Search Results (28)

Ambient backscatter communication (AmBC) has been regarded as an energy- and spectrum-efficient backscatter scheme for the massive Internet of Things (IoT). However, most existing AmBC systems are non-adaptive end-to-end systems, which cannot fully accommodate the forthcoming massive communications of the sixth-generation (6G) wireless communication systems. Adaptive backscatter communication has emerged as a research hotspot in AmBC in recent years. In this paper, we propose a novel adaptive backscatter technique on passive backscatter devices (BDs) in massive IoT scenarios. We first design a low-power adaptive strategy for the AmBC system where the backscatter receiver (BR) assigns a decision threshold to the passive BDs for the local adaptive backscatter mode chosen. Then, we propose the decision threshold design method by solving a joint sum rate maximization problem where the reflection coefficients (RCs) and transmit time allocation (TA) of different backscatter modes are also jointly optimized. Finally, simulations are provided to verify the efficiency of the proposed adaptive backscatter technique in terms of sum rate and outage probability performances. The results show that our proposed adaptive multi-source AmBC system can achieve a 34.8% average sum rate performance improvement compared with traditional AmBC systems under a common setup, and it performs better than other existing adaptive backscatter systems. Moreover, the numeric results confirm the accuracy and tightness of our derivation of outage probabilities. Full article

The last few decades have witnessed the rapid development of passive backscatter technologies, which envision promising cost-efficient ambient Internet of Things (IoT) for various applications, such as distributed solar sensor networks. However, limited by the harmonic interference caused by the conventional frequency-shifting-based backscatter control methods, existing backscatter communication technologies cannot support the growing scale of the network. To tackle this issue, we propose a harmonic interference resilient frequency-shifting technique to compress the harmonics during backscatter communication. Different from conventional backscatter tags that shift the frequency with square waves with a constant pulse width, we dynamically modify the pulse width of the square wave to compress different parts of the harmonic waves. Furthermore, we propose a lightweight communication coding algorithm to enhance the compatibility of our system with backscatter applications. We implement the system with off-the-shelf components and conduct comprehensive experiments to evaluate the performance. The results demonstrate our harmonic interference resilient backscatter system can compress the harmonic interference and reduce the BER (bit error rate) by 70%. Full article

Indoor Internet of Things (IoT) is considered as a crucial component of Industry 4.0, enabling devices and machine to communicate and share sensed data leading to increased efficiency, productivity, and automation. Increased energy efficiency is a significant focus within Industry 4.0, as it offers numerous benefits. To support this focus, we developed a hybrid switching mechanism to switch between energy harvesting techniques, ambient backscattering and Simultaneous Wireless Information and Power Transfer (SWIPT), which can be utilized within cooperative communications. To implement the proposed switching mechanism, we consider an indoor warehouse environment, where the moving sensor node transmits sensed data to the fixed relay located on the roof, which is then transmitted to an IoT gateway. The relay is equipped with the proposed switch to energize its communication capabilities while maintaining the expected quality of service at the IoT gateway. Simulation results illustrate the improved energy efficiency within the indoor communication setup while maintaining QoS at varying signal-to-noise (SNR) conditions. Full article

This paper presents a cognitive radio (CR)-enabled symbiotic ambient backscatter communication (AmBC) system with the help of a zero-energy reconfigurable intelligent surface (zeRIS). An adaptive transmission (AT) strategy for the zeRIS is devised based on the amount of harvested energy. Specifically, when energy reserve is insufficient, the zeRIS merely reflects signals without any phase adjustments (PAs), whereas under sufficient energy conditions, it reflects signals following precise PAs. Moreover, a segmented zeRIS is adopted by taking primary transmission (PT) and backscatter transmission (BT) into account. Following this, the coexistence outage probability and ergodic capacity are derived to assess the reliability and effectiveness of the proposed model, respectively. Their asymptotic performance is analyzed to gain insightful observations. Finally, simulation results are provided to verify the accuracy of the theoretical analysis, confirming that AT offers improved reliability, system rate, and energy efficiency over non-adaptive transmission. Furthermore, CR-aided AT demonstrates superior energy efficiency compared to non-CR-assisted AT. It is also crucial to note that the allocation of reflective elements between PT and BT must be reasonably managed to satisfy specific system requirements. Full article

With the rapid consumer adoption of mobile devices such as tablets and smart phones, tele-traffic has experienced a tremendous growth, making low-power technologies highly desirable for future communication networks. In this paper, we consider an ambient backscatter (AB)-based user cooperation (UC) scheme for mmWave wireless-powered communication networks (WPCNs) with lens antenna arrays. Firstly, we formulate an optimization problem to maximize the minimum rate of two users by jointly designing power and time allocation. Then, we introduce auxiliary variables and transform the original problem into a convex form. Finally, we propose an efficient algorithm to solve the transformed problem. Simulation results demonstrate that the proposed AB-based UC scheme outperforms the competing schemes, thus improving the fairness performance of throughput in WPCNs. Full article

Ambient backscatter communication (AmBC), an emerging mechanism for batteryless communications that can utilize ambient radio-frequency signals to modulate information and thus reduce power consumption, has attracted considerable attention and has been considered as a critical technology in green “Internet of Things” sensor networks due to its ultra-low power consumption. This paper presents the first a complete dual-polarization AmBC (DPAm) system model, which can extend AmBC into polarization diversity and improve the data-transmission rate of backscatter symbols. We proposed two scenarios: direct dual-polarization-based DPAm node structures and polarization-conversion-based DPAm node structures. In addition, we consider a parallel backscatter mode with differential coding and develop corresponding detectors, which also give the analytical detection thresholds. Moreover, we consider a simultaneous backscatter mode with Manchester coding in order to avoid complex-parameter estimation. To address the power imbalance problem of the DPAm system that arises because the polarization deflection angle would cause the power level to change with different polarization patterns, we also develop a power-average detector and a clustering detector. Simulation results show the throughput performance on each DPAm node structure with each detector, demonstrating the feasibility and efficiency of the proposed DPAm nodes and detectors. Compared with single-polarization AmBC (SPAm), the proposed DPAm node can achieve higher throughput in most cases. Finally, the clustering detector is shown to be more robust to short training sequences and complex environments. Full article

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. Full article

Backscatter communication (BC) systems are a promising technology for internet of things (IoT) applications that allow devices to transmit information by modulating ambient radio signals without the need for a dedicated power source. However, the security of BC systems is a critical concern due to the vulnerability of the wireless channel. This paper investigates the impact of side information (SI) on the secrecy performance of BC systems. SI mainly refers to the additional knowledge that is available to the communicating parties beyond transmitted data, which can be used to enhance reliability, efficiency, security, and quality of service in various communication systems. In particular, in this paper, by considering a non-causally known SI at the transmitter, we derive compact analytical expressions of average secrecy capacity (ASC) and secrecy outage probability (SOP) for the proposed system model to analyze how SI affects the secrecy performance of BC systems. Moreover, a Monte Carlo simulation validates the accuracy of our analytical results and reveals that considering such knowledge at the transmitter has constructive effects on the system performance and ensures reliable communication with higher rates than the conventional BC systems without SI, namely, lower SOP and higher ASC are achievable. Full article

Previous works only focus on the optimization design for the dual-hop cooperative ambient backscatter communication (AmBC) system with single-relay selection. The impact of relay selection on the outage performance of dual-hop cooperative AmBC systems is still missing. Motivated by this, in this paper, we investigate the outage performance of a dual-hop cooperative AmBC system with single-relay selection, where the backscatter link shares the receiver with the cellular link and the harmful direct-link interference (DLI) is mitigated by using successive interference cancellation (SIC). In the system considered, the selected relay has dual functions. One is to forward message for the cellular link, and the other is to act as the radio-frequency (RF) source for the backscatter device (BD). Specifically, after proposing two novel single-relay selection schemes (RSSs), namely reactive RSS and proactive RSS, we derive the closed-form outage probability (OP) expressions for both RSSs, which can be performed in a distributed manner. To gain more insights, the asymptotic OPs at high signal-to-noise ratio (SNR) are explored and the outage performance comparison between the reactive RSS and proactive RSS are also provided. Results show that the proposed reactive RSS is outage-optimal among all possible single-relay selection schemes. The theoretical analysis is validated by Monte Carlo simulations. The results also show that the relay selection scheme, the number of relays, the location of BD, and the reflection coefficient of BD have great impact on the outage performance of cooperative AmBC systems. Full article

This paper analyzed the performance of an ambient-backscatter-(AmBC)-assisted non-orthogonal multiple access (NOMA) system, where a backscatter device (BD) broadcasts its signal to numerous users. More specifically, the realistic assumptions of imperfect successive interference cancellation (ipSIC) and residual hardware impairments (RHIs) for AmBC–NOMA systems were taken into consideration. We further derived the closed-form and asymptotic expressions of outage probability for the BD and the d-th user. Based on the asymptotic expressions, the diversity orders of the BD and the d-th user were obtained in the high SNR regime. Furthermore, throughput and energy efficiency are further discussed for AmBC-assisted orthogonal multiple access (OMA) systems in the delay-limited transmission model. The numerical results revealed that: (i) AmBC–NOMA systems have the ability to achieve better outage behavior than AmBC–OMA; (ii) due to the existence of the backscatter link, the error floors of outage probability for the BD and the d-th user appear at a high signal-to-noise ratio; (iii) AmBC–NOMA systems are able to achieve higher energy efficiency and throughput than AmBC–OMA systems. Full article

Supply chain management aims to achieve both efficiency and low cost. Backscatter technology provides a low-energy consumption approach for critical links in the supply chain, such as warehouse management and cargo identification. Traditional backscatter systems achieve tag data transmission through dedicated hardware or controlled transmission sources. An additional access point (AP) can be used to ensure that the original data are always known in tag data decoding. These requirements increase the deployment costs and are not suitable for large-scale applications. To address these challenges, we introduce CRCScatter, a backscatter system based on a cyclic redundancy check (CRC) reverse algorithm, with an uncontrolled source and a single-AP receiver. The CRCScatter decoder at the receiver uses the constraints within 802.11b WiFi packets to recover the original packet and decode tag data from the backscatter packet. Our Matlab simulation results show that CRCScatter is effective in the low signal-to-noise ratio (SNR) regime, and its average decoding time is independent of the length of tag data. By appending redundant bits in tag data, the decoding accuracy of CRCScatter can be improved. In summary, CRCScatter presents a backscatter communication mode based on ambient WiFi signals with fewer hardware requirements and low deployment costs. Furthermore, the decoding idea of calculating unknown data based on the packet constraints has the potential to expand to different types of excitation packages. Full article

The sixth generation (6G) wireless technology aims to achieve global connectivity with environmentally sustainable networks to improve the overall quality of life. The driving force behind these networks is the rapid evolution of the Internet of Things (IoT), which has led to a proliferation of wireless applications across various domains through the massive deployment of IoT devices. The major challenge is to support these devices with limited radio spectrum and energy-efficient communication. Symbiotic radio (SRad) technology is a promising solution that enables cooperative resource-sharing among radio systems through symbiotic relationships. By fostering mutualistic and competitive resource sharing, SRad technology enables the achievement of both common and individual objectives among the different systems. It is a cutting-edge approach that allows for the creation of new paradigms and efficient resource sharing and management. In this article, we present a detailed survey of SRad with the goal of offering valuable insights for future research and applications. To achieve this, we delve into the fundamental concepts of SRad technology, including radio symbiosis and its symbiotic relationships for coexistence and resource sharing among radio systems. We then review the state-of-the-art methodologies in-depth and introduce potential applications. Finally, we identify and discuss the open challenges and future research directions in this field. Full article

Backscatter communication (BackCom) constitutes intriguing technology that enables low-power devices in transmitting signals by reflecting ambient radio frequency (RF) signals that consume ultra-low energy. Applying the BackCom technique in large-scale networks with massive low-power devices can effectively address the energy issue observed in low-power devices. Prior studies only consider large-scale BackCom networks equipped with omni-directional antennas, called Omn-BackCom Net. To improve the network’s performance, we employ directional antennas in large-scale BackCom networks, called Dir-BackCom Nets. This article establishes a theoretical model for analyzing the performance of Dir-BackCom Nets. The performance metrics include both connectivity and spatial throughput. Our model is genaralized for both Dir-BackCom Nets and Omn-BackCom Net. The accuracy of our theoretical model is verified by extensive simulations. Results indicate that Dir-BackCom Nets can improve connectivity and spatial throughput. Moreover, results show that the throughput can be maximized by choosing an optimal density of BTs. In addition, both the connectivity and spatial throughput of BackCom Nets can be improved by choosing a directional antenna with a proper beamwidth and gain of the main lobe. Our theoretical model and results can offer beneficial implications for constructing Dir-BackCom Nets. Full article

Signal detection is one of the most critical and challenging issues in ambient backscatter communication (AmBC) systems. In this paper, a multi-antenna AmBC signal detection method is proposed based on reconfigurable intelligent surface (RIS) and deep reinforcement learning. Firstly, an efficient multi-antenna AmBC system is developed based on RIS, which can achieve information transmission and energy collection simultaneously. Secondly, a smart twin delayed deep deterministic (TD3) AmBC signal detection method is presented, based on deep reinforcement learning. Extensive quantitative and qualitative experiments are performed, which show that the proposed method is more compelling than the outstanding comparison methods. Full article

The recent combination of ambient backscatter communication (ABC) with non-orthogonal multiple access (NOMA) has shown great potential for connecting large-scale Internet of Things (IoT) in future unmanned aerial vehicle (UAV) networks. The basic idea of ABC is to provide battery-free transmission by harvesting the energy of existing RF signals of WiFi, TV towers, and cellular base stations/UAV. ABC uses smart sensor tags to modulate and reflect data among wireless devices. On the other side, NOMA makes possible the communication of more than one IoT on the same frequency. In this work, we provide an energy efficient transmission design ABC-aided UAV network using NOMA. This work aims to optimize the power consumption of a UAV system while ensuring the minimum data rate of IoT. Specifically, the transmit power of UAVs and the reflection coefficient of the ABC system are simultaneously optimized under the assumption of imperfect channel state information (CSI). Due to co-channel interference among UAVs, imperfect CSI, and NOMA interference, the joint optimization problem is formulated as non-convex, which involves high complexity and makes it hard to obtain the optimal solution. Thus, it is first transformed and then solved by a sub-gradient method with low complexity. In addition, a conventional NOMA UAV framework is also studied for comparison without involving ABC. Numerical results demonstrate the benefits of using ABC in a NOMA UAV network compared to the conventional UAV framework. Full article