Spectrum Trading: An Abstracted Bibliography

This document contains a bibliographic list of major papers on spectrum trading and their abstracts. The aim of the list is to offer researchers entering this field a fast panorama of the current literature. The list is continually updated on the webpage \url{http://www.disp.uniroma2.it/users/naldi/Ricspt.html}. Omissions and papers suggested for inclusion may be pointed out to the authors through e-mail (\textit{[email protected]})

Multi-objective optimization of cognitive radio networks

New generation networks, based on Cognitive Radio technology, allow dynamic allocation of the spectrum, alleviating spectrum scarcity. These networks also have a resilient potential for dynamic operation for energy saving. In this paper, we present a novel wireless network optimization algorithm for cognitive radio networks based on a cloud sharing-decision mechanism. Three Key Performance Indicators (KPIs) were optimized: spectrum usage, power consumption, and exposure. For a realistic suburban scenario in Ghent city, Belgium, we determine the optimal trade-off between the KPIs. Compared to a traditional Cognitive Radio network design, our optimization algorithm for the cloud-based architecture reduced the network power consumption by 27.5%, the average global exposure by 34.3%, and spectrum usage by 34.5% at the same time. Even for the worst-case optimization (worst achieved result of a single KPI), our solution performs better than the traditional architecture by 4.8% in terms of network power consumption, 7.3% in terms of spectrum usage, and 4.3% in terms of global exposure

A Comprehensive Survey on Networking over TV White Spaces

The 2008 Federal Communication Commission (FCC) ruling in the United States opened up new opportunities for unlicensed operation in the TV white space spectrum. Networking protocols over the TV white spaces promise to subdue the shortcomings of existing short-range multi-hop wireless architectures and protocols by offering more availability, wider bandwidth, and longer-range communication. The TV white space protocols are the enabling technologies for sensing and monitoring, Internet-of-Things (IoT), wireless broadband access, real-time, smart and connected community, and smart utility applications. In this paper, we perform a retrospective review of the protocols that have been built over the last decade and also the new challenges and the directions for future work. To the best of our knowledge, this is the first comprehensive survey to present and compare existing networking protocols over the TV white spaces.Comment: 19 page

DR9.3 Final report of the JRRM and ASM activities

Deliverable del projecte europeu NEWCOM++This deliverable provides the final report with the summary of the activities carried out in NEWCOM++ WPR9, with a particular focus on those obtained during the last year. They address on the one hand RRM and JRRM strategies in heterogeneous scenarios and, on the other hand, spectrum management and opportunistic spectrum access to achieve an efficient spectrum usage. Main outcomes of the workpackage as well as integration indicators are also summarised.Postprint (published version

Intelligent Approaches for Energy-Efficient Resource Allocation in the Cognitive Radio Network

The cognitive radio (CR) is evolved as the promising technology to alleviate the spectrum scarcity issues by allowing the secondary users (SUs) to use the licensed band in an opportunistic manner. Various challenges need to be addressed before the successful deployment of CR technology. This thesis work presents intelligent resource allocation techniques for improving energy efficiency (EE) of low battery powered CR nodes where resources refer to certain important parameters that directly or indirectly affect EE. As far as the primary user (PU) is concerned, the SUs are allowed to transmit on the licensed band until their transmission power would not cause any interference to the primary network. Also, the SUs must use the licensed band efficiently during the PU’s absence. Therefore, the two key factors such as protection to the primary network and throughput above the threshold are important from the PU’s and SUs’ perspective, respectively. In deployment of CR, malicious users may be more active to prevent the CR users from accessing the spectrum or cause unnecessary interference to the both primary and secondary transmission. Considering these aspects, this thesis focuses on developing novel approaches for energy-efficient resource allocation under the constraints of interference to the PR, minimum achievable data rate and maximum transmission power by optimizing the resource parameters such as sensing time and the secondary transmission power with suitably selecting SUs. Two different domains considered in this thesis are the soft decision fusion (SDF)-based cooperative spectrum sensing CR network (CRN) models without and with the primary user emulation attack (PUEA). An efficient iterative algorithm called iterative Dinkelbach method (IDM) is proposed to maximize EE with suitable SUs in the absence of the attacker. In the proposed approaches, different constraints are evaluated considering the negative impact of the PUE attacker on the secondary transmission while maximizing EE with the PUE attacker. The optimization problem associated with the non-convex constraints is solved by our proposed iterative resource allocation algorithms (novel iterative resource allocation (NIRA) and novel adaptive resource allocation (NARA)) with suitable selection of SUs for jointly optimizing the sensing time and power allocation. In the CR enhanced vehicular ad hoc network (CR-VANET), the time varying channel responses with the vehicular movement are considered without and with the attacker. In the absence of the PUE attacker, an interference-aware power allocation scheme based on normalized least mean square (NLMS) algorithm is proposed to maximize EE considering the dynamic constraints. In the presence of the attacker, the optimization problem associated with the non-convex and time-varying constraints is solved by an efficient approach based on genetic algorithm (GA). Further, an investigation is attempted to apply the CR technology in industrial, scientific and medical (ISM) band through spectrum occupancy prediction, sub-band selection and optimal power allocation to the CR users using the real time indoor measurement data. Efficacies of the proposed approaches are verified through extensive simulation studies in the MATLAB environment and by comparing with the existing literature. Further, the impacts of different network parameters on the system performance are analyzed in detail. The proposed approaches will be highly helpful in designing energy-efficient CRN model with low complexity for future CR deployment