Backscatter Sensor Networks Research Articles

Orthogonal Space–Time Block Code Based Over-the-Air Computation in Backscatter Sensor Networks

Orthogonal Space–Time Block Code Based Over-the-Air Computation in Backscatter Sensor Networks

Efficient Charging and Data Collection in UAV-Aided Backscatter Sensor Networks

Efficient Charging and Data Collection in UAV-Aided Backscatter Sensor Networks

Batteryless Backscatter Sensor Networks—Part I: Challenges With (Really) Simple Tags

Backscatter radio only requires a simple switch, terminating the tag antenna between (at least) two loads. However, recent detection in ambient backscatter sensor networks assumes that the tag is receiver-equipped, able to synchronize its backscattering with the illuminating (ambient) transmission. Additional challenges with simple, potentially receiver-less, backscattering tags include: lack of cooperation with the legacy, ambient illuminator, asynchronous channel estimation, tag frame synchronization, energy harvesting for batteryless tag operation and multiple access. Part I addresses asynchronous channel estimation and detection with digital ambient signals and concrete analysis; Part II partially addresses all challenges with analog ambient signals and practical deployment.

Batteryless Backscatter Sensor Networks—Part II: Lessons From Scalable Deployment

Inspired by the challenges presented in Part I, Part II examines analog ambient backscatter for scalable, batteryless, wireless and ultra-low cost sensing of soil moisture. Ultra-low power ambient backscatter sensors are built, with accuracy below 4%, cost of a few euros per sensor and ability to report soil moisture to any conventional FM radio-equipped smartphone. Calibration, characterization, extensive usage and evaluation was conducted in research greenhouses and small-scale farms. Probabilistic graphical model-based algorithms were also devised that complete missing measurements. Hopefully, this work will spark further interest in batteryless backscatter sensor networks with holistic approaches and tremendous socioeconomic impact.

Mobility-Assisted Over-the-Air Computation for Backscatter Sensor Networks

Future intelligent systems will consist of a massive number of battery-less sensors, where quick and accurate aggregation of sensor data will be of paramount importance. Over-the-air computation (AirComp) is a promising technology wherein sensors concurrently transmit their measurements over the wireless channel, and a reader receives the noisy version of a function of measurements due to the superposition property. A key challenge in AirComp is the accurate power alignment of individual transmissions, addressed previously by using conventional precoding methods. In this paper, we investigate a UAVenabled backscatter communication framework, wherein UAV acts both as a power emitter and reader. The mobility of the reader is leveraged to replace the complicated precoding at sensors, where UAV first collects sum channel gains in the first flyover, and then, use these to estimate the actual aggregated sensor data in the second flyover. Our results demonstrate improvements of up to 10 dB in MSE compared to that of a benchmark case where UAV is incognizant of sum channel gains.

Optimal Data Scheduling and Admission Control for Backscatter Sensor Networks

This paper studies the data scheduling and admission control problem for a backscatter sensor network (BSN). In the network, instead of initiating their own transmissions, the sensors can send their data to the gateway just by switching their antenna impedance and reflecting the received RF signals. As such, we can reduce remarkably the complexity, the power consumption, and the implementation cost of sensor nodes. Different sensors may have different functions, and data collected from each sensor may also have a different status, e.g., urgent or normal, and thus we need to take these factors into account. Therefore, in this paper, we first introduce a system model together with a mechanism in order to address the data collection and scheduling problem in the BSN. We then propose an optimization solution using the Markov decision process framework and a reinforcement learning algorithm based on the linear function approximation method, with the aim of finding the optimal data collection policy for the gateway. Through simulation results, we not only show the efficiency of the proposed solution compared with other baseline policies, but also present the analysis for data admission control policy under different classes of sensors as well as different types of data.

A SDR Prototype for Backscatter Sensor Networks

A SDR Prototype for Backscatter Sensor Networks

Sensitive and Efficient RF Harvesting Supply for Batteryless Backscatter Sensor Networks

This work presents an efficient and high-sensitivity radio frequency (RF) energy harvesting supply. The harvester consists of a single-series circuit with one double diode on a low-cost, lossy FR-4 substrate, despite the fact that losses decrease RF harvesting efficiency. The design targeted minimum reflection coefficient and maximum rectification efficiency, taking into account not only the impedance matching network, but also the rectifier microstrip trace dimensions and the load. The simulated and measured rectenna efficiency was 28.4% for $-\hbox{20-dBm}$ power input. In order to increase sensitivity, i.e., ability to harvest energy and operate at low power density, rectennas were connected in series configuration (voltage summing), forming rectenna arrays. The proposed RF harvesting system ability was tested at various input power levels, various sizes of rectenna arrays, with or without a commercial boost converter, allowing operation at RF power density as low as 0.0139 $\mu \hbox{W/cm}^{2}$ . It is emphasized that the boost converter, whenever used, was self-started, without any additional external energy. The system was tested in supplying a scatter radio sensor, showing experimentally the effect of input power density on the operational cold start duration and duty cycle of the sensor.

Coherent Detection and Channel Coding for Bistatic Scatter Radio Sensor Networking

With rapid advances of scatter radio systems, the principle of reflection rather than active transmission employed by backscatter sensor networks, has emerged as a potential key enabler for low-cost, large-scale and dense ubiquitous sensor networks. Despite the presence of three different unknown channel links due to the bistatic setup (i.e., carrier emitter and receiver are dislocated), as well as multiple unknown scatter radio-related parameters, this work offers a novel coherent receiver of frequency-shift keying (FSK) modulation for the bistatic scatter radio channel. Furthermore, with the objective of range maximization, specific short block-length cyclic channel codes are utilized. The proposed approach requires minimum encoding complexity, ideal for resource-constrained, ultra-low power (e.g. microcontroller unit-based), low-bit rate scatter radio tags, adheres to simple low-complexity decoding at the receiver and achieves high-order signal diversity. Analysis is followed by experimental validation with a commodity software-defined radio (SDR) reader and a custom scatter radio tag; tag-to-reader ranges up to 150 meters are demonstrated with as little as 20 milliWatt transmission power, increasing sensing ranges by approximately 10 additional meters, compared to state-of-the-art bistatic scatter radio receivers. With the imminent emergence of backscatter sensor networks, this work serves as a small step forward towards the realization of low-cost, low-power, increased-range, wireless sensing applications.

Anti-collision backscatter sensor networks

Sensor collision (interference) is studied in a large network of low bit-rate sensors that communicate via backscatter, i.e. modulate the reflection of a common carrier transmitted by a central reader. Closed-form analysis is provided, quantifying sensor collision (interference) in high-density, backscatter sensor networks (BSN), as a function of number of tags and aggregate bandwidth. Analysis is applicable to a broad class of sensor subcarrier modulations, propagation environments and reader antenna directivity patterns. It is discovered that anti-collision performance in high-density backscatter sensor networks is feasible provided that appropriate modulation is used at each sensor. That is due to the round-trip nature of backscatter communication as well as the extended target range, which both impose stringent requirements on spectrum efficiency, not easily met by all modulations. Furthermore, aggregate bandwidth savings for given anti-collision performance are quantified, when simple division techniques on subcarrier (modulating) frequency and space (via moderately directive hub antenna) are combined.