Distributed Detection and Its Applications with Energy Harvesting Wireless Networks

Sammanfattning: With the advent and widespread applications of high data-rate wireless services and devices, two of the fundamental resources in wireless communication have become extremely important and are scarce. These two resources are bandwidth and energy respectively. To tackle the problem of the ever-growing requirements of bandwidth, the paradigm of cognitive radio has been proposed in the literature where the users without any license are capable of utilizing the wireless radio spectrum allocated to the licensed user when it is idle. The performance of such a dynamic spectrum allocation policy depends heavily on the unlicensed users' ability to detect the vacancy in a licensed user's radio spectrum. Different types of detection algorithms have been investigated in the literature for this purpose. Some classic detection techniques like energy detection, matched filter detection, cyclo-stationary detector, generalized likelihood ratio test detector have found significant applications in sensing the licensed spectrum. These group of detection techniques focuses on collecting samples and performing the detection in a non-sequential fashion. The sequential counterpart of such techniques which are implemented sequentially at every time instant has also been studied extensively.Tackling the evergrowing energy requirement has been the other major challenge for wireless communication. To address this issue, a significant amount of research has been dedicated to the idea of incorporating the capability of energy harvesting in wireless devices. Further research in this domain has also introduced the idea of wireless energy sharing, where individual users are additionally capable of sharing energy with each other. The problem with such systems is the inherently stochastic nature of the energy harvesting process. Furthermore, there are practical limitations of the size of the battery for each user, which limits the amount of energy that can be stored at a particular time instant.Motivated by these two factors, the work presented in this thesis has its focus on cognitive radio networks with energy harvesting capability. In the aforementioned network, unlicensed users are concerned with achieving two fundamental goals. Firstly, they want to efficiently utilize the radio spectrum when the licensed user is not active, which results in the sum-throughput maximization problem with energy harvesting constraint. We have also investigated this problem where individual unlicensed users are capable of sharing energy with each other. Secondly, they want to detect the change in the activity in the licensed user spectrum as soon as possible. Motivated by this goal, we have investigated the problem of change point detection delay minimization in wireless sensor networks with energy harvesting constraints in a decentralized setting. Furthermore, we have explored the detection delay parameter for the decentralized settings with local decisions with similar constraints of energy availability due to energy harvesting.