High-frequency modulated-backscatter communication using multiple antennas

Backscatter radio - the broad class of systems that communicate using scattered electromagnetic waves - is the driving technology behind many compelling applications such as radio frequency identification (RFID) tags and passive sensors. These systems can be used in many ways including article tracking, position location, passive temperature sensors, passive data storage, and in many other systems which require information exchange between an interrogator and a small, low-cost transponder with little-to-no transponder power consumption. Although backscatter radio is maturing, such systems have limited communication range and reliability caused, in part, by multipath fading. The research presented in this dissertation investigates how multipath fading can be reduced using multiple antennas at the interrogator transmitter, interrogator receiver, and on the transponder, or RF tag. First, two link budgets for backscatter radio are presented and fading effects demonstrated through a realistic, 915 MHz, RFID-portal example. Each term in the link budget is explained and used to illuminate the propagation and high-frequency effects that influence RF tag operation. Second, analytic envelope distributions for the M x L x N, dyadic backscatter channel - the general channel in which a backscatter system with M transmitter, L RF tag, and N receiver antennas operates - are derived. The distributions show that multipath fading can be reduced using multiple-antenna RF tags and by using separate transmitter and receiver antenna arrays at the interrogator. These results are verified by fading measurements of the M x L x N, dyadic backscatter channel at 5.8 GHz - the center of the 5725-5850 MHz unlicensed industrial, scientific, and medical (ISM) frequency band that offers reduced antenna size, increased antenna gain, and, in some cases, reduced object attachment losses compared to the commonly used 902-928 MHz ISM band. Measurements were taken with a custom backscatter testbed and details of its design are provided. In the end, this dissertation presents both theory and measurements that demonstrate multipath fading reductions for backscatter-radio systems that use multiple antennas.Ph.D.Committee Chair: Durgin, Gregory; Committee Member: Ingram, Mary Ann; Committee Member: Nikitin, Pavel; Committee Member: Peterson, Andrew; Committee Member: Steffes, Pau

A Frequency Diverse Gen2 RFID System with Isolated Continuous Wave Emitters

Abstract—The “Gen2 ” specification for UHF passive RFID systems released by EPCglobal has become an intense research interest. A Gen2 tag derives its power from the RF wave emitted by a Gen2 RFID reader and responds its modulated backscatter signals to the reader. Due to the large propagation loss, the accessible range of a Gen2 tag is hence limited. Moreover, the readability of a Gen2 tag is often influenced by the multipath fading problem. In order to mitigate the problems, a multi-carrier UHF passive RFID system utilizing the frequency diverse backscatter ability of a Gen2 tag is proposed in a prior work. In this work, a thorough analysis of the system is given. Especially, the appropriate powers of the transceiver and CWEs are derived to make the system more feasible in practical applications. Index Terms—RFID, Gen2, multipath fading, frequency diversity I

A Statistical Approach to the Alignment of fMRI Data

Multi-subject functional Magnetic Resonance Image studies are critical. The anatomical and functional structure varies across subjects, so the image alignment is necessary. We define a probabilistic model to describe functional alignment. Imposing a prior distribution, as the matrix Fisher Von Mises distribution, of the orthogonal transformation parameter, the anatomical information is embedded in the estimation of the parameters, i.e., penalizing the combination of spatially distant voxels. Real applications show an improvement in the classification and interpretability of the results compared to various functional alignment methods

A comparison of the CAR and DAGAR spatial random effects models with an application to diabetics rate estimation in Belgium

When hierarchically modelling an epidemiological phenomenon on a finite collection of sites in space, one must always take a latent spatial effect into account in order to capture the correlation structure that links the phenomenon to the territory. In this work, we compare two autoregressive spatial models that can be used for this purpose: the classical CAR model and the more recent DAGAR model. Differently from the former, the latter has a desirable property: its ρ parameter can be naturally interpreted as the average neighbor pair correlation and, in addition, this parameter can be directly estimated when the effect is modelled using a DAGAR rather than a CAR structure. As an application, we model the diabetics rate in Belgium in 2014 and show the adequacy of these models in predicting the response variable when no covariates are available