Estimation of RFID Tag Population Size by Gaussian Estimator

Radio Frequency IDenti cation (RFID) systems are prevalent in all sorts of daily life endeavors. In this thesis we propose a new method to estimate RFID tag population size. We have named our algorithm Gaussian Estimation of RFID Tags, namely, GERT. We present GERT under both {0,1} and {0,1,e} channel models, and in both cases the estimator we use is a well justi ed Gaussian random variable for large enough frame size based on Central Limit Theorem for triangular arrays. The most prominent feature of GERT is the quality with which it estimates a tag population size. We support all the required approximations with detailed analytical work and account for all the approximation errors when we consider the overall quality of the estimation. Our simulation results agree well with analytical ones. GERT, based on standardized frame slotted Aloha protocol, can estimate any tag population size with desired level of accuracy using fewer number of frame slots than previously proposed algorithms

Energy efficiency in short and wide-area IoT technologies—A survey

In the last years, the Internet of Things (IoT) has emerged as a key application context in the design and evolution of technologies in the transition toward a 5G ecosystem. More and more IoT technologies have entered the market and represent important enablers in the deployment of networks of interconnected devices. As network and spatial device densities grow, energy efficiency and consumption are becoming an important aspect in analyzing the performance and suitability of different technologies. In this framework, this survey presents an extensive review of IoT technologies, including both Low-Power Short-Area Networks (LPSANs) and Low-Power Wide-Area Networks (LPWANs), from the perspective of energy efficiency and power consumption. Existing consumption models and energy efficiency mechanisms are categorized, analyzed and discussed, in order to highlight the main trends proposed in literature and standards toward achieving energy-efficient IoT networks. Current limitations and open challenges are also discussed, aiming at highlighting new possible research directions