11 research outputs found

    Sparsity-aware multiple relay selection in large multi-hop decode-and-forward relay networks

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    In this paper, we propose and investigate two novel techniques to perform multiple relay selection in large multi-hop decode-and-forward relay networks. The two proposed techniques exploit sparse signal recovery theory to select multiple relays using the orthogonal matching pursuit algorithm and outperform state-of-the-art techniques in terms of outage probability and computation complexity. To reduce the amount of collected channel state information (CSI), we propose a limited-feedback scheme where only a limited number of relays feedback their CSI. Furthermore, a detailed performance-complexity tradeoff investigation is conducted for the different studied techniques and verified by Monte Carlo simulations.NPRP grant 6-070-2-024 from the Qatar National Research Fund (a member of Qatar Foundation)Scopu

    Hierarchical Coverage Extension in Self-organising Wireless Network Systems

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    Future self-organising ad hoc networks (MANETs) will provide Internet access for ubiquitous wireless computing. In combination with cellular systems, e.g., B3G and 4G networks, self-organising networks will increase the coverage of cellular systems. The advantage of the so-called coverage extension is that there is no demand for extension of cost-intensive infrastructure, yet it extends network access where no coverage is provided by network operators. This paper extends studies of other related and ongoing work regarding the integration of ad hoc networks in cellular systems and coverage extension based on a complete network topology, which has been implemented for this research. A simulation study is presented in this paper with an evaluation of coverage extension methods in a free scalable hierarchical network environment and considers a trade-off discussion based on a scalable coverage area including various numbers of ad hoc nodes and base station

    Minimize end-to-end delay through cross-layer optimization in multi-hop wireless sensor networks

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    End-to-end delay plays a very important role in wireless sensor networks. It refers to the total time taken for a single packet to be transmitted across a network from source to destination. There are many factors could affect the end-to-end delay, among them the routing path and the interference level along the path are the two basic elements that could have significant influence on the result of the end-to-end delay. This thesis presents a transmission scheduling scheme that minimizes the end-to-end delay when the node topology is given. The transmission scheduling scheme is designed based on integer linear programming and the interference modeling is involved. By using this scheme, we can guarantee that no conflicting transmission will appear at any time during the transmission. A method of assigning the time slot based on the given routing is presented. The simulation results show that the link scheduling scheme can significantly reduce the end-to-end delay. Further, this article also shows two methods which could directly addresses routing and slot assignment, one is MI+MinDelay algorithm and the other is called One-Phase algorithm. A comparison was made between the two and the simulation result shows the latter one leads to smaller latency while it takes much more time to be solved. Besides, due to the different routing policy, we also demonstrate that the shortest path routing does not necessarily result in minimum end-to-end delay --Abstract, page ii

    Power-efficient resource allocation in a heterogeneous network with cellular and D2D capabilities

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    This paper focuses on a heterogeneous scenario in which cellular and wireless local area technologies coexist and in which mobile devices are enabled with device-to-device communication capabilities. In this context, this paper assumes a network architecture in which a given user equipment (UE) can receive mobile service either by connecting directly to a cellular base station or by connecting through another UE that acts as an access point and relays the traffic from a cellular base station. The paper investigates the optimization of the connectivity of different UEs with the target to minimize the total transmission power. An optimization framework is presented, and a distributed strategy based on Q-learning and softmax decision making is proposed as a means to solve the considered problem with reduced complexity. The proposed strategy is evaluated under different conditions, and it is shown that the strategy achieves a performance very close to the optimum. Moreover, significant transmission power reductions of approximately 40% are obtained with respect to the classical approach, in which all UEs are connected to the cellular infrastructure. For multi-cell scenarios, in which the optimum solution cannot be easily known a priori, the proposed approach is compared against a centralized genetic algorithm. The proposed approach achieves similar performance in terms of total transmitted power, while exhibiting much lower computational requirements.Peer ReviewedPostprint (author's final draft

    Mobile agent based distributed network management : modeling, methodologies and applications

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    The explosive growth of the Internet and the continued dramatic increase for all wireless services are fueling the demand for increased capacity, data rates, support of multimedia services, and support for different Quality of Services (QoS) requirements for different classes of services. Furthermore future communication networks will be strongly characterized by heterogeneity. In order to meet the objectives of instant adaptability to the users\u27 requirements and of interoperability and seamless operation within the heterogeneous networking environments, flexibility in terms of network and resource management will be a key design issue. The new emerging technology of mobile agent (MA) has arisen in the distributed programming field as a potential flexible way of managing resources of a distributed system, and is a challenging opportunity for delivering more flexible services and dealing with network programmability. This dissertation mainly focuses on: a) the design of models that provide a generic framework for the evaluation and analysis of the performance and tradeoffs of the mobile agent management paradigm; b) the development of MA based resource and network management applications. First, in order to demonstrate the use and benefits of the mobile agent based management paradigm in the network and resource management process, a commercial application of a multioperator network is introduced, and the use of agents to provide the underlying framework and structure for its implementation and deployment is investigated. Then, a general analytical model and framework for the evaluation of various network management paradigms is introduced and discussed. It is also illustrated how the developed analytical framework can be used to quantitatively evaluate the performances and tradeoffs in the various computing paradigms. Furthermore, the design tradeoffs for choosing the MA based management paradigm to develop a flexible resource management scheme in wireless networks is discussed and evaluated. The integration of an advanced bandwidth reservation mechanism with a bandwidth reconfiguration based call admission control strategy is also proposed. A framework based on the technology of mobile agents, is introduced for the efficient implementation of the proposed integrated resource and QoS management, while the achievable performance of the overall proposed management scheme is evaluated via modeling and simulation. Finally the use of a distributed cooperative scheme among the mobile agents that can be applied in the future wireless networks is proposed and demonstrated, to improve the energy consumption for the routine management processes of mobile terminals, by adopting the peer-to-peer communication concept of wireless ad-hoc networks. The performance evaluation process and the corresponding numerical results demonstrate the significant system energy savings, while several design issues and tradeoffs of the proposed scheme, such as the fairness of the mobile agents involved in the management activity, are discussed and evaluated

    Cooperative control of relay based cellular networks

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    PhDThe increasing popularity of wireless communications and the higher data requirements of new types of service lead to higher demands on wireless networks. Relay based cellular networks have been seen as an effective way to meet users’ increased data rate requirements while still retaining the benefits of a cellular structure. However, maximizing the probability of providing service and spectrum efficiency are still major challenges for network operators and engineers because of the heterogeneous traffic demands, hard-to-predict user movements and complex traffic models. In a mobile network, load balancing is recognised as an efficient way to increase the utilization of limited frequency spectrum at reasonable costs. Cooperative control based on geographic load balancing is employed to provide flexibility for relay based cellular networks and to respond to changes in the environment. According to the potential capability of existing antenna systems, adaptive radio frequency domain control in the physical layer is explored to provide coverage at the right place at the right time. This thesis proposes several effective and efficient approaches to improve spectrum efficiency using network wide optimization to coordinate the coverage offered by different network components according to the antenna models and relay station capability. The approaches include tilting of antenna sectors, changing the power of omni-directional antennas, and changing the assignment of relay stations to different base stations. Experiments show that the proposed approaches offer significant improvements and robustness in heterogeneous traffic scenarios and when the propagation environment changes. The issue of predicting the consequence of cooperative decisions regarding antenna configurations when applied in a realistic environment is described, and a coverage prediction model is proposed. The consequences of applying changes to the antenna configuration on handovers are analysed in detail. The performance evaluations are based on a system level simulator in the context of Mobile WiMAX technology, but the concepts apply more generally

    Distributed space time block coding in asynchronous cooperative relay networks

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    The design and analysis of various distributed space time block coding schemes for asynchronous cooperative relay networks is considered in this thesis. Rayleigh frequency flat fading channels are assumed to model the links in the networks, and interference suppression techniques together with an orthogonal frequency division multiplexing type transmission approach are employed to mitigate the synchronization errors at the destination node induced by the different delays through the relay nodes. Closed-loop space time block coding is first considered in the context of decode-and-forward (regenerative) networks. In particular, quasi orthogonal and extended orthogonal coding techniques are employed for transmission from four relay nodes and parallel interference cancellation detection is exploited to mitigate synchronization errors. Availability of a direct link between the source and destination nodes is studied, and a new Alamouti space time block coding technique with parallel interference cancellation detection which does not require such a direct link connection and employs two relay nodes is proposed. Outer coding is then added to gain further improvement in end-to-end performance and amplify-and-forward (non regenerative) type networks together with distributed space time coding are considered to reduce relay node complexity. Novel detection schemes are then proposed for decode-and-forward networks with closed-loop extended orthogonal coding which reduce the computational complexity of the parallel interference cancellation. Both sub-optimum and near-optimum detectors are presented for relay nodes with single or dual antennas. End-to-end bit error rate simulations confirm the potential of the approaches and their ability to mitigate synchronization errors. A relay selection approach is also formulated which maximizes spatial diversity gain and attains robustness to timing errors. Finally, a new closed-loop distributed extended orthogonal space time block coding solution for amplify-and-forward type networks which minimizes the number of feedback bits by using a cyclic rotation phase is presented. This approach utilizes an orthogonal frequency division multiplexing type transmission structure with a cyclic prefix to mitigate synchronization errors. End-to-end bit error performance evaluations verify the efficacy of the scheme and its success in overcoming synchronization errors

    Cognitive network framework for heterogeneous wireless mesh systems

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    Heterogeneous wireless mesh networks (WMN) provide an opportunity to secure higher network capacity, wider coverage and higher quality of service (QoS). However, heterogeneous systems are complex to configure because of the high diversity of associated devices and resources. This thesis introduces a novel cognitive network framework that allows the integration of WMNs with long-term evolution (LTE) networks so that none of the overlapped frequency bands are used. The framework consists of three novel systems: the QoS metrics management system, the heterogeneous network management system and the routing decision-making system. The novelty of the QoS metrics management system is that it introduces a new routing metric for multi-hop wireless networks by developing a new rate adaptation algorithm. This system directly addresses the interference between neighbouring nodes, which has not been addressed in previous research on rate adaptation for WMN. The results indicated that there was a significant improvement in the system throughput by as much as to 90%. The routing decision-making system introduces two novel methods to select the transmission technology in heterogeneous nodes: the cognitive heterogeneous routing (CHR) system and the semantic reasoning system. The CHR method is used to develop a novel reinforcement learning algorithm to optimise the selection of transmission technology on wireless heterogeneous nodes by learning from previous actions. The semantic reasoning method uses ontologies and fuzzy-based semantic reasoning to facilitate the dynamic addition of new network types to the heterogeneous network. The simulation results showed that the heterogeneous network outperformed the benchmark networks by up to 200% of the network throughput
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