1,115 research outputs found

    Matching Theory for Future Wireless Networks: Fundamentals and Applications

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    The emergence of novel wireless networking paradigms such as small cell and cognitive radio networks has forever transformed the way in which wireless systems are operated. In particular, the need for self-organizing solutions to manage the scarce spectral resources has become a prevalent theme in many emerging wireless systems. In this paper, the first comprehensive tutorial on the use of matching theory, a Nobelprize winning framework, for resource management in wireless networks is developed. To cater for the unique features of emerging wireless networks, a novel, wireless-oriented classification of matching theory is proposed. Then, the key solution concepts and algorithmic implementations of this framework are exposed. Then, the developed concepts are applied in three important wireless networking areas in order to demonstrate the usefulness of this analytical tool. Results show how matching theory can effectively improve the performance of resource allocation in all three applications discussed

    Energy-Efficient Matching for Resource Allocation in D2D Enabled Cellular Networks

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    Energy-efficiency (EE) is critical for device-to-device (D2D) enabled cellular networks due to limited battery capacity and severe co-channel interference. In this paper, we address the EE optimization problem by adopting a stable matching approach. The NP-hard joint resource allocation problem is formulated as a one-to-one matching problem under two-sided preferences, which vary dynamically with channel states and interference levels. A game-theoretic approach is employed to analyze the interactions and correlations among user equipments (UEs), and an iterative power allocation algorithm is developed to establish mutual preferences based on nonlinear fractional programming. We then employ the Gale-Shapley (GS) algorithm to match D2D pairs with cellular UEs (CUs), which is proved to be stable and weak Pareto optimal. We provide a theoretical analysis and description for implementation details and algorithmic complexity. We also extend the algorithm to address scalability issues in large-scale networks by developing tie-breaking and preference deletion based matching rules. Simulation results validate the theoretical analysis and demonstrate that significant performance gains of average EE and matching satisfactions can be achieved by the proposed algorithm

    Relay assisted device-to-device communication with channel uncertainty

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    The gains of direct communication between user equipment in a network may not be fully realised due to the separation between the user equipment and due to the fading that the channel between these user equipment experiences. In order to fully realise the gains that direct (device-to-device) communication promises, idle user equipment can be exploited to serve as relays to enforce device-to-device communication. The availability of potential relay user equipment creates a problem: a way to select the relay user equipment. Moreover, unlike infrastructure relays, user equipment are carried around by people and these users are self-interested. Thus the problem of relay selection goes beyond choosing which device to assist in relayed communication but catering for user self-interest. Another problem in wireless communication is the unavailability of perfect channel state information. This reality creates uncertainty in the channel and so in designing selection algorithms, channel uncertainty awareness needs to be a consideration. Therefore the work in this thesis considers the design of relay user equipment selection algorithms that are not only device centric but that are relay user equipment centric. Furthermore, the designed algorithms are channel uncertainty aware. Firstly, a stable matching based relay user equipment selection algorithm is put forward for underlay device-to-device communication. A channel uncertainty aware approach is proposed to cater to imperfect channel state information at the devices. The algorithm is combined with a rate based mode selection algorithm. Next, to cater to the queue state at the relay user equipment, a cross-layer selection algorithm is proposed for a twoway decode and forward relay set up. The algorithm proposed employs deterministic uncertainty constraint in the interference channel, solving the selection algorithm in a heuristic fashion. Then a cluster head selection algorithm is proposed for device-to-device group communication constrained by channel uncertainty in the interference channel. The formulated rate maximization problem is solved for deterministic and probabilistic constraint scenarios, and the problem extended to a multiple-input single-out scenario for which robust beamforming was designed. Finally, relay utility and social distance based selection algorithms are proposed for full duplex decode and forward device-to-device communication set up. A worst-case approach is proposed for a full channel uncertainty scenario. The results from computer simulations indicate that the proposed algorithms offer spectral efficiency, fairness and energy efficiency gains. The results also showed clearly the deterioration in the performance of networks when perfect channel state information is assumed

    Matching Theory Framework for 5G Wireless Communications

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    The prevalence of high-performance mobile devices such as smartphones and tablets has brought fundamental changes to the existing wireless networks. The growth of multimedia and location-based mobile services has exponentially increased the network congestion and the demands for more wireless resources. The extremely high computational complexity and communication overhead resulting from the conventional centralized resource management methods are no longer suitable to capture the scale of tomorrow’s wireless networks. As a result, the resource management in next-generation networks is shifting from the centralized optimization to the self-organizing solutions. The goal of this thesis is to demonstrate the effectiveness of matching theory, a powerful operational research framework, for solving the wireless resource allocation problems in a distributed manner. Matching theory, as a Nobel-prize winning framework, has already been widely used in many economic fields. More recently, matching theory has been shown to have a promising potential for modeling and analyzing wireless resource allocation problems due to three reasons: (1) it offers suitable models that can inherently capture various wireless communication features; (2) the ability to use notions, such as preference relations, that can interpret complex system requirements; (3) it provides low-complexity and near-optimal matching algorithms while guaranteeing the system stability. This dissertation provides a theoretical research of implementing the matching theory into the wireless communication fields. The main contributions of this dissertation are summarized as follows. An overview of the basic concepts, classifications, and models of the matching theory is provided. Furthermore, comparisons with existing mathematical solutions for the resource allocation problems in the wireless networks are conducted. Applications of matching theory in the wireless communications are studied. Especially, the stable marriage model, the student project allocation model and so on are introduced and applied to solve the resource allocation problems, such as the device-to-device (D2D) communication, LTE-Unlicensed, and so on. Both theoretical and numerical analysis are provided to show that matching theory can model complex system requirements, and also provide semi-distributive matching algorithms to achieve stable and close-optimal results. The potential and challenges of the matching theory for designing resource allocation mechanisms in the future wireless networks are discussed.Electrical and Computer Engineering, Department o

    Interference Management of Inband Underlay Device-toDevice Communication in 5G Cellular Networks

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    The explosive growth of data traffic demands, emanating from smart mobile devices and bandwidth-consuming applications on the cellular network poses the need to drastically modify the cellular network architecture. A challenge faced by the network operators is the inability of the finite spectral resources to support the growing data traffic. The Next Generation Network (NGN) is expected to meet defined requirements such as massively connecting billions of devices with heterogeneous applications and services through enhanced mobile broadband networks, which provides higher data rates with improved network reliability and availability, lower end-to-end latency and increased energy efficiency. Device-to-Device (D2D) communication is one of the several emerging technologies that has been proposed to support NGN in meeting these aforementioned requirements. D2D communication leverages the proximity of users to provide direct communication with or without traversing the base station. Hence, the integration of D2D communication into cellular networks provides potential gains in terms of throughput, energy efficiency, network capacity and spectrum efficiency. D2D communication underlaying a cellular network provides efficient utilisation of the scarce spectral resources, however, there is an introduction of interference emanating from the reuse of cellular channels by D2D pairs. Hence, this dissertation focuses on the technical challenge with regards to interference management in underlay D2D communication. In order to tackle this challenge to be able to exploit the potentials of D2D communication, there is the need to answer some important research questions concerning the problem. Thus, the study aims to find out how cellular channels can be efficiently allocated to D2D pairs for reuse as an underlay to cellular network, and how mode selection and power control approaches influence the degree of interference caused by D2D pairs to cellular users. Also, the research study continues to determine how the quality of D2D communication can be maintained with factors such as bad channel quality or increased distance. In addressing these research questions, resource management techniques of mode selection, power control, relay selection and channel allocation are applied to minimise the interference caused by D2D pairs when reusing cellular channels to guarantee the Quality of Service (QoS) of cellular users, while optimally improving the number of permitted D2D pairs to reuse channels. The concept of Open loop power control scheme is examined in D2D communication underlaying cellular network. The performance of the fractional open loop power control components on SINR is studied. The simulation results portrayed that the conventional open loop power control method provides increased compensation for the path loss with higher D2D transmit power when compared with the fractional open loop power control method. Furthermore, the problem of channel allocation to minimise interference is modelled in two system model scenarios, consisting of cellular users coexisting with D2D pairs with or without relay assistance. The channel allocation problem is solved as an assignment problem by using a proposed heuristic channel allocation, random channel allocation, Kuhn-Munkres (KM) and Gale-Shapley (GS) algorithms. A comparative performance evaluation for the algorithms are carried out in the two system model scenarios, and the results indicated that D2D communication with relay assistance outperformed the conventional D2D communication without relay assistance. This concludes that the introduction of relay-assisted D2D communication can improve the quality of a network while utilising the available spectral resources without additional infrastructure deployment costs. The research work can be extended to apply an effective relay selection approach for a user mobility scenario
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