1,406 research outputs found

    Session-Based Cooperation in Cognitive Radio Networks: A Network-Level Approach

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    In cognitive radio networks (CRNs), secondary users (SUs) can proactively obtain spectrum access opportunities by helping with primary users' (PUs') data transmissions. Currently, such kind of spectrum access is implemented via a cooperative communications based link-level frame-based cooperative (LLC) approach where individual SUs independently serve as relays for PUs in order to gain spectrum access opportunities. Unfortunately, this LLC approach cannot fully exploit spectrum access opportunities to enhance the throughput of CRNs and fails to motivate PUs to join the spectrum sharing processes. To address these challenges, we propose a network-level session-based cooperative (NLC) approach where SUs are grouped together to cooperate with PUs session by session, instead of frame by frame as what has been done in existing works, for spectrum access opportunities of the corresponding group. Thanks to our group-based session-by-session cooperating strategy, our NLC approach is able to address all those challenges in the LLC approach. To articulate our NLC approach, we further develop an NLC scheme under a cognitive capacity harvesting network (CCHN) architecture. We formulate the cooperative mechanism design as a cross-layer optimization problem with constraints on primary session selection, flow routing and link scheduling. To search for solutions to the optimization problem, we propose an augmented scheduling index ordering based (SIO-based) algorithm to identify maximal independent sets. Through extensive simulations, we demonstrate the effectiveness of the proposed NLC approach and the superiority of the augmented SIO-based algorithm over the traditional method

    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

    Aeronautical Ad Hoc Networking for the Internet-Above-The-Clouds

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    The engineering vision of relying on the ``smart sky" for supporting air traffic and the ``Internet above the clouds" for in-flight entertainment has become imperative for the future aircraft industry. Aeronautical ad hoc Networking (AANET) constitutes a compelling concept for providing broadband communications above clouds by extending the coverage of Air-to-Ground (A2G) networks to oceanic and remote airspace via autonomous and self-configured wireless networking amongst commercial passenger airplanes. The AANET concept may be viewed as a new member of the family of Mobile ad hoc Networks (MANETs) in action above the clouds. However, AANETs have more dynamic topologies, larger and more variable geographical network size, stricter security requirements and more hostile transmission conditions. These specific characteristics lead to more grave challenges in aircraft mobility modeling, aeronautical channel modeling and interference mitigation as well as in network scheduling and routing. This paper provides an overview of AANET solutions by characterizing the associated scenarios, requirements and challenges. Explicitly, the research addressing the key techniques of AANETs, such as their mobility models, network scheduling and routing, security and interference are reviewed. Furthermore, we also identify the remaining challenges associated with developing AANETs and present their prospective solutions as well as open issues. The design framework of AANETs and the key technical issues are investigated along with some recent research results. Furthermore, a range of performance metrics optimized in designing AANETs and a number of representative multi-objective optimization algorithms are outlined

    Computational Intelligence Inspired Data Delivery for Vehicle-to-Roadside Communications

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    We propose a vehicle-to-roadside communication protocol based on distributed clustering where a coalitional game approach is used to stimulate the vehicles to join a cluster, and a fuzzy logic algorithm is employed to generate stable clusters by considering multiple metrics of vehicle velocity, moving pattern, and signal qualities between vehicles. A reinforcement learning algorithm with game theory based reward allocation is employed to guide each vehicle to select the route that can maximize the whole network performance. The protocol is integrated with a multi-hop data delivery virtualization scheme that works on the top of the transport layer and provides high performance for multi-hop end-to-end data transmissions. We conduct realistic computer simulations to show the performance advantage of the protocol over other approaches

    Reconfigurable Wireless Networks

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    Driven by the advent of sophisticated and ubiquitous applications, and the ever-growing need for information, wireless networks are without a doubt steadily evolving into profoundly more complex and dynamic systems. The user demands are progressively rampant, while application requirements continue to expand in both range and diversity. Future wireless networks, therefore, must be equipped with the ability to handle numerous, albeit challenging requirements. Network reconfiguration, considered as a prominent network paradigm, is envisioned to play a key role in leveraging future network performance and considerably advancing current user experiences. This paper presents a comprehensive overview of reconfigurable wireless networks and an in-depth analysis of reconfiguration at all layers of the protocol stack. Such networks characteristically possess the ability to reconfigure and adapt their hardware and software components and architectures, thus enabling flexible delivery of broad services, as well as sustaining robust operation under highly dynamic conditions. The paper offers a unifying framework for research in reconfigurable wireless networks. This should provide the reader with a holistic view of concepts, methods, and strategies in reconfigurable wireless networks. Focus is given to reconfigurable systems in relatively new and emerging research areas such as cognitive radio networks, cross-layer reconfiguration and software-defined networks. In addition, modern networks have to be intelligent and capable of self-organization. Thus, this paper discusses the concept of network intelligence as a means to enable reconfiguration in highly complex and dynamic networks. Finally, the paper is supported with several examples and case studies showing the tremendous impact of reconfiguration on wireless networks.Comment: 28 pages, 26 figures; Submitted to the Proceedings of the IEEE (a special issue on Reconfigurable Systems

    Hybrid Satellite-Terrestrial Communication Networks for the Maritime Internet of Things: Key Technologies, Opportunities, and Challenges

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    With the rapid development of marine activities, there has been an increasing number of maritime mobile terminals, as well as a growing demand for high-speed and ultra-reliable maritime communications to keep them connected. Traditionally, the maritime Internet of Things (IoT) is enabled by maritime satellites. However, satellites are seriously restricted by their high latency and relatively low data rate. As an alternative, shore & island-based base stations (BSs) can be built to extend the coverage of terrestrial networks using fourth-generation (4G), fifth-generation (5G), and beyond 5G services. Unmanned aerial vehicles can also be exploited to serve as aerial maritime BSs. Despite of all these approaches, there are still open issues for an efficient maritime communication network (MCN). For example, due to the complicated electromagnetic propagation environment, the limited geometrically available BS sites, and rigorous service demands from mission-critical applications, conventional communication and networking theories and methods should be tailored for maritime scenarios. Towards this end, we provide a survey on the demand for maritime communications, the state-of-the-art MCNs, and key technologies for enhancing transmission efficiency, extending network coverage, and provisioning maritime-specific services. Future challenges in developing an environment-aware, service-driven, and integrated satellite-air-ground MCN to be smart enough to utilize external auxiliary information, e.g., sea state and atmosphere conditions, are also discussed

    Statistical Routing for Multihop Wireless Cognitive Networks

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    To account for the randomness of propagation channels and interference levels in hierarchical spectrum sharing, a novel approach to multihop routing is introduced for cognitive random access networks, whereby packets are randomly routed according to outage probabilities. Leveraging channel and interference level statistics, the resultant cross-layer optimization framework provides optimal routes, transmission probabilities, and transmit-powers, thus enabling cognizant adaptation of routing, medium access, and physical layer parameters to the propagation environment. The associated optimization problem is non-convex, and hence hard to solve in general. Nevertheless, a successive convex approximation approach is adopted to efficiently find a Karush-Kuhn-Tucker solution. Augmented Lagrangian and primal decomposition methods are employed to develop a distributed algorithm, which also lends itself to online implementation. Enticingly, the fresh look advocated here permeates benefits also to conventional multihop wireless networks in the presence of channel uncertainty.Comment: Accepted for publication on the IEEE Journal on Selected Areas in Communications - Cognitive Radio Series (Nov 2012 Issue

    System Power Minimization to Access Non-Contiguous Spectrum in Cognitive Radio Networks

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    Wireless transmission using non-contiguous chunks of spectrum is becoming increasingly important due to a variety of scenarios such as: secondary users avoiding incumbent users in TV white space; anticipated spectrum sharing between commercial and military systems; and spectrum sharing among uncoordinated interferers in unlicensed bands. Multi-Channel Multi-Radio (MCMR) platforms and Non-Contiguous Orthogonal Frequency Division Multiple Access (NC-OFDMA) technology are the two commercially viable transmission choices to access these non-contiguous spectrum chunks. Fixed MC-MRs do not scale with increasing number of non-contiguous spectrum chunks due to their fixed set of supporting radio front ends. NC-OFDMA allows nodes to access these non-contiguous spectrum chunks and put null sub-carriers in the remaining chunks. However, nulling sub-carriers increases the sampling rate (spectrum span) which, in turn, increases the power consumption of radio front ends. Our work characterizes this trade-off from a cross-layer perspective, specifically by showing how the slope of ADC/DAC power consumption versus sampling rate curve influences scheduling decisions in a multi-hop network. Specifically, we provide a branch and bound algorithm based mixed integer linear programming solution that performs joint power control, spectrum span selection, scheduling and routing in order to minimize the system power of multi-hop NC-OFDMA networks. We also provide a low complexity (O(E^2 M^2)) greedy algorithm where M and E denote the number of channels and links respectively. Numerical simulations suggest that our approach reduces system power by 30% over classical transmit power minimization based cross-layer algorithms.Comment: Submitted to IEEE Transactions on Cognitive Communications and Networkin
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