A study on social-based cooperative sensing in cognitive radio networks

A cognitive radio (CR) is an intelligent radio that reuses frequency band based on dynamic spectrum access (DSA). CR implements spectrum sensing to detect primary users' (PU) presence, and exploits available spectrum without interfering PU. In contrast with local spectrum sensing, cooperative sensing which is implemented by multiple CRs, is more efficient and effective generally. Previous work on cooperative spectrum sensing in cognitive radio (CR) assumes a default mode that CRs are willing to cooperate for others unconditionally. While this situation does not always hold, the requested CR might reject the cooperation request due to its insufficient energy, or security concerns. In this thesis, we propose a social-based cooperative sensing scheme (SBC) that exploits social ties of CRs on their cooperative sensing. Simulation results show that SBC fulfills improved sensing quality, and the sensing performance of CRs correlate to the social degree and social network topology

Computing normalisers of intransitive groups

Funding: The first and third authors would like to thank the Isaac Newton Institute for Mathematical Sciences, Cambridge, for support and hospitality during the programme “Groups, Representations and Applications: New perspectives”, where work on this paper was undertaken. This work was supported by EPSRC grant no EP/R014604/1. This work was also partially supported by a grant from the Simons Foundation. The first and second authors are supported by the Royal Society (RGF\EA\181005 and URF\R\180015).The normaliser problem takes as input subgroups G and H of the symmetric group Sn, and asks one to compute NG(H). The fastest known algorithm for this problem is simply exponential, whilst more efficient algorithms are known for restricted classes of groups. In this paper, we will focus on groups with many orbits. We give a new algorithm for the normaliser problem for these groups that performs many orders of magnitude faster than previous implementations in GAP. We also prove that the normaliser problem for the special case G=Sn  is at least as hard as computing the group of monomial automorphisms of a linear code over any field of fixed prime order.Publisher PDFPeer reviewe

Résolution de Dec-POMDP à horizon infini à l'aide de contrôleurs à états finis dans JESP

National audienceThis paper looks at solving collaborative planning problems formalized as Decentralized POMDPs (DecPOMDPs) by searching for Nash equilibria, i.e., situations where each agent’s policy is a best response to the other agents’ (fixed) policies. While the joint equilibrium-based search for policies (JESP) algorithm does this in the finitehorizon setting relying on policy trees, we propose here to adapt JESP to infinite-horizon Dec-POMDPs by using Finite State Controller policy representations. In this article, we (1) explain how to turn a Dec-POMDP with N −1 fixed finite state controllers into an infinite-horizon POMDP whose solution is a best response of the Nth agent ; (2) propose a JESP variant based on this transformation, called inf-JESP, for solving infinite-horizon Dec-POMDPs ; (3) introduce heuristic initializations for JESP aiming at deterministically leading to good solutions ; and (4) conduct experiments on state-of-the-art benchmark problems to evaluate our approach.Cet article s'intéresse à la résolution de problèmes de planification collaborative formalisés comme des POMDP décentralisés (Dec-POMDP) en cherchant des équilibres de Nash, c'est-à-dire des situations dans lesquelles la politique de chaque agent est une meilleure réponse aux politiques (fixes) des autres agents. Alors que l'algorithme joint equilibrium-based search for policies (JESP) fait ceci dans le cadre d'horizons finis en se reposant sur des arbres-politiques, nous proposons ici d'adapter JESP aux Dec-POMDP à horizon infini en représentant les politiques des agents par des contrôleurs à états finis. Dans cet article, nous (1) expliquons comment transformer un Dec-POMDP avec N − 1 contrôleurs à états finis fixés en un POMDP à horizon infini dont la solution est une meilleure réponse du N ième agent ; (2) proposons une variante de JESP, appelée inf-JESP, reposant sur cette transformation pour résoudre des Dec-POMDP à horizon infini ; (3) introduisons des initialisations heuristiques pour JESP visant à conduire à de bonnes solutions ; et (4) conduisons une évaluation empirique de notre approche sur des bancs d'essais de l'état de l'art

The Lens of the Lab: Design Challenges in Scientific Software

Playful and gameful design could improve the quality of scientific software. However, literature about gamification methods for that particular type of software is presently scarce. As an effort to fill that gap, this paper introduces a set of design challenges and opportunities that should be informative to professionals approaching the area. This research is based on literature review on scientific software development, also contemplating material on the gamification of science, software, and work. From the gathered information, we identify, map, and discuss key aspects of development and use of professional scientific software. Those findings are, then, formatted as a Design Lens—a set of questions designers should ask themselves to gain insight, from a particular perspective, on their work. We propose the Lens of the Lab as a design lens to support designers working in collaboration with scientists and software engineers in professional scientific software initiatives