This paper studies backscatter communication (BackCom) systems with a passive backscatter tag. The effectiveness of these tags is limited by the amount of energy they can harness from incident radio signals, which are used to backscatter information through the modulation of reflections. To address this limitation, we adopt a practical Constant-Linear-Constant (CLC) energy harvesting model that accounts for the harvester’s sensitivity and saturation threshold, both of which depend on the input power. This paper aims to maximize this harvested power at a passive tag by optimally designing the underlying M-ary amplitude-shift keying (ASK) modulator in a monostatic BackCom system. Specifically, we derive the closed-form expression for the global optimal reflection coefficients that maximize the tag’s harvested power while satisfying the minimum symbol error rate (SER) requirement, tag sensitivity, and reader sensitivity constraints. We also proposed optimal binary-ASK modulation design to gain novel design insights on practical BackCom systems with readers having superior sensitivity. We have validated these nontrivial analytical claims via extensive simulations. The numerical results provide insight into the impact of the transmit symbol probability, tag sensitivity constraint, and SER on the maximum average harvested power. Remarkably, our design achieves an overall gain of around 13% over the benchmark, signifying its utility in improving the efficiency of BackCom systems. Moreover, our proposed solution methodology for determining the maximum average harvested power is applicable to any type of energy harvesting model that exhibits a monotonic increasing relationship with the input power.

Backscatter communication (BackCom) systems play a crucial role in low-cost and low-data-rate Internet of Things (IoT) applications. However, existing research predominantly focuses on idealized scenarios using minimum scattering antennas, resulting in performance discrepancies between simulations and practical implementations. To address this limitation, we investigate the impact of the antenna-dependent parameter associated with structural mode scattering on the amplitude and phase of the backscattered signal.We reveal that the conventional assumption of a minimum scattering antenna negatively affects BackCom system performance. To overcome this challenge, we propose an innovative signal subtraction technique (SST) that effectively mitigates the issues arising from this assumption. Our proposedSSTnot only preserves the minimum scattering antenna assumption but also enhances BackCom systems. Specifically, it improves the signal-to-noise ratio (SNR) in amplitude-shift keying (ASK)-modulated BackCom systems and introduces a trade-off between SNR and bit error rate (BER) in phase-shift keying (PSK)-modulated BackCom systems. Our extensive simulations highlight the practical application ofSST, demonstrating zero performance degradation when applying optimized designs tailored for minimum scattering antennas to any tag antenna. These findings underscore the pivotal role ofSSTin optimizing ASK- and PSK-modulated BackCom systems and offer valuable insights for enhancing overall system performance.

Backscatter communication (BackCom) is a wireless technology that is highly cost-effective and power-efficient. It uses passive tags to reflect incoming radio frequency (RF) signals to transmit data instead of actively generating their own RF signals. Our study aims to improve the performance of the BackCom system by using Quadrature Amplitude Modulation (QAM), which can make it more useful in various applications. Our primary goal is to increase the distance between the emitter and the tag, which is essential in determining the practicality of BackCom systems. We achieve this by optimizing the reflection coefficients while considering quality of service (QoS) requirements such as tag sensitivity, receiver sensitivity, and the occurrence of symbol error rate. We apply a successive convex approximation method to transform the non-convex problem of maximizing the range into a convex one, enabling us to find the optimal solution using a proposed low-complexity maximization algorithm. The simulation results verify the key analytical claims and provide novel insights into the maximum emitter-to-tag distance for different BackCom applications and tag design specifications, including the near-optimal QAM constellation design.

In traditional Internet-of-Things (IoT) networks, devices generate their own signals to transmit data, which consumes more power. However, monostatic backscatter communications (BSC) can perform modulation and signal processing using an external signal from a reader, rather than generating signals from the device itself. Radio Frequency Identification (RFID) systems operate on this monostatic backscattering technology. Despite its benefits, BSC is vulnerable to exploitation by cyber attackers, primarily due to the limited hardware capabilities of passive RFID tags. Jamming attacks can disrupt legitimate BSC systems, enabling illegal activities or allowing competitors to gain advantages. This novel empirical investigation proposes two methods, power control and location control, to enable a typical RFID system to read data even in the presence of a powerful jamming attack. The study analyzed the relationships among reader power, the reader-to-tag (R2T) distance, the jammer-to-tag (A2T) distance, and power gain. The performance was analytically characterized and evaluated through computer simulations and hardware experiments. To the best of our knowledge, this is the first work to empirically quantify the impact of jamming attacks on RFID read rates at the reader and to assess the efficacy of physical layer security techniques in mitigating their impact. Lastly, experimental validation utilizing commodity hardware provides novel insights into optimal power and topology control for securing passive tags in sustainable IoT environments against jamming attacks.

Backscatter Communication (BackCom) is gaining popularity due to its potential for sustainable and low-cost Internet of Things (IoT) applications. However, due to the limited resources of passive tags, optimizing the backscatter modulation is critical for the widespread use of this technology. Current backscatter modulation designs ignore the impact of the tag’s antenna structure, which we show in this paper to have a negative effect on system performance and lead to design discrepancies. We investigate the impact of the antenna structure parameter on the backscattered signal characteristics. Then, we propose a novel signal subtraction technique that effectively calibrates the received signal based on the tag’s antenna structure to enable accurate detection. Our simulation results demonstrate that different values of this critical parameter result in different backscattered signals, which influence the signal decoding efficiency at the receiver. Furthermore, our work provides insights for optimized system design and enhanced BackCom performance.

Wireless technology has been used to locate and track people in real time using active sensors attached to the subject. Camera systems can be contact-free, but they are also invasive in terms of privacy. Backscattering and deep learning algorithms have enabled low-cost sustainable tracking, but this also needs to be worn by the subject. We present a novel solution that utilises backscattering from radio frequency identification (RFID) tags placed in the environment, not on the person, to detect the underlying location. These battery-less, sub-dollar energy harvesting tags are sustainable and enable passive contactfree localisation, acting as multiple sensors. To come up with a timely, real-time green, noninvasive wireless localisation system, we use a pre-trained linear machine learning algorithm to predict a person’s location based on a Received Signal Strength Indicator (RSSI) measured from an array of tags placed in the target environment. Our experiments demonstrate that we can accurately predict an individual’s location with high precision on commodity hardware, achieving a resolution of $0.4 \times 0.4 \mathbf{m}^{2}$ in a $6 \mathbf{m}^{2}$ area, with an accuracy of 81.26% in real-time.

This paper proposes a novel cooperative transmission protocol for a three-user backscatter communication (BackCom) in the Internet of Things. Specifically, the optimal time-division multiple access based transmission protocols for the 2-hop and 3-hop cooperative schemes in the BackCom system have been developed to maximize the underlying system throughput. In the investigated monostatic BackCom system, a reader simultaneously transmits the radio frequency signal to the backscatter tags in the downlink and receives the backscattered signals in the uplink. In the 2-hop cooperative scheme, either one of the near-apart tags serves as a cooperative decode-and-forward agent that relays the far-apart tag’s information to the reader. On the other hand, the farthest tag collaborates with the two near-apart tags to relay its information to the reader in the 3-hop cooperative scheme. Since we aim to maximize the system throughput of the cooperative BackCom system, we formulate the maximization problem of minimum throughput among the tags in both 2-hop and 3-hop cooperative schemes. Then, we investigate the optimal time allocation for maximizing the minimum system throughput for both 2-hop and 3-hop cooperative schemes. Subsequently, we introduce auxiliary variables to the original problems and convert them into equivalent linear programming problems. The numerical results verify the utility of the cooperative schemes in different transmission channels and tags’ placement. In our investigation, the proposed 3-hop cooperative scheme obtained an average gain above 30% over the non-cooperative scheme.

This paper explores a novel cooperative timing protocol in two-user backscatter communication (BSC) network, where one Reader transmits a wireless energy signal to two collaborative backscatter tags. These tags modulate the incident signal and backscatter its information to the Reader. Specifically, the tag closer to the Reader uses its resources to help relay the far tag’s information to the Reader to reduce the effect of the doubly near-far problem in BSC. We aim to maximize the transmission range of the farther tag while satisfying the Quality of Service (QoS) requirement in terms of throughput and energy threshold. First, we derive the necessary conditions for the proposed problem’s feasibility for throughput and energy constraints. Then, we solve this non-convex range maximization problem by alternatively optimizing the time allocation for maximizing minimum throughput and energy, respectively, and the transmission range. The numerical simulations have been conducted to provide insight into the impact of energy and throughput base QoS demand on the achievable transmission range. The average gain of the proposed cooperative BSC over the non-cooperative one is $\gt 20$%.