized network environments. Despite the fact that many analytical tools have been proposed for capacity and radio resource modelling in cellular networks, only a few of them explicitly incorporate priorities among services. We propose a novel analytical model to analyse the performance of a priority-based cellular CDMA system with finite source population. When the cell load is above a certain level, low-priority calls may be blocked to preserve the quality of service of high-priority calls. The proposed model leads to an efficient closed-form solution that enables fast and very accurate calculation of resource occupancy of the CDMA system and call blocking probabilities, for different services and many priority classes. To achieve them, the system is modelled as a continuous-time Markov chain. We evaluate the accuracy of the proposed analytical model by means of computer simulations and find that the introduced approximation errors are negligible

    A study of teletraffic problems in multicast networks

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    This dissertation studies teletraffic engineering of dynamic multicast connections. The traditional models in teletraffic engineering do not handle multicast connections properly, since in a dynamic multicast tree, users may join and leave the connection freely, and thus the multicast tree evolves in time. A model called multicast loss system is used to calculate blocking probabilities in a single link and in tree-type networks. In a single link case, the problem is a generalised Engset problem, and a method for calculating call blocking probabilities for users is presented. Application of the reduced load approximation for multicast connections is studied. Blocking probabilities in a cellular system are studied by means of simulation. The analysis is mainly concentrated on tree type networks, where convolution-truncation algorithms and simulation methods for solving the blocking probabilities exactly are derived. Both single layer and hierarchically coded streams are treated. The presented algorithms reduce significantly the computational complexity of the problem, compared to direct calculation from the system state space. An approximative method is given for background traffic. The simulation method presented is an application of the Inverse Convolution Monte-Carlo method, and it gives a considerable variance reduction, and thus allows simulation with smaller sample sizes than with traditional simulation methods. Signalling load for dynamic multicast connections in a node depends on the shape of the tree as well as the location of the node in the tree. This dissertation presents a method for calculating the portion of signalling load that is caused by call establishments and tear-downs.reviewe

    Introduction to Queueing Theory and Stochastic Teletraffic Models

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    The aim of this textbook is to provide students with basic knowledge of stochastic models that may apply to telecommunications research areas, such as traffic modelling, resource provisioning and traffic management. These study areas are often collectively called teletraffic. This book assumes prior knowledge of a programming language, mathematics, probability and stochastic processes normally taught in an electrical engineering course. For students who have some but not sufficiently strong background in probability and stochastic processes, we provide, in the first few chapters, background on the relevant concepts in these areas.Comment: 298 page

    Teletraffic engineering and network planning

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    Quantum Reinforcement Learning for Dynamic Spectrum Access in Cognitive Radio Networks

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    Abstract This thesis proposes Quantum Reinforcement Learning (QRL) as an improvement to conventional reinforcement learning-based dynamic spectrum access used within cognitive radio networks. The aim is to overcome the slow convergence problem associated with exploration within reinforcement learning schemes. A literature review for the background of the carried out research work is illustrated. Review of research works on learning-based assignment techniques as well as quantum search techniques is provided. Modelling of three traditional dynamic channel assignment techniques is illustrated and the advantage characteristic of each technique is discussed. These techniques have been simulated to provide a comparison with learning based techniques, including QRL. Reinforcement learning techniques are used as a direct comparison with the Quantum Reinforcement Learning approaches. The elements of Quantum computation are then presented as an introduction to quantum search techniques. The Grover search algorithm is introduced. The algorithm is discussed from a theoretical perspective. The Grover algorithm is then used for the first time as a spectrum allocation scheme and compared to conventional schemes. Quantum Reinforcement Learning (QRL) is introduced as a natural evolution of the quantum search. The Grover search algorithm is combined as a decision making mechanism with conventional Reinforcement Learning (RL) algorithms resulting in a more efficient learning engine. Simulation results are provided and discussed. The convergence speed has been significantly increased. The beneficial effects of Quantum Reinforcement Learning (QRL) become more pronounced as the traffic load increases. The thesis shows that both system performance and capacity can be improved. Depending on the traffic load, the system capacity has improved by 9-84% from a number of users supported perspective. It also demonstrated file delay reduction for up to an average of 26% and 2.8% throughput improvement

    Efficient radio resource allocation in SDN/NFV based mobile cellular networks under the complete sharing policy

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    Novel networking paradigms, such as software-defined networking (SDN) and network function virtualisation (NFV), introduce new opportunities in the design of next-generation mobile networks. The present work investigates the benefits of the emerging SDN and NFV technologies on the radio resource management (RRM) in mobile cellular networks. In particular, the aim of the proposed RRM scheme is to enable an efficient and flexible radio resource allocation in order to assure quality of experience of mobile users. The authors consider the orthogonal frequency division multiple access scheme and the complete radio resource sharing policy. To enable time- and space-efficient resource allocation, the authors investigate the applicability of the well-known Kaufman–Roberts recursion in the context of new architectural and functional changes of SDN/NFV based mobile environments. Finally, they discuss the applicability of the proposed approach for more complicated resource sharing policies

    On a Bicriterion Server Allocation Problem for a Multidimensional Erlang Loss System

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    In this work an optimization problem on a classical elementary stochastic system system, modeled as an Erlang-B (M/M/x) loss system, is formulated by using a bicriteria approach. The problem is focused on the allocation of a given total of k servers to a number of groups of servers capable of carrying certain offered traffic processes assumed as Poissonian in nature. Two main objectives are present in this formulation. Firstly a criterion of equity in the grade of service, measured by the call blocking probabilities, entails that the absolute difference between the blocking probabilities experienced by the calls in the different service groups must be as small as possible. Secondly a criterion of system economic performance optimization requires the total traffic carried by the system, to be maximized. Relevant mathematical results characterizing the two objective functions and the set N of the non-dominated solutions, are presented. An algorithm for traveling on N based on the resolution of single criterion convex problems, using a Newton-Raphson method, is also proposed. In each iteration the two first derivatives of the Erlang-B function in the number of circuits (a difficult numerical problem) are calculated using a method earlier proposed. Some computational results are also presented

    Product forms for queueing networks with limited clusters

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