This paper considers social welfare maximization for spatial resource sharing networks(SRSNs),in which multiple autonomous users are spatially located and mutual influence only occurs between nearby users.To cope with a lack of central control and the restriction that only local information is available,a spatial resource sharing game is proposed.However,individual selfishness in traditional game models generally leads to inefficiency and dilemmas.Inspired by local cooperative behavior in biological sys- tems,a community cooperation mechanism(CCM)is proposed to improve the efficiency of the game.Specifically,when a user makes a decision,it maximizes the aggregate payoffs for its local community rather than selfishly consider itself.It is analytically shown that with the bio-inspired CCM,the social optimum of SRSNs is achieved with an exchange of local information.The proposed bio-inspired CCM is very general and can be applied to various communication networks.
A large number of previous works have demonstrated that cooperative spectrum sensing(CSS) among multiple users can greatly improve detection performance.However,when the number of secondary users(SUs;i.e.,spectrum sensors) is large,the sensing overheads(e.g.,time and energy consumption) will likely be intolerable if all SUs participate in CSS.In this paper,we proposed a fully decentralized CSS scheme based on recent advances in consensus theory and unsupervised learning technology.Relying only on iteratively information exchanges among one-hop neighbors,the SUs with potentially best detection performance form a cluster in an ad hoc manner.These SUs take charge of CSS according to an average consensus protocol and other SUs outside the cluster simply overhear the sensing outcomes.For comparison,we also provide a decentralized implementation of the existing centralized optimal soft combination(OSC) scheme.Numerical results show that the proposed scheme has detection performance comparable to that of the OSC scheme and outperforms the equal gain combination scheme and location-awareness scheme.Meanwhile,compared with the OSC scheme,the proposed scheme significantly reduces the sensing overheads and does not require a priori knowledge of the local received signal-to-noise ratio at each SU.
Information theory(IT)is the derivation and foundation of information science,and has become one of the most mature,complete and systematic components in information and communication fields within these years.This article extends classic IT from the traditional form aspect to the semantic aspect and gives an informational perspective of semantic cognition process(SCP),which is motivated by the stringent requirements of information predigestion and machine cognition in cognitive wireless networks.To begin with,we establish three key viewpoints on semantic,which are semantic objectivity,semantic conditional uniformity and semantic dependency,as the basis and premise of this article.Next,we establish a comprehensive theoretical framework of SCP in terms of the natural connotation,the three-layer framework and the mathematical model of SCP.Then we give a couple of primary theorems of SCP as well as their practical instructions.Furthermore,the research challenges ahead are presented in this article.
