10 research outputs found

    Collaborative spectrum sensing optimisation algorithms for cognitive radio networks

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    The main challenge for a cognitive radio is to detect the existence of primary users reliably in order to minimise the interference to licensed communications. Hence, spectrum sensing is a most important requirement of a cognitive radio. However, due to the channel uncertainties, local observations are not reliable and collaboration among users is required. Selection of fusion rule at a common receiver has a direct impact on the overall spectrum sensing performance. In this paper, optimisation of collaborative spectrum sensing in terms of optimum decision fusion is studied for hard and soft decision combining. It is concluded that for optimum fusion, the fusion centre must incorporate signal-to-noise ratio values of cognitive users and the channel conditions. A genetic algorithm-based weighted optimisation strategy is presented for the case of soft decision combining. Numerical results show that the proposed optimised collaborative spectrum sensing schemes give better spectrum sensing performance

    A General Framework for Analyzing, Characterizing, and Implementing Spectrally Modulated, Spectrally Encoded Signals

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    Fourth generation (4G) communications will support many capabilities while providing universal, high speed access. One potential enabler for these capabilities is software defined radio (SDR). When controlled by cognitive radio (CR) principles, the required waveform diversity is achieved via a synergistic union called CR-based SDR. Research is rapidly progressing in SDR hardware and software venues, but current CR-based SDR research lacks the theoretical foundation and analytic framework to permit efficient implementation. This limitation is addressed here by introducing a general framework for analyzing, characterizing, and implementing spectrally modulated, spectrally encoded (SMSE) signals within CR-based SDR architectures. Given orthogonal frequency division multiplexing (OFDM) is a 4G candidate signal, OFDM-based signals are collectively classified as SMSE since modulation and encoding are spectrally applied. The proposed framework provides analytic commonality and unification of SMSE signals. Applicability is first shown for candidate 4G signals, and resultant analytic expressions agree with published results. Implementability is then demonstrated in multiple coexistence scenarios via modeling and simulation to reinforce practical utility

    Learning preferences for personalisation in a pervasive environment

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    With ever increasing accessibility to technological devices, services and applications there is also an increasing burden on the end user to manage and configure such resources. This burden will continue to increase as the vision of pervasive environments, with ubiquitous access to a plethora of resources, continues to become a reality. It is key that appropriate mechanisms to relieve the user of such burdens are developed and provided. These mechanisms include personalisation systems that can adapt resources on behalf of the user in an appropriate way based on the user's current context and goals. The key knowledge base of many personalisation systems is the set of user preferences that indicate what adaptations should be performed under which contextual situations. This thesis investigates the challenges of developing a system that can learn such preferences by monitoring user behaviour within a pervasive environment. Based on the findings of related works and experience from EU project research, several key design requirements for such a system are identified. These requirements are used to drive the design of a system that can learn accurate and up to date preferences for personalisation in a pervasive environment. A standalone prototype of the preference learning system has been developed. In addition the preference learning system has been integrated into a pervasive platform developed through an EU research project. The preference learning system is fully evaluated in terms of its machine learning performance and also its utility in a pervasive environment with real end users

    Energy-efficient cooperative resource allocation for OFDMA

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    Energy is increasingly becoming an exclusive commodity in next generation wireless communication systems, where even in legacy systems, the mobile operators operational expenditure is largely attributed to the energy bill. However, as the amount of mobile traffic is expected to double over the next decade as we enter the Next Generation communications era, the need to address energy efficient protocols will be a priority. Therefore, we will need to revisit the design of the mobile network in order to adopt a proactive stance towards reducing the energy consumption of the network. Future emerging communication paradigms will evolve towards Next Generation mobile networks, that will not only consider a new air interface for high broadband connectivity, but will also integrate legacy communications (LTE/LTE-A, IEEE 802.11x, among others) networks to provide a ubiquitous communication platform, and one that can host a multitude of rich services and applications. In this context, one can say that the radio access network will predominantly be OFDMA based, providing the impetus for further research studies on how this technology can be further optimized towards energy efficiency. In fact, advanced approaches towards both energy and spectral efficient design will still dominate the research agenda. Taking a step towards this direction, LTE/LTE-A (Long Term Evolution-Advanced) have already investigated cooperative paradigms such as SON (self-Organizing Networks), Network Sharing, and CoMP (Coordinated Multipoint) transmission. Although these technologies have provided promising results, some are still in their infancy and lack an interdisciplinary design approach limiting their potential gain. In this thesis, we aim to advance these future emerging paradigms from a resource allocation perspective on two accounts. In the first scenario, we address the challenge of load balancing (LB) in OFDMA networks, that is employed to redistribute the traffic load in the network to effectively use spectral resources throughout the day. We aim to reengineer the load-balancing (LB) approach through interdisciplinary design to develop an integrated energy efficient solution based on SON and network sharing, what we refer to as SO-LB (Self-Organizing Load balancing). Obtained simulation results show that by employing SO-LB algorithm in a shared network, it is possible to achieve up to 15-20% savings in energy consumption when compared to LTE-A non-shared networks. The second approach considers CoMP transmission, that is currently used to enhance cell coverage and capacity at cell edge. Legacy approaches mainly consider fundamental scheduling policies towards assigning users for CoMP transmission. We build on these scheduling approaches towards a cross-layer design that provide enhanced resource utilization, fairness, and energy saving whilst maintaining low complexity, in particular for broadband applications

    Radio Communications

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    In the last decades the restless evolution of information and communication technologies (ICT) brought to a deep transformation of our habits. The growth of the Internet and the advances in hardware and software implementations modified our way to communicate and to share information. In this book, an overview of the major issues faced today by researchers in the field of radio communications is given through 35 high quality chapters written by specialists working in universities and research centers all over the world. Various aspects will be deeply discussed: channel modeling, beamforming, multiple antennas, cooperative networks, opportunistic scheduling, advanced admission control, handover management, systems performance assessment, routing issues in mobility conditions, localization, web security. Advanced techniques for the radio resource management will be discussed both in single and multiple radio technologies; either in infrastructure, mesh or ad hoc networks

    Pameran Reka Cipta, Penyelidikan dan Inovasi (PRPI) 2009

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    PRPI 2009 kini telah memasuki tahun penganjurannya yang ke-7. Pameran penyelidikan di UPM telah bermula sejak tahun 1997 semasa Exhibition & Seminar Harnessing for Industry Advantage. Pada tahun 2002, Pameran Reka Cipta dan Penyelidikan (PRP) buat pertama kali telah diadakan dengan menggunakan konsep pertandingan hasil projek penyelidikan yang telah dijalankan oleh para penyelidik UPM. Kejayaan penganjuran PRP 2002 telah merintis usaha untuk menjadikannya sebagai aktiviti tahunan UPM dan ianya terus berkembang sejajar dengan nama baharunya yang ditukar kepada Pameran Reka Cipta, Penyelidikan dan Inovasi yang bermula penganjurannya pada tahun 2005. Sebagai kesinambungan daripada kejayaan penganjuran PRPI 2006, 2007 dan 2008 yang lalu dan status UPM sebagai salah sebuah Universiti Penyelidikan, PRPI 2009 kali ini yang merupakan pameran penyelidikan yang terbesar di UPM terus dilaksanakan dengan aspirasi dan semangat yang lebih jitu. Pameran ini juga menjadi pelantar kepada para penyelidik untuk mengenengahkan hasil penyelidikan yang dijalankan dan penemuan baharu kepada umum. Di samping itu ianya juga menjadi penanda aras terhadap kualiti sesuatu projek penyelidikan bagi melayakkan para penyelidik UPM untuk menyertai pameran di peringkat kebangsaan dan seterusnya antarabangsa. Adalah diharapkan pelaksanaan PRPI 2009 ini akan dapat menyemarakkan budaya penyelidikan di kalangan staf dan juga pelajar UPM sekaligus menjadikan UPM sebagai Universiti Penyelidikan yang cemerlang di negara ini

    BOBCATSSS 2016 : Information, Libraries, Democracy. Proceedings & Abstracts

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    Actes du congrès BOBCATSSS 2016 qui s\u27est déroulé à Lyon du 27 au 29 janvier 2016 sur le thème : Information, bibliothèques, démocratie
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