3,712 research outputs found

    Green Cellular Networks: A Survey, Some Research Issues and Challenges

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    Energy efficiency in cellular networks is a growing concern for cellular operators to not only maintain profitability, but also to reduce the overall environment effects. This emerging trend of achieving energy efficiency in cellular networks is motivating the standardization authorities and network operators to continuously explore future technologies in order to bring improvements in the entire network infrastructure. In this article, we present a brief survey of methods to improve the power efficiency of cellular networks, explore some research issues and challenges and suggest some techniques to enable an energy efficient or "green" cellular network. Since base stations consume a maximum portion of the total energy used in a cellular system, we will first provide a comprehensive survey on techniques to obtain energy savings in base stations. Next, we discuss how heterogeneous network deployment based on micro, pico and femto-cells can be used to achieve this goal. Since cognitive radio and cooperative relaying are undisputed future technologies in this regard, we propose a research vision to make these technologies more energy efficient. Lastly, we explore some broader perspectives in realizing a "green" cellular network technologyComment: 16 pages, 5 figures, 2 table

    Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey

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    Wireless sensor networks (WSNs) consist of autonomous and resource-limited devices. The devices cooperate to monitor one or more physical phenomena within an area of interest. WSNs operate as stochastic systems because of randomness in the monitored environments. For long service time and low maintenance cost, WSNs require adaptive and robust methods to address data exchange, topology formulation, resource and power optimization, sensing coverage and object detection, and security challenges. In these problems, sensor nodes are to make optimized decisions from a set of accessible strategies to achieve design goals. This survey reviews numerous applications of the Markov decision process (MDP) framework, a powerful decision-making tool to develop adaptive algorithms and protocols for WSNs. Furthermore, various solution methods are discussed and compared to serve as a guide for using MDPs in WSNs

    Robotic Wireless Sensor Networks

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    In this chapter, we present a literature survey of an emerging, cutting-edge, and multi-disciplinary field of research at the intersection of Robotics and Wireless Sensor Networks (WSN) which we refer to as Robotic Wireless Sensor Networks (RWSN). We define a RWSN as an autonomous networked multi-robot system that aims to achieve certain sensing goals while meeting and maintaining certain communication performance requirements, through cooperative control, learning and adaptation. While both of the component areas, i.e., Robotics and WSN, are very well-known and well-explored, there exist a whole set of new opportunities and research directions at the intersection of these two fields which are relatively or even completely unexplored. One such example would be the use of a set of robotic routers to set up a temporary communication path between a sender and a receiver that uses the controlled mobility to the advantage of packet routing. We find that there exist only a limited number of articles to be directly categorized as RWSN related works whereas there exist a range of articles in the robotics and the WSN literature that are also relevant to this new field of research. To connect the dots, we first identify the core problems and research trends related to RWSN such as connectivity, localization, routing, and robust flow of information. Next, we classify the existing research on RWSN as well as the relevant state-of-the-arts from robotics and WSN community according to the problems and trends identified in the first step. Lastly, we analyze what is missing in the existing literature, and identify topics that require more research attention in the future

    Cooperative Communications in Smart Grid Networks

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    The conventional grid system is facing great challenges due to the fast growing electricity demand throughout the world. The smart grid has emerged as the next generation of grid power systems, aimed at providing secure, reliable and low cost power generation, distribution and consumption intelligently. The smart grid communication system within the smart grid network is of fundamental importance to support data transfer and information exchange within the smart grid system. The National Institute of Standards and Technology has identified wireless communications as an important networking technology to be employed in power systems. The reliability of the data transmission is essential for the smart grid system to achieve high accuracy for the power generation, distribution and consumption. In this thesis, we investigate cooperative communications to improve transmission reliability in smart grid networks. Although many issues within cooperative communication have already been addressed, there is a lack of research efforts on cooperative communication for the wireless smart grid communication system which has its own network features and different transmission requirements. In our research, the smart grid communication networks were studied, and cooperative communications in smart grid networks were analysed. The research work mainly focuses on three problems: the application of cooperative relay communications to modern smart grid communication networks, the cooperative relay-based network development strategy, and the optimization of cooperative relay communication for smart grids. For the first problem, the application of cooperative relay communication to a home area network (HAN) of smart grid system is presented. The wireless transmission reliability is identified as the issue of most concern in wireless smart grid networks. We model the smart grid HAN as a wireless mesh network that deploys cooperative relay communication to enhance the transmission reliability. We apply cooperative relay communication to provide a user equipment selection scheme to effectively improve the transmission quality between the electricity equipment and the smart meter. For the second problem, we address the network design and planning problem in the smart grid HAN. The outage performance of direct transmission and cooperative transmission was analysed. Based on the reliability performance metric that we have defined, we propose a HAN deployment strategy to improve the reliability of the transmission links. The proposed HAN deployment strategy is tested in a home environment. The smart meter location optimization problem has also been identified and solved. The simulation results show that our proposed network deployment strategy can guarantee high reliability for smart grid communications in home area networks. For the third problem, the research focuses on the optimization of the cooperative relay transmission regarding the power allocation and relay selection in the neighbourhood area network (NAN) of the smart grid system. Owing to the complexity of the joint optimization problem, reduced-complexity algorithms have been proposed to minimize the transmission power, at the same time, guarantee the link reliability of the cooperative communications. The optimization problem of power allocation and relay selection is formulated and treated as a combinatorial optimization problem. Two sub-optimal solutions that simplify the optimization process are devised. Based on the solutions, two different algorithms are proposed to solve the optimization problem with reduced complexity. The simulation results demonstrate that both two algorithms have good performance on minimizing the total transmission power while guaranteeing the transmission reliability for the wireless smart grid communication system. In this thesis, we consider cooperative communications in a smart grid scenario. We minimize the outage probability and thus improve the reliability of the communications taking place in the smart grid by considering the optimization problem of power control, relay selection and the network deployment problem. Although similar problems might have been well investigated in conventional wireless networks, such as the cellular network, little research has been conducted in smart grid communications. We apply new optimization techniques and propose solutions for these optimization problems specifically tailored for smart grid communications. We demonstrate that, compared to naively applying the algorithms suitable for conventional communications to the smart gird scenario, our proposed algorithm significantly improves the performance of smart grid communications. Finally, we note that, in future work, it will be possible to consider more complex smart grid communications system models. For example, it is worthwhile considering hetregeneous smart communications by combining HAN and wide area networks (WAN). In addition, instead of assuming that all communications have the equal priority, as in this thesis, more comprehensive analysis of the priority of the smart grid communication can be applied to the research

    Drone Base Station Trajectory Management for Optimal Scheduling in LTE-Based Sparse Delay-Sensitive M2M Networks

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    Providing connectivity in areas out of reach of the cellular infrastructure is a very active area of research. This connectivity is particularly needed in case of the deployment of machine type communication devices (MTCDs) for critical purposes such as homeland security. In such applications, MTCDs are deployed in areas that are hard to reach using regular communications infrastructure while the collected data is timely critical. Drone-supported communications constitute a new trend in complementing the reach of the terrestrial communication infrastructure. In this study, drones are used as base stations to provide real-time communication services to gather critical data out of a group of MTCDs that are sparsely deployed in a marine environment. Studying different communication technologies as LTE, WiFi, LPWAN and Free-Space Optical communication (FSOC) incorporated with the drone communications was important in the first phase of this research to identify the best candidate for addressing this need. We have determined the cellular technology, and particularly LTE, to be the most suitable candidate to support such applications. In this case, an LTE base station would be mounted on the drone which will help communicate with the different MTCDs to transmit their data to the network backhaul. We then formulate the problem model mathematically and devise the trajectory planning and scheduling algorithm that decides the drone path and the resulting scheduling. Based on this formulation, we decided to compare between an Ant Colony Optimization (ACO) based technique that optimizes the drone movement among the sparsely-deployed MTCDs and a Genetic Algorithm (GA) based solution that achieves the same purpose. This optimization is based on minimizing the energy cost of the drone movement while ensuring the data transmission deadline missing is minimized. We present the results of several simulation experiments that validate the different performance aspects of the technique

    Context-aware Cluster Based Device-to-Device Communication to Serve Machine Type Communications

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    Billions of Machine Type Communication (MTC) devices are foreseen to be deployed in next ten years and therefore potentially open a new market for next generation wireless network. However, MTC applications have different characteristics and requirements compared with the services provided by legacy cellular networks. For instance, an MTC device sporadically requires to transmit a small data packet containing information generated by sensors. At the same time, due to the massive deployment of MTC devices, it is inefficient to charge their batteries manually and thus a long battery life is required for MTC devices. In this sense, legacy networks designed to serve human-driven traffics in real time can not support MTC efficiently. In order to improve the availability and battery life of MTC devices, context-aware device-to-device (D2D) communication is exploited in this paper. By applying D2D communication, some MTC users can serve as relays for other MTC users who experience bad channel conditions. Moreover, signaling schemes are also designed to enable the collection of context information and support the proposed D2D communication scheme. Last but not least, a system level simulator is implemented to evaluate the system performance of the proposed technologies and a large performance gain is shown by the numerical results
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