This work offers design and implementation of in-network inference, using message passing among ambiently powered wireless sensor network (WSN) terminals. The stochastic nature of ambient energy harvesting dictates intermittent operation of each WSN terminal and as such, the message passing inference algorithms should be robust to asynchronous operation. It is shown, perhaps for the first time in the literature (to the best of our knowledge), a proof of concept, where a WSN harvests energy from the environment and processes itself the collected information in a distributed manner, by converting the (network) inference task to a probabilistic, in-network message passing problem, often at the expense of increased total delay. Examples from Gaussian belief propagation and average consensus (AC) are provided, along with the derivation of a statistical convergence metric for the latter case. A k-means method is offered that maps the elements of the calculated vector to the different WSN terminals and overall execution delay (in number of iterations) is quantified. Interestingly, it is shown that there are divergent instances of the in-network message passing algorithms that become convergent, under asynchronous operation. Ambient solar energy harvesting availability is also studied, controlling the probability of successful (or not) message passing. Hopefully, this work will spark further interest for asynchronous message passing algorithms and technologies that enable in-network inference, toward ambiently powered, batteryless Internet of Things-That-Think.

This work exploits ultra-low cost, commodity, radio frequency identification (RFID) tags as elements of a reconfigurable intelligent surface (RIS). Such batteryless tags are powered and controlled by a software-defined radio reader, with properly modified software, so that a source-destination link is assisted, operating at a different band. Signal model includes small-scale and large-scale fading, direct link, as well as specific parameters relevant to reflection (i.e., backscatter) radio, such as antenna structural mode and reflection efficiency, typically overlooked in the literature. An algorithm is offered that computes the optimal RIS configuration with complexity of$\mathcal {O}(M\log {M})$in number of elements$M$, instead of intractable exponential complexity of exhaustive search, while accommodating any number$K\geq 2$of loads. With the proposed algorithm, it is shown that performance gains reach a plateau for constant element spacing and increasing number of elements, suggesting that the weak, passive nature of backscattered links limits the performance gains, even with perfect channel estimation. Channel estimation with linear minimum mean squared error (LMMSE) estimator is shown to be effective, provided that there are sufficient number of pilot symbols. A concrete way is offered to design and prototype a wireless, batteryless, RF-powered, reconfigurable surface and a proof-of-concept is experimentally demonstrated.

Backscatter radio utilizes the reflection that an electromagnetic wave undergoes when it impinges an unmatched-to-a-load antenna, in order to achieve ultra-low-power communication. This work exploits principles commonly found in the ultra-low-power, backscatter communication literature, offering multi-element array functionalities to a single-antenna receiver. A small number of simple, switching backscattering tags deployed in space, emulate a distributed, multi-element antenna array by copying a transmitter’s signal to distinct frequency bands. A receiver can then obtain independent observations of the same signal by discriminating said bands. Using the backscatter tag-based array, the direction of arrival (DoA) estimation problem is addressed without the cost of multiple RF front ends or hardware modifications, at either end of a wireless communication link. The feasibility of the idea was examined through both simulations and experimental deployments. An absolute error of$\approx 20$degrees was observed when utilizing 5 custom-built backscattering tags, while simulations showed that more than 10 tags can offer error of less than 5 degrees.

Is it possible to build ultra-low power wireless sensor networks (WSN) that exploit the inherent parallel and distributed nature of powerful message passing/inference algorithms, embrace ultra-low power communication principles and make autonomous, in-network decisions, solely powered by the environment? While edge and cloud computing emerge, this work points towards the opposite direction, inspired by the fact that ambient energy, either from radio frequency (RF), sun, motion, temperature or even living organisms, has fixed (on average) density per surface (or volume). It is shown, perhaps for the first time in the literature (to the best of our knowledge), a proof of concept, where a WSN harvests energy from the environment and processes itself the collected information in a distributed manner, by converting the (network) inference task to a probabilistic, message passing problem. Examples from Gaussian Belief Propagation and Average Consensus are offered; ambient energy harvesting and availability are quantified, controling the probability of successful (or not) message passing. Such interrupted communication requires distributed algorithms robust to asynchrony, at the expense of increased overall delay. Simulation and experimental validation are offered in a WSN testbed with solar energy harvesting. Future work will focus on overall delay minimization.

This work exploits commodity, ultra-low cost, com-mercial radio frequency identification tags (RFID) as the elements of a reconfigurable surface. Such batteryless tags are powered and controlled by a software-defined (SDR) reader, with properly modified software, so that a source-destination link is assisted, operating at a different carrier frequency. In terms of theory, the optimal gain and corresponding best element configuration is offered, with tractable polynomial complexity (instead of exponential) in number of elements. In terms of practice, a concrete way to design and prototype a wireless, batteryless, RF-powered, reconfigurable surface is offered and a proof-of-concept is experimentally demonstrated. It is also found that even with perfect channel estimation, the weak nature of backscattered links limits the performance gains, even for large number of surface elements. Impact of channel estimation errors is also studied. Future extensions at various carrier frequencies could be directly accommodated, through simple modifications in the antenna and matching network of each RFID tag/surface element.

Conventional direction of arrival (DoA) techniques employ multi-antenna receivers with increased complexity and cost. This work emulates a multi-antenna system using a singleantenna receiver and exploiting the beauty and simplicity of backscatter radio. More specifically, a number of simple backscatter radio tags offer copies of the hidden RF source, relayed in space and shifted in frequency, while requiring minimal time-synchronisation. DoA of a hidden RF source was estimated with an error of less than 5 degrees, exploiting a small number of simple, ultra-low-cost backscattering tags.

Passive Gen2 radio frequency identification (RFID) tags work thanks to the utilization of line codes that balance their operation between two opposite states: absorbing RF (for energy harvesting) and reflecting RF (for backscattering/communications). Given the current RF harvesting technology, batteryless tags need to be located very close to an active illuminator in order to harvest sufficient energy and operate. To tackle this limitation, prior art has tried to bring the illuminator closer to the tags by designing proprietary illuminating architectures. Our solution comes in two parts. First, we offer a novel, Gen2-compliant, near-optimal, noncoherent sequence detection algorithm with linear complexity (in the sequence length) for Miller line codes. We leverage the robustness of this algorithm to overcome issues inherent in multistatic setups, such as carrier frequency offset. Second, we propose a modular multistatic architecture that makes use of low-cost commodity software defined radios (SDR) and omnipresent Ethernet infrastructure. Simulations and experimental results in a monostatic, bistatic, or multistatic SDR testbed with commercial RFIDs, corroborate the low-cost, real-time and near-optimal flavor of our solution.

Motivated by the extensive use of simplified models in the recent ambient backscatter literature, this work will demonstrate the importance of utilizing realistic models when deriving appropriate detectors. For this purpose, two recent works on ambient backscatter will be evaluated under realistic channel models, accounting for all communication parameters. It is shown that assuming a complex normal illuminator (i.e., ignoring illuminator's signal structure) leads to significant performance losses compared to explicitly considering illuminator's modulation (e.g., FM). Based on FM illumination, the importance of the latter is further highlighted by deriving a high performance, fully noncoherent sequence detector. In most cases, switching techniques (e.g., SBPSK) are shown to outperform conventional techniques (OOK), at the expense of increased complexity.

This work offers both analog and digital tag modulation schemes and respective receiver designs, for ultra-low power, high performance, ambient backscatter communications. All proposed techniques are based on simple, but careful, switching frequency control at the tag, allowing for the easy frequency-domain multiple access. First, a digital modulation scheme is offered, namely pseudo-frequency shift keying, assuming illumination from constant envelope-modulated signals and a fully coherent detector is derived along with closed-form probability of error. A second digital modulation scheme is also offered, based on a frequency-shifted form of binary phase shift keying (S-BPSK), relaxing the constant-envelope requirement for the illuminator and an illumination-agnostic detector is derived. Based on S-BPSK, short packet error correction coding is utilized for ambient backscatter communication, for the first time in the literature. It is shown that the proposed coded scheme under modulated ambient signal illumination & wireless channel variation, offers tremendous performance gains, i.e., modulation of the ambient signal is helpful. Finally, a third, purely analog, modulation scheme is analyzed, based on FM remodulation principles. A low-cost tag is implemented, demonstrating tag-to-receiver ranges up to 26 meters outdoors, power consumption of 24 μWatts in continuous operation, able to be interrogated by any conventional frequency modulation (FM) receiver. The proposed techniques cover a large variety of omnipresent wireless industry systems, enabling universal ambient backscatter and relevant wireless information and power transfer (WIPT) applications.