191 research outputs found

    Radio Co-location Aware Channel Assignments for Interference Mitigation in Wireless Mesh Networks

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    Designing high performance channel assignment schemes to harness the potential of multi-radio multi-channel deployments in wireless mesh networks (WMNs) is an active research domain. A pragmatic channel assignment approach strives to maximize network capacity by restraining the endemic interference and mitigating its adverse impact on network performance. Interference prevalent in WMNs is multi-faceted, radio co-location interference (RCI) being a crucial aspect that is seldom addressed in research endeavors. In this effort, we propose a set of intelligent channel assignment algorithms, which focus primarily on alleviating the RCI. These graph theoretic schemes are structurally inspired by the spatio-statistical characteristics of interference. We present the theoretical design foundations for each of the proposed algorithms, and demonstrate their potential to significantly enhance network capacity in comparison to some well-known existing schemes. We also demonstrate the adverse impact of radio co- location interference on the network, and the efficacy of the proposed schemes in successfully mitigating it. The experimental results to validate the proposed theoretical notions were obtained by running an exhaustive set of ns-3 simulations in IEEE 802.11g/n environments.Comment: Accepted @ ICACCI-201

    High Throughput WMN for the Communication in Disaster Scenario

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    The Wireless mesh network (WMN) is a popular network architecture used to support disaster recovery operations. However, few research works have addressed the capacity problem of such a network. This is due to the assumption that the communication network in disaster scenario is built to support services with a low rate requirement like delay tolerant messages. At the same time, the demand for higher data rates has increased in recent years due to the digitalisation of rescue operations and the use of new services (e.g. VoIP, drones and robots). Therefore, the capacity of the WMN is becoming a central issue in the design of future WMNs. This paper proposes a Layer 1 cluster-based network to solve the throughput bottleneck in the WMN. The proposed architecture is evaluated by several real world measurements. The obtained results are compared with the theory. The proposed solution shows a throughput improvement compared to a single-radio WMN and a multi-radio WMN using the CoMTaC channel allocation strategy

    Optimal Access Point Power Management for Green IEEE 802.11 Networks

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    In this paper, we present an approach and an algorithm aimed at minimising the energy consumption of enterprise Wireless Local Area Networks (WLANs) during periods of low user activity. We act on two network management aspects: powering off some Access Points (APs), and choosing the level of transmission power of each AP. An efficient technique to allocate the user terminals to the various APs is the key to achieving this goal. The approach has been formulated as an integer programming problem with nonlinear constraints, which comes from a general but accurate characterisation of the WLAN. This general problem formulation has two implications: the formulation is widely applicable, but the nonlinearity makes it NP-hard. To solve this problem to optimality, we devised an exact algorithm based on a customised version of Benders’ decomposition method. The computational results proved the ability to obtain remarkable power savings. In addition, the good performance of our algorithm in terms of solving times paves the way for its future deployment in real WLANs.publishedVersio

    Channel parameter tuning in a hybrid Wi-Fi-Dynamic Spectrum Access Wireless Mesh Network

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    This work addresses Channel Assignment in a multi-radio multi-channel (MRMC) Wireless Mesh Network (WMN) using both Wi-Fi and Dynamic Spectrum Access (DSA) spectrum bands and standards. This scenario poses new challenges because nodes are spread out geographically so may have differing allowed channels and experience different levels of external interference in different channels. A solution must meet two conflicting requirements simultaneously: 1) avoid or minimise interference within the network and from external interference sources, and 2) maintain connectivity within the network. These two requirements must be met while staying within the link constraints and the radio interface constraints, such as only assigning as many channels to a node as it has radios. This work's original contribution to the field is a unified framework for channel optimisation and assignment in a WMN that uses both DSA and traditional Wi-Fi channels for interconnectivity. This contribution is realised by providing and analysing the performance of near-optimal Channel Assignment (CA) solutions using metaheuristic algorithms for the MRMC WMNs using DSA bands. We have created a simulation framework for evaluating the algorithms. The performance of Simulated Annealing, Genetic Algorithm, Differential Evolution, and Particle Swarm Optimisation algorithms have been analysed and compared for the CA optimisation problem. We introduce a novel algorithm, used alongside the metaheuristic optimisation algorithms, to generate feasible candidate CA solutions. Unlike previous studies, this sensing and CA work takes into account the requirement to use a Geolocation Spectrum Database (GLSD) to get the allowed channels, in addition to using spectrum sensing to identify and estimate the cumulative severity of both internal and external interference sources. External interference may be caused by other secondary users (SUs) in the vicinity or by primary transmitters of the DSA band whose emissions leak into adjacent channels, next-toadjacent, or even into further channels. We use signal-to-interference-plus-noise ratio (SINR) as the optimisation objective. This incorporates any possible source or type of interference and makes our method agnostic to the protocol or technology of the interfering devices while ensuring that the received signal level is high enough for connectivity to be maintained on as many links as possible. To support our assertion that SINR is a reasonable criterion on which to base the optimisation, we have carried out extensive outdoor measurements in both line-of-sight and wooded conditions in the television white space (TVWS) DSA band and the 5 GHz Wi-Fi band. These measurements show that SINR is useful as a performance measure, especially when the interference experienced on a link is high. Our statistical analysis shows that SINR effectively differentiates the performance of different channels and that SINR is well correlated with throughput and is thus a good predictor of end-user experience, despite varying conditions. We also identify and analyse the idle times created by Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) contention-based Medium Access Control (MAC) operations and propose the use of these idle times for spectrum sensing to measure the SINR on possible channels. This means we can perform spectrum sensing with zero spectrum sensing delay experienced by the end user. Unlike previous work, this spectrum sensing is transparent and can be performed without causing any disruption to the normal data transmission of the network. We conduct Markov chain analysis to find the expected length of time of a sensing window. We also derive an efficient minimum variance unbiased estimator of the interference plus noise and show how the SINR can be found using this estimate. Our estimation is more granular, accurate, and appropriate to the problem of Secondary User (SU)-SU coexistence than the binary hypothesis testing methods that are most common in the literature. Furthermore, we construct confidence intervals based on the probability density function derived for the observations. This leads to finding and showing the relationships between the number of sampling windows and sampling time, the interference power, and the achievable confidence interval width. While our results coincide with (and thus are confirmed by) some key previous recommendations, ours are more precise, granular, and accurate and allow for application to a wider range of operating conditions. Finally, we present alterations to the IEEE 802.11k protocol to enable the reporting of spectrum sensing results to the fusion or gateway node and algorithms for distributing the Channel Assignment once computed. We analyse the convergence rate of the proposed procedures and find that high network availability can be maintained despite the temporary loss of connectivity caused by the channel switching procedure. This dissertation consolidates the different activities required to improve the channel parameter settings of a multi-radio multi-channel DSA-WMN. The work facilitates the extension of Internet connectivity to the unconnected or unreliably connected in rural or peri-urban areas in a more cost-effective way, enabling more meaningful and affordable access technologies. It also empowers smaller players to construct better community networks for sharing local content. This technology can have knock-on effects of improved socio-economic conditions for the communities that use it

    Differential Evolution in Wireless Communications: A Review

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    Differential Evolution (DE) is an evolutionary computational method inspired by the biological processes of evolution and mutation. DE has been applied in numerous scientific fields. The paper presents a literature review of DE and its application in wireless communication. The detailed history, characteristics, strengths, variants and weaknesses of DE were presented. Seven broad areas were identified as different domains of application of DE in wireless communications. It was observed that coverage area maximisation and energy consumption minimisation are the two major areas where DE is applied. Others areas are quality of service, updating mechanism where candidate positions learn from a large diversified search region, security and related field applications. Problems in wireless communications are often modelled as multiobjective optimisation which can easily be tackled by the use of DE or hybrid of DE with other algorithms. Different research areas can be explored and DE will continue to be utilized in this contex

    New Waves of IoT Technologies Research – Transcending Intelligence and Senses at the Edge to Create Multi Experience Environments

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    The next wave of Internet of Things (IoT) and Industrial Internet of Things (IIoT) brings new technological developments that incorporate radical advances in Artificial Intelligence (AI), edge computing processing, new sensing capabilities, more security protection and autonomous functions accelerating progress towards the ability for IoT systems to self-develop, self-maintain and self-optimise. The emergence of hyper autonomous IoT applications with enhanced sensing, distributed intelligence, edge processing and connectivity, combined with human augmentation, has the potential to power the transformation and optimisation of industrial sectors and to change the innovation landscape. This chapter is reviewing the most recent advances in the next wave of the IoT by looking not only at the technology enabling the IoT but also at the platforms and smart data aspects that will bring intelligence, sustainability, dependability, autonomy, and will support human-centric solutions.acceptedVersio

    Cooperative Radio Communications for Green Smart Environments

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    The demand for mobile connectivity is continuously increasing, and by 2020 Mobile and Wireless Communications will serve not only very dense populations of mobile phones and nomadic computers, but also the expected multiplicity of devices and sensors located in machines, vehicles, health systems and city infrastructures. Future Mobile Networks are then faced with many new scenarios and use cases, which will load the networks with different data traffic patterns, in new or shared spectrum bands, creating new specific requirements. This book addresses both the techniques to model, analyse and optimise the radio links and transmission systems in such scenarios, together with the most advanced radio access, resource management and mobile networking technologies. This text summarises the work performed by more than 500 researchers from more than 120 institutions in Europe, America and Asia, from both academia and industries, within the framework of the COST IC1004 Action on "Cooperative Radio Communications for Green and Smart Environments". The book will have appeal to graduates and researchers in the Radio Communications area, and also to engineers working in the Wireless industry. Topics discussed in this book include: • Radio waves propagation phenomena in diverse urban, indoor, vehicular and body environments• Measurements, characterization, and modelling of radio channels beyond 4G networks• Key issues in Vehicle (V2X) communication• Wireless Body Area Networks, including specific Radio Channel Models for WBANs• Energy efficiency and resource management enhancements in Radio Access Networks• Definitions and models for the virtualised and cloud RAN architectures• Advances on feasible indoor localization and tracking techniques• Recent findings and innovations in antenna systems for communications• Physical Layer Network Coding for next generation wireless systems• Methods and techniques for MIMO Over the Air (OTA) testin

    Planification globale des réseaux mobiles de la quatrième génération (4G)

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    RÉSUMÉ Dans le contexte actuel où l’information est la clé du succès, peu importe le domaine où l’on se place, les réseaux de télécommunications sont de plus en plus sollicités. D’énormes quantités d’informations circulent sur les réseaux à chaque seconde. Il est primordial d’assurer la disponibilité de ces réseaux afin de garantir la transmission de ces données en toutes circonstances. Le problème de la planification des réseaux de télécommunications consiste à déterminer, parmi un ensemble de sites potentiels, ceux à utiliser afin de couvrir une zone géographique donnée. Il convient également de choisir les équipements à installer sur ces sites et de faire le lien entre eux en fonction de certaines contraintes bien définies. Depuis des dizaines d’années, plusieurs auteurs se sont penchés sur la résolution de ce problème dans le but de minimiser le coût d’installation du réseau. Ces auteurs se sont intéressés à divers aspects du problème sans le considérer dans sa globalité. Certaines études ont été effectuées récemment sur la planification globale des réseaux mobiles. Les auteurs se sont intéressés aux réseaux de la troisième génération et ont proposé un modèle pour résoudre le problème de façon globale. Cependant, ils n’ont pas pris en compte la tolérance du réseau aux pannes qui pourraient survenir. Cette thèse propose un cadre de planification globale pour les réseaux de la quatrième génération (la nouvelle génération des réseaux mobiles). La survivabilité du réseau est prise en compte dans cette étude. Le travail a été effectué en trois phases. Dans la première phase, un modèle global incluant la tolérance aux pannes a été conçu pour la planification des réseaux 4G (WiMAX) et résolu de manière optimale avec un solveur mathématique, en utilisant la programmation linéaire en nombres entiers. L’objectif du modèle consiste à minimiser le coût du réseau, tout en maximisant sa survivabilité. Afin de montrer la pertinence de la résolution globale, le modèle a été comparé à un modèle séquentiel avec les mêmes contraintes. Le modèle séquentiel consiste à subdiviser le problème en trois sous-problèmes et à les résoudre successivement. Un modèle global qui n’intègre pas les contraintes de fiabilité a également été conçu afin de vérifier l’effet des pannes sur le réseau. Les résultats obtenus par le modèle global proposé sont, en moyenne, 25% meilleurs que ceux des deux autres modèles. Le problème de planification globale des réseaux et le problème de survivabilité des réseaux de télécommunications sont deux problèmes NP-difficiles. La combinaison de ces deux problèmes donne un problème encore plus difficile à résoudre que chacun des problèmes pris séparément. La méthode exacte utilisée dans la première phase ne peut résoudre que des instances de petite taille. Dans la deuxième phase, nous proposons une métaheuristique hybride afin trouver de "bonnes solutions" en un temps "raisonnable" pour des instances de plus grande taille. La métaheuristique proposée est une nouvelle forme d’hybridation entre l’algorithme de recherche locale itérée et la méthode de programmation linéaire en nombres entiers. L’hybridation de ces deux méthodes permet de bénéficier de leurs avantages respectifs, à savoir l’exploration efficace de l’espace de recherche et l’intensification des solutions obtenues. L’intensification est effectuée par la méthode exacte qui calcule la meilleure solution possible à partir d’une configuration donnée tandis que l’exploration de l’espace est faite à travers l’algorithme de recherche locale itérée. Les performances de l’algorithme ont été évaluées par rapport à la méthode exacte proposée lors de la première phase. Les résultats montrent que l’algorithme proposé génère des solutions qui sont, en moyenne à 0,06% des solutions optimales. Pour les instances de plus grande taille, des bornes inférieures ont été calculées en utilisant une relaxation du modèle. La comparaison des résultats obtenus par l’algorithme proposé avec ces bornes inférieures montrent que la métaheuristique obtient des solutions qui sont, en moyenne à 2,43% des bornes inférieures pour les instances qui ne peuvent pas être résolues de manière optimale, avec un temps de calcul beaucoup plus faible. La troisième phase a consisté à la conception d’une métaheuristique multi-objectifs pour résoudre le problème. En effet, nous essayons d’optimiser deux objectifs contradictoires qui sont le coût du réseau et sa survivabilité. L’algorithme proposé permet d’offrir plus d’alternatives au planificateur, lui donnant ainsi plus de flexibilité dans la prise de décision.----------ABSTRACT In the current context where information is the key to success in any field where one stands, telecommunications networks are increasingly in demand. Huge amounts of information circulates on the networks every second. It is essential to ensure the availability of these networks to ensure the transmission of these data at any time. The problem of planning of telecommunication networks is to determine, from a set of potential sites, those to be used to cover a given geographical area. One should also choose the equipment to be installed on these sites and to link them according to certain well-defined constraints. For decades, several authors have focused on solving this problem in order to minimize the cost of network installation. These authors were interested in various aspects of the problem without considering it in its entirety. Some studies have recently been performed on the global planning of mobile networks. The authors were interested in the third generation networks. They proposed a model to solve the problem entirely, without breaking it down into sub-problems. However, they did not take into account the fault tolerance of network. This thesis proposes a global planning framework for the fourth generation (4G) networks (the new generation of mobile networks). The survivability of the network is taken into account in this study. The work was conducted in three phases. In the first phase, a global model including survivability has been designed for the planning of 4G (WiMAX) networks and solved optimally with a mathematical solver using the integer linear programing method. The objective of the model is to minimize the network cost while maximizing its survivability. To show the relevance of the global resolution, the model was compared to a sequential model with the same constraints. The sequential model is to divide the problem into three sub-problems and solve them successively. A global model which does not include survivability constraints has also been designed to test the effect of failures on the network. The results show that the proposed model performs on average 25% better than the two other models. The problem of global network planning and the problem of survivability of telecommunications networks are two NP-hard problems. The combination of these two problems provides a problem even more difficult to solve than each problem taken separately. The exact method used in the first phase can only solve small instances. In the second phase, we propose a hybrid metaheuristic to find `good solutions' in a `reasonable time' for instances of larger size. The proposed metaheuristic is a new form of hybridization between the iterated local search algorithm and the integer linear programing method. The hybridization of these two methods can benefit from their respective advantages, namely the efficient exploration of the search space and the intensification of the solutions obtained. The intensification is performed by the exact method that calculates the best possible solution from a given configuration while the exploration of the search space is made through the iterated local search algorithm. The performance of the algorithm have been evaluated with respect to the exact method given in the first phase. The results show that the proposed algorithm generates solutions that are on average 0,06% of the optimal solutions. For the larger instances, the lower bounds are calculated using a relaxation of the model. The comparison of the results obtained by the proposed algorithm with the lower bounds show that the metaheuristic obtains solutions that are on average 2,43% from the lower bounds, for the instances that cannot be solved optimally, within a much less computation time. The third phase involved the design of a multi-objective metaheuristics to solve the problem. Indeed, we try to optimize two conflicting objectives which are the cost of network and its survivability. The proposed algorithm allows us to offer more alternatives to the planner, giving him (her) more exibility in the decision making process

    Radio resource management and metric estimation for multicarrier CDMA systems

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