Massive and ubiquitous deployment of devices in networks of fifth generation (5G) and beyond wireless has necessitated the development of ultra-low-power wireless communication paradigms. Recently, wireless-powered networks with backscatter communications (WPN-BCs) has been emerged as a most prominent technology for enabling large-scale selfsustainable wireless networks with the capabilities of RF energy harvesting (EH) and of extreme low power consumption. Therefore, we provide a comprehensive literature review on the fundamentals, challenges and the on-going research efforts in the domain of WPN-BCs. Our emphasis is on large-scale networks. In particular, we discuss signal processing aspects, network design issues and efficient communication techniques. Moreover, we review emerging technologies for WPN-BCs to bring about the best use of resources. Some applications of this innovative technology are also highlighted. Finally, we address some open research problems and future research directions.
Abstract-Detection of an unknown deterministic signal by using an energy detector is of promising for cognitive radio networks. In this paper, a new approach is proposed to analyze the performance of the energy detector. It is based on the contour integral representation of the Marcum-Q function and the use of the moment generating function (MGF) of the signal-to-noise ratio (SNR). A new decision variable is constructed for the case of maximal ratio combining (MRC) reception. With its help and the MGF based approach, the performance of the MRC energy detector over i.i.d. Rician fading channels is analyzed. This case is intractable with the conventional probability density function (PDF) based approach. Further the detection probability of MRC combined energy detector over Nakagami-m fading branches is derived. The simulation results are presented to support the developed MGF based method, decision variable formulation and derivations. The detector performance is evaluated over different fading and diversity parameters with the help of numerical and simulation examples.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.