In cognitive radio (CR) systems, the primary user (PU) signal would randomly depart or arrive during the sensing period of a CR user, which is referred to as the high traffic environment. In this paper, we propose a novel spectrum sensing scheme based on the cyclostationarity of PU signals in high traffic environments. Specifically, we obtain a test statistic by applying an estimate of spectral...

Wireless sensor networks (WSNs) have many applications in the areas of commercial, military and environmental requirements. Regarding the deployment of low cost sensor nodes with restricted energy resources, these networks face a lot of security challenges. A basic approach for preparing a secure wireless communication in WSNs, is to propose an efficient cryptographic key management protocol be...

We propose a study using hidden Markov model (HMM) with state prediction for opportunistic spectrum access (OSA) in cognitive radio (CR) networks. The primary channels are assumed to be operating in a TDMA manner with synchronous time slots of equal length and alternating between idle and busy states. The secondary users (SUs) may use them when they are idle by channel sensing. In contrast to t...

Compressive sensing (CS) provides an energy-efficient paradigm for data gathering in wireless sensor networks (WSNs). However, the existing work on spatial-temporal data gathering using compressive sensing only considers either multi-hop relaying based or multiple random walks based approaches. In this paper, we exploit the mobility pattern for spatial-temporal data collection and propose a nov...

Mobile sensing has become a promising paradigm for mobile users to obtain information by task crowdsourcing. However, due to the social preferences of mobile users, the quality of sensing reports may be impacted by the underlying social attributes and selfishness of individuals. Therefore, it is crucial to consider the social impacts and trustworthiness of mobile users when selecting task parti...