Powered Backscatter Communications Research Articles

Enhanced Triboelectric Outputs from PAN/MoS2 Nanofiber‐Based Nanogenerators for Powering Backscatter Communications in Sustainable 6G Networks

This work explores the development of a triboelectric nanogenerator (TENG) based on polyacrylonitrile (PAN) and molybdenum disulfide (MoS2) nanosheets composite fibers for enhancing tribo‐positive electricity to power backscatter communication systems, contributing to the sustainable internet of things (IoT) nodes in future 6 G networks. By incorporating different concentrations of MoS2 (1, 2, 3, and 4 wt%) nanosheets into PAN nanofibers via electrospinning, the nanocomposite fiber‐based TENGs exhibit improved triboelectric properties. The TENG based on PAN/4% MoS2 nanocomposite fiber mat achieve a peak open‐circuit voltage of 296 V and a short‐circuit current of 6.16 μA, which represents an ≈95% and 77% enhancement, respectively, in comparison with the TENGs based on neat PAN nanofiber mat. The enhanced charge transfer ability at the PAN and MoS2 nanosheet interface, the increased dielectric properties, the rougher surface morphology of the composite nanofibers contribute to the enhancements in triboelectric performance. These TENGs are integrated with the backscatter communication system to power a wireless identification and sensing platform (WISP) tag, demonstrating extended transmission range and improved real‐time data acquisition. These findings suggest that TENGs can play a significant role in sustainable energy solutions for 6 G‐enabled IoT applications.

Resource Allocation Optimization for Secure Multidevice Wirelessly Powered Backscatter Communication With Artificial Noise

Wirelessly powered backscatter communications (WPBC) is an emerging technology for providing continuous energy and ultra-low power communications. Despite some progress in WPBC systems, resource allocation for multiple devices towards secure backscatter communications (BC) and efficient-energy harvesting (EH) requests a deep-insight investigation. In this paper, we consider a WPBC system in which a full-duplex access point (AP) transmits multi-sinewave signals to power backscatter devices (BDs) and injects artificial noise (AN) to secure their backscatter transmissions. To maximize the minimum harvested energy and ensure fairness and security of all BDs, we formulate an optimization problem by jointly considering the backscatter time, power splitting ratio between multi-sinewave and AN, and signal power allocation. For a single-BD system, we characterize the achievable secrecy rate-energy region with a non-linear energy harvester and propose two algorithms to solve an energy maximization problem. We then analyze the effect of multi-sinewave and AN signals on BD’s secrecy rate and harvested energy through simulations and proof-of-concept experiments. For a multi-BD system, we propose an iterative algorithm by leveraging block successive upper-bound minimization (BSUM) techniques to solve the non-convex problem of fair resource allocation and show its convergence and complexity. Numerical results show the proposed algorithm achieves optimal and equitable harvested energy for all BDs with satisfying the security constraint.

UGV-Assisted Wireless Powered Backscatter Communications for Large-Scale IoT Networks

Wireless powered backscatter communications (WPBC) is capable of implementing ultra-low-power communication, thus promising in the Internet of Things (IoT) networks. In practice, however, it is challenging to apply WPBC in large-scale IoT networks because of its short communication range. To address this challenge, this paper exploits an unmanned ground vehicle (UGV) to assist WPBC in large-scale IoT networks. In particular, we investigate the joint design of network planning and dynamic resource allocation of the access point (AP), tag reader, and UGV to minimize the total energy consumption. Also, the AP can operate in either half-duplex (HD) or full-duplex (FD) multiplexing mode. Under HD mode, the optimal cell radius is derived and the optimal power allocation and transmit/receive beamforming are obtained in closed form. Under FD mode, the optimal resource allocation, as well as two suboptimal ones with low computational complexity, is developed. Simulation results disclose that dynamic power allocation at the tag reader rather than at the AP dominates the network energy efficiency while the AP operating in FD mode outperforms that in HD mode concerning energy efficiency.

Advances in Wirelessly Powered Backscatter Communications: From Antenna/RF Circuitry Design to Printed Flexible Electronics

Backscatter communication is an emerging paradigm for pervasive connectivity of low-power communication devices. Wirelessly powered backscattering wireless sensor networks (WSNs) become particularly important to meet the upcoming era of the Internet of Things (IoT), which requires the massive deployment of self-sustainable and maintenance-free low-cost sensing and communication devices. This article will introduce the state-of-the-art antenna design and radio frequency (RF) system integration for wirelessly powered backscatter communications, covering both the node and the base unit. We capture the latest development in ultralow-power RF front ends and coding schemes for <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu \text{W}$ </tex-math></inline-formula> -level backscatter modulators, as well as the latest progress in wireless power transfer (WPT) and energy harvesting (EH) techniques. Newly emerged rectenna system, waveform design, and channel optimization are reviewed in light of the opportunities for adaptively optimizing the WPT/EH efficiency for low-power signals with varying conditions. In addition, advanced device packaging and integration technologies in, e.g., additively manufactured RF components and modules for microwave and millimeter-wave ubiquitous sensing and backscattering energy-autonomous RF structures are reported. Inkjet printing for the sustainable and ultralow-cost fabrication of flexible RF devices and sensors will be reviewed to provide a prospective insight into the future packaging of backscatter communications from the chip-level design to complete system integration. Finally, this article will also address the challenges in fully wireless powered backscatter radio networks and discuss the future directions of backscatter communication in terms of “Green IoT” and “Low Carbon” smart home, smart city, smart skin, and machine-to-machine (M2M) applications.

Throughput Fairness Guarantee in Wireless Powered Backscatter Communications With HTT

Harvest-then-transmit (HTT) and backscatter communications have different tradeoffs between energy harvesting and data transmission and may complement each other for increasing the achievable throughput, which however has not been sufficiently exploited by the existing works. In this letter, we propose a max-min throughput based resource allocation scheme for a wireless powered Internet of Things (IoT) network to ensure the fairness among multiple sensor nodes (SNs), which harvest energy from the signals transmitted by a power beacon (PB) and convey their information to an information receiver (IR) by backscattering, HTT, or the hybrid of them. We introduce a series of auxiliary variables to transform the non-convex max-min throughput problem into a convex one. We show that the max-min throughput is achieved when the SN with the worst link, which achieves the minimum throughput, consumes all the harvested energy and works in the hybrid of backscattering and HTT. Simulation results show that compared with the sum-throughput maximization scheme, our developed resource allocation scheme achieves a much better throughput fairness, while maintaining almost the same average throughput.

Energy-Efficient Resource Allocation for Wirelessly Powered Backscatter Communications

In this letter, we consider a wireless-powered backscatter communication (WP-BackCom) network, where the transmitter first harvests energy from a dedicated energy RF source in the sleep state, and then backscatters information and harvests energy simultaneously through a reflection coefficient. Our goal is to maximize the achievable energy efficiency of the WP-BackCom network via jointly optimizing time allocation, reflection coefficient and transmit power of the dedicated energy RF source. The optimization problem is non-convex and challenging to solve. We develop an efficient Dinkelbach-based iterative algorithm to obtain the optimal resource allocation scheme. The study shows that for each iteration, the energy-efficient WP-BackCom network is equivalent to either the network in which the transmitter always operates in the active state, or the network in which the dedicated energy RF source adopts the maximum allowed power.

Multiuser Wirelessly Powered Backscatter Communications: Nonlinearity, Waveform Design, and SINR-Energy Tradeoff

Wireless power transfer and backscatter communications have emerged as promising solutions for energizing and communicating with power limited devices. Despite some progress in wirelessly powered backscatter communications, the focus has been on backscatter and energy harvesters (EHs). Recently, significant progress has been made on the design of the transmit multisine waveform, adaptive to the channel state information at the transmitter (CSIT), in a point-to-point backscatter system. In this paper, we leverage the work and study the design of the transmit multisine waveform in a multiuser backscatter system, made of one transmitter, one reader, and multiple tags active simultaneously. We derive an efficient algorithm to optimize the transmit waveform so as to identify the tradeoff between the amount of energy harvested at the tags and the reliability of the communication, measured in terms of signal-to-interference-plus-noise ratio (SINR) at the reader. The performance with the optimized waveform based on the linear and nonlinear EH models is studied. The numerical results demonstrate the benefits of accounting for the EH nonlinearity, multiuser diversity, frequency diversity, and multisine waveform adaptive to the CSIT to enlarge the SINR-energy region.

Backscatter Communications for Wireless Powered Sensor Networks With Collision Resolution

Wireless powered backscatter communications is an attractive technology for next-generation low-powered sensor networks such as the Internet of Things. However, backscattering suffers from collisions due to multiple simultaneous transmissions and a dyadic backscatter channel, which greatly attenuate the received signal at the reader. This letter deals with backscatter communications in sensor networks from a large-scale point-of-view and considers various collision resolution techniques: directional antennas, ultra-narrow band transmissions, and successive interference cancellation. We derive analytical expressions for the decoding probability and our results show the significant gains, which can be achieved from the aforementioned techniques.

Wirelessly Powered Backscatter Communications: Waveform Design and SNR-Energy Tradeoff

This paper shows that wirelessly powered backscatter communications is subject to a fundamental tradeoff between the harvested energy at the tag and the reliability of the backscatter communication, measured in terms of SNR at the reader. Assuming the RF transmit signal is a multisine waveform adaptive to the channel state information, we derive a systematic approach to optimize the transmit waveform weights (amplitudes and phases) in order to enlarge as much as possible the SNRenergy region. Performance evaluations confirm the significant benefits of using multiple frequency components in the adaptive transmit multisine waveform to exploit the nonlinearity of the rectifier and a frequency diversity gain.