Backscatter Communication Systems 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.

Joint Localization and Signal Detection for Ambient Backscatter Communication Systems

Joint Localization and Signal Detection for Ambient Backscatter Communication Systems

Channel Estimation for Full-Duplex OFDM-Based Ambient Backscatter Communication Systems With I/Q Imbalance

Channel Estimation for Full-Duplex OFDM-Based Ambient Backscatter Communication Systems With I/Q Imbalance

On the Unique Channel Identification in Ambient Backscatter Communication Systems

Channel coefficient estimation is a challenging problem in ambient backscatter communication systems. In this paper, unique identification of channel coefficients using the Expectation-Maximization (EM) method is investigated. It is proven that the EM method is not able to always yield unique solutions to channel coefficients and therefore the tag symbol estimation accuracy can be compromised. A correct derivation of the hybrid Cramer-Rao Bound (HCRB) is also provided.

Channel estimation for backscatter communication systems with retrodirective arrays

AbstractBackscatter communications, which originated from World War II, have been widely applied in the logistics domain, and recently attract emerging interest from both academic and industrial circles. Here, the backscatter communication systems equipped with retrodirective arrays that can re‐transmit the impinging signals back toward the direction of incidence are studied so as to reduce the power loss of the signals. Specifically, the authors consider the tag is equipped with retrodirective arrays to improve reliability and enhance communication range. The probability density function of channel coefficients is then derived. Next, a channel estimator based on Bayesian theory is proposed to acquire the modulus values of channel parameters and calculate its Bayesian Cramer–Rao Lower Bound. Finally, simulation results are provided to corroborate these theoretical studies.

Toward Zero Blind-Zone Backscatter Communications: Real-Time System Design, Implementation, and Experimental Evaluation

Backscatter communication with amplitude modulation is promising in facilitating cost-effective and low-power transmission in Internet of Things (IoT). Various backscatter communication systems with amplitude modulation have been investigated in the latest work. One critical issue in the work is that only when the tag is placed in certain positions within the communication range can the system achieve good communication performance, where poor performance is seen in other blind zones. In this paper, we address the blind zone problem in backscatter communications with amplitude modulation and analyze the problem according to the Fresnel zone theory. We also design and implement realtime systems employing multi-antenna transmission and multi-receiver reception to deal with the blind zone problem. Experimental evaluation has verified that the multi-receiver reception can improve the communication coverage with greatly decreased blind zone and the multi-antenna technique can facilitate full backscatter communications with no blind zone.

Channel Estimation for Backscatter Communication Systems Under Circuit Sensitivity Constraint

Channel Estimation for Backscatter Communication Systems Under Circuit Sensitivity Constraint

A BLE 5.0 Extended Advertising Backscatter with Commodity Devices in Passive IoT Scenarios

BLE-based (Bluetooth Low Energy-based) backscatter has received considerable attention, as it aims to communicate with everyday smart devices such as smartphones, smartwatches, and tablets in passive IoT. The state-of-the-art BLE backscatter systems enable communication using a specialized continuous wave (CW) generator or entirely using commodity BLE 4.0 radios as an RF source. However, the existing BLE communication systems suffer from several key issues, including a short carrier length and a large frequency shift. This paper presents a passive BLE (PBLE) backscatter communication system that utilizes commodity BLE 5.0 radios. The system uses a BLE 5.0 extended advertising packet with partial single tones as excitations transmitting on the secondary advertising channel of BLE 5.0, and the BLE backscatter tag produces bandpass frequency-shift keying modulation at 1 Mb/s, which enables compatibility with BLE advertising channels. The prototype is implemented using an NRF52832 BLE 5.0 commodity chip, smart devices, and tags with FPGAS and chips. In FPGA board-level verification, when the downlink distance is 0.5 m, the uplink distance can reach 10 m. In chip testing, the uplink distance can reach 7 m when the downlink distance is 1 m. The baseband power consumption is 2 μW, with a total power consumption of 10 μW. This system eliminates the need for expensive and costly specialized RF sources, unlike the BLE backscatter communication system that uses a specialized CW generator. Compared to the BLE backscatter communication system that uses commodity BLE 4.0 radios, this system reduces the minimum frequency shift from 24 MHz to 2 MHz and increases the length of the single tones as a CW by a factor of about seven, from 31 bytes to 254 bytes.

A survey of millimeter wave backscatter communication systems

Backscatter communication is an emerging low-power communication technology that has been integrated into the Internet of Things (IoT) due to its exceptional self-sustainability. However, conventional backscatter communication (BackCom) technologies often encounter limitations in data transmission rates, making it challenging to meet the growing bandwidth demands of IoT applications. In contrast, millimeter wave (mmWave) BackCom exhibits significant potential for high-speed data transmission owing to its abundant spectrum resources. Therefore, this paper presents a comprehensive survey of the existing literature on mmWave BackCom. We start by introducing the fundamental principles of mmWave BackCom, encompassing its architecture, basic techniques, and foundational knowledge. Subsequently, we review various mmWave backscatter communication techniques proposed in the current literature. Finally, we discuss several applications based on these techniques before finally addressing challenges and open issues associated with mmWave backscatter.

Joint optimization of resource allocation and trajectory based on user trajectory for UAV-assisted backscatter communication system

Joint optimization of resource allocation and trajectory based on user trajectory for UAV-assisted backscatter communication system

Ambient Backscatter Communication System Empowered by Matching Game and Machine Learning for Enabling Massive IoT Over 6G HetNets

Ambient Backscatter Communication System Empowered by Matching Game and Machine Learning for Enabling Massive IoT Over 6G HetNets

A 1T2R High-Sensitivity and Dual-Channel Transceiver for Backscatter Communication Systems

A 1T2R High-Sensitivity and Dual-Channel Transceiver for Backscatter Communication Systems

Design of a New CIM-DCSK-Based Ambient Backscatter Communication System

Design of a New CIM-DCSK-Based Ambient Backscatter Communication System

Machine Learning Based Blind Signal Detection for Ambient Backscatter Communication Systems

Machine Learning Based Blind Signal Detection for Ambient Backscatter Communication Systems

Outage Performance Analysis for Mutualistic Symbiotic Backscatter Communication Systems

Outage Performance Analysis for Mutualistic Symbiotic Backscatter Communication Systems

Design and Implementation of a Tunable Metasurface Enhanced Monostatic Backscatter Communication System for IoT

Design and Implementation of a Tunable Metasurface Enhanced Monostatic Backscatter Communication System for IoT

Number Detection for Backscatter Communication Systems: Identification of the Number of Active and Inactive Tags

Number Detection for Backscatter Communication Systems: Identification of the Number of Active and Inactive Tags

On the Achievable Rate Maximization in RIS Enhanced Ambient Backscatter Communication Systems

On the Achievable Rate Maximization in RIS Enhanced Ambient Backscatter Communication Systems

Next-Generation IoT: Harnessing AI for Enhanced Localization and Energy Harvesting in Backscatter Communications

Ongoing backscatter communications and localisation research have been able to obtain incredibly accurate results in controlled environments. The main issue with these systems is faced in complex RF environments. This paper investigates concurrent localization and ambient radio frequency (RF) energy harvesting using backscatter communication systems for Internet of Things networks. Dynamic real-world environments introduce complexity from multipath reflection and shadowing, as well as interference from movements. A machine learning framework leveraging K-Nearest Neighbors and Random Forest classifiers creates robustness against such variability. Historically, received signal measurements construct a location fingerprint database resilient to perturbations. The Random Forest model demonstrates precise localization across customized benches with programmable shuffling of chairs outfitted with RF identification tags. Average precision accuracy exceeds 99% despite deliberate placement modifications, inducing signal fluctuations emulating mobility and clutter. Significantly, directional antennas can harvest over −3 dBm, while even omnidirectional antennas provide −10 dBm—both suitable for perpetually replenishing low-energy electronics. Consequently, the intelligent backscatter platform localizes unmodified objects to customizable precision while promoting self-sustainability.

Bulk Schottky Junctions-Based Flexible Triboelectric Nanogenerators to Power Backscatter Communications in Green 6G Networks.

This work introduces a novel method to construct Schottky junctions to boost the output performance of triboelectric nanogenerators (TENGs). Perovskite barium zirconium titanate (BZT) core/metal silver shell nanoparticles are synthesized to be embedded into electrospun polyvinylidene fluoride-co-hexafluoropropylene (PVDF-HFP) nanofibers before they are used as tribo-negative layers. The output power of TENGs with composite fiber mat exhibited >600% increase compared to that with neat polymer fiber mat. The best TENG achieved 1339V in open-circuit voltage, 40µA in short-circuit current and 47.9Wm-2 in power density. The Schottky junctions increased charge carrier density in tribo-layers, ensuring a high charge transfer rate while keeping the content of conductive fillers low, thus avoiding charge loss and improving performance. These TENGs are utilized to power radio frequency identification (RFID) tags for backscatter communication (BackCom) systems, enabling ultra-massive connectivity in the 6G wireless networks and reducing information communications technology systems' carbon footprint. Specifically, TENGs are used to provide an additional energy source to the passive tags. Results show that TENGs can boost power for BackCom and increase the communication range by 386%. This timely contribution offers a novel route for sustainable 6G applications by exploiting the expanded communication range of BackCom tags.