Ambient Backscatter Communication Systems Research Articles

Azimuth Estimation for the Backscatter Device in Ambient Backscatter Communication System

In this letter, we study the azimuth estimation for the backscatter device (BD) in ambient backscatter communication system, where the receiver is equipped with the uniform linear array (ULA). By utilizing the covariance matrices in two symbol periods with different BD symbols, we apply the conventional multiple signal classification (MUSIC) algorithm to estimate the azimuths of both the BD and the ambient radio frequency (RF) source. Then, we propose a novel eigenvector-based algorithm to identify the azimuth of the BD from the two estimated azimuths. Moreover, we qualitatively analyze the impacts of the reflection coefficients on the performance of the proposed azimuth estimation approach. Finally, the simulation results are provided to validate the effectiveness of the proposed method and to justify the qualitative analytical conclusions.

Generalized Space Shift Keying for Ambient Backscatter Communication

We consider a generalized space shift keying (GSSK)-enabled multiple-input multiple-output (MIMO) ambient backscatter communication (ABC) system. We propose a scheme to exploit the multiple antenna structure of the system to achieve a lower error-rate performance than conventional ABC systems. Furthermore, we present a novel low complexity energy-based maximum likelihood (EML) GSSK detector, which does not require the perfect knowledge of the ambient source’s signal, unlike the conventional ABC receivers. To gain insights into the performance of the proposed scheme, we derive the exact pairwise error probability (PEP) of the EML detector and further obtain an upper bound on the probability of error. We also derive a simple asymptotic PEP expression as the number of antennas of the reader becomes large. Finally, we derive a simple, asymptotic PEP at the reader when the noise variance approaches zero, i.e., under the large signal-to-interference ratio regime. We validate our analysis through Monte Carlo simulations and show a small performance loss due to the approximations.

Energy Efficient Transmission Design for NOMA Backscatter-Aided UAV Networks with Imperfect CSI

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.

The New Era of Long-Range "Zero-Interception" Ambient Backscattering Systems: 130 m with 130 nA Front-End Consumption.

Internet of Things applications based on backscatter radio principles have appeared to address the limitations of high cost and high power consumption. While radio-frequency identification (RFID) sensor nodes are among the most commonly utilized state-of-the-art technologies, their range for passive implementations is typically short and well below 10 m being impractical for “rugged” applications where approaching the tag at such proximity, is not convenient or safe. In this work, we propose a long-range “zero interception” ambient backscatter (LoRAB) communication system relying on low power sensor (tag) deployments. Without employing a dedicated radio transmission, our technology enables the “zero interception” communication of the tags with portable receivers over hundreds of meters. This enables low-cost and low-power communications across a wide range of missions by using chirp spread spectrum (CSS) modulation on ambient FM signals. A laboratory prototype exploiting commercial components (laptops, DAQ, software-defined radios (SDR) platform) have demonstrated the potential by achieving 130 m tag-to-reader distance for a low bit rate of 88 bps with the modulator current consumption at around 103 nA.

Physical Layer Security of Two-Way Ambient Backscatter Communication Systems

Achieving high network traffic demand in limited spectrum resources is a technical challenge for the beyond 5G and 6G communication systems. To this end, ambient backscatter communication (AmBC) is proposed for Internet-of-Things (IoT), because the backscatter device (BD) can realize communication without occupying extra spectrum resources. Moreover, the spectral efficiency can be further improved by using two-way (TW) communication. However, secure communication is a great challenge for accessing massive IoT devices due to the broadcasting nature of wireless propagation environments. In light of this fact, this article proposed a two-way ambient backscatter communication (TW-AmBC) network with an eavesdropper. Specifically, the physical layer security (PLS) is studied through deriving the analytical/asymptotic expressions of the outage probability (OP) and intercept probability (IP). Moreover, the outage probabilities (OPs) in high signal-to-noise ratio (SNR) regions are studied for the asymptotic behavior and the intercept probabilities (IPs) in high main-to-eavesdropping ratio (MER) regions as well. Through analysis and evaluation of simulation performance, the results show that (i) when considering the target node, the OP of the BD decreases with increasing SNR, that is, enhancing the reliability; (ii) an optimal value of BD’s reflection coefficient that maximize the reliability of backscatter link can be obtained; (iii) in high SNR regions, the OPs approach a constant; thus, the diversity orders are zero; (iv) when increasing the MER, the IP of target node decreases, suggesting the security enhances; (v) a trade-off exists between reliability and security which can be optimized by carefully designing the parameters.

Bayesian‐MLE signal detection for multi‐antenna ambient backscatter communication

Multi-antenna signal detection is one of the most critical and challenging issues for ambient backscatter communication (AmBC) systems. This paper proposes an efficient multi-antenna AmBC signal detection method, called Bayesian-MLE (maximum likelihood estimation). It shows good performance on high transmission rate, detection accuracy and low energy consumption. Particularly, a practical multi-antenna AmBC system model is developed to offer transmit-receive diversity, and then an efficient multi-antenna AmBC signal detection method is presented using Bayesian optimization and MLE theory. Furthermore, to maximize the detection performance, an optimal detection threshold selection scheme is developed. Particularly, a non-central chi-square distribution conditional probability density function (PDF) is considered instead of the conventional Gaussian PDF. Extensive qualitative and quantitative experiments are performed, showing that the proposed Bayesian-MLE detector achieves the state-of-the-art signal detection performance.

A Novel SR-DCSK-Based Ambient Backscatter Communication System

In order to expand the application of differential chaos shift keying (DCSK) technology in Internet of Things, a novel ambient backscatter communication system is proposed. In this system, the ambient short reference DCSK (SR-DCSK) signal is ultilized as radio frequency (RF) source, and the modulation waveform design can be easily generated by the state transition of the SR-DCSK modulation symbol according to the transmitted information bit, so as to eliminate strong direct-link interference. Furthermore, a noise reduction method based on averaging operation at the detector is designed for enhancing the bit error rate (BER) performance. Theoretical BER expression over Rayleigh fading channel is derived and validated via simulation. Moreover, the performance of the proposed system is compared with those of other DCSK-based systems.

Sensitivity and distance based performance analysis for batteryless tags with transmit beamforming and ambient backscattering

Ambient backscatter is a new green technology for Internet of Things (IoT) that utilizes surrounding wireless signals to enable batteryless devices to communicate with other devices. The battery-free devices first harvest energy from ambient wireless signals and then backscatter the signals for communications. Clearly, sensitivity and distance are two important parameters for system performance. However, most existing studies on ambient backscatter communication systems do not consider the impact of the sensitivity of the energy-harvesting nodes and the distances between these devices. In this paper, we first provide a literature review for ambient communication technology and then take sensitivity and distance as two key parameters and investigate the sensitivity and distance based performance for ambient backscatter communication systems. Specifically, we establish the mathematical model based on distances between transceivers and backscattering nodes, extract a parameter that can differentiate the direct path and the backscattering path, evaluate the effects of transmit beamforming, design an energy detector for the reader, and analyze the outage probability of energy harvesting at the tag and the bit error rate (BER) at the reader. Simulations are then provided to corroborate the proposed studies.

A Prototype of Reconfigurable Intelligent Surface with Continuous Control of the Reflection Phase

With the development of the next generation of mobile networks, new research challenges have emerged, and new technologies have been proposed to face them. On one hand, the reconfigurable intelligent surface (RIS) technology is being investigated for partially controlling the wireless channels. RIS is a promising technology for improving the signal quality by controlling the propagation of the electromagnetic waves in a nearly passive manner. On the other hand, ambient backscatter communications (AmBC) is another promising technology that is tailored to address the energy efficiency requirements of the Internet of Things. AmBC enables low-power communications by backscattering the ambient signals and thus reusing existing electromagnetic waves for communications. RIS can be utilized in the context of AmBC for improving system performance. In this article, we report a prototype of an RIS that offers the capability of controlling the phase shifts applied to the incident waves in a continuous manner, and we characterize its properties with the aid of full-wave simulations and through experimental measurements. Specifically, we introduce a phase shift model for predicting the signal reflected by the designed RIS prototype. We apply the proposed model for optimizing an RIS-assisted AmBC system, and we demonstrate that the use of an RIS can significantly improve system performance.

Multi-Tag Selection in Cognitive Ambient Backscatter Communications for Next-Generation IoT Networks

In this paper, we propose multi-tag selection schemes to improve achievable rate of a secondary ambient backscatter communication (ABC) system with multiple tags and a single power beacon in cognitive radio (CR) environments. Using the secondary power beacon, which plays a role as radio frequency (RF) source when there is no ambient RF source signals, with spectrum sensing capability, the secondary ABC system determines operation modes according to activity of the licensed primary system. When the primary system is active, a tag is randomly selected due to a lack of channel information, while when it is inactive, the best tag maximizing achievable rate is selected using the secondary power beacon. Moreover, we apply a successive interference cancellation (SIC) technique when the secondary power beacon is able to work. The performance of the proposed multi-tag selection schemes is mathematically analyzed in terms of bit error rate (BER) and achievable rate. Finally, the performance of the proposed schemes is evaluated through simulations in terms of BER and achievable rate. It is shown that our approach can significantly outperform a conventional ABC system in CR environments, especially under a low-active primary system regime.

Coherent Multiantenna Receiver for BPSK-Modulated Ambient Backscatter Tags

Ambient backscatter communication (AmBC) is an emerging communication technology enabling green Internet of Things deployments. The widespread acceptance of this paradigm is limited by the low signal-to-interference-plus-noise ratio (SINR) of the signal impinging on the receiver antenna due to the strong direct path interference and unknown ambient signal. The adverse impact of these two factors can be mitigated by using noncoherent multiantenna receivers, which are known to require a higher SINR to reach the bit-error-rate (BER) performance of coherent receivers. However, considering the unknown ambient signal, unknown location of AmBC tags, and varying channel conditions, coherent receivers for AmBC systems are rarely studied in the literature. In this article, a coherent multiantenna receiver, which requires no prior information of the ambient signal for decoding the binary-phase-shift-keying (BPSK) modulated signal, is presented. The performance of the proposed receiver is compared with an ideal coherent receiver that has perfect phase information, and also with the performance of a noncoherent receiver, which assumes distributions for ambient signal and phase offset caused by the excess length of the backscatter path. Comparative simulation results show the designed receiver can achieve the same BER performance of the ideal coherent receiver with 1-dB more SINR, which corresponds to 5-dB or more gain with respect to noncoherent reception of on-off-keying modulated signals. Variation in the detection performance with the tag location shows that the coverage area is in the close vicinity of the transmitter and a larger region around the receiver, which is consistent with the theoretical results.

When NOMA Multiplexing Meets Symbiotic Ambient Backscatter Communication: Outage Analysis

Non-orthogonal multiple access (NOMA) and ambient backscatter communication (AmBC) have gained a lot of interest as key enabling technologies in wireless communications systems. NOMA is a key player for enhancing spectrum utilization either by multiplexing multiple messages for the same user or allowing multi-users access, while AmBC shows great potential for enhancing both spectrum and energy efficiency for battery-limited devices. In this paper, the performance of a downlink NOMA multiplexing based symbiotic-radio ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$SR$</tex-math></inline-formula> ) AmBC system is analyzed over Nakagami- <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">m</i> fading channels. New closed-form expressions for the exact and asymptotic outage probabilities are derived. Moreover, we analyze the diversity order and the influence of the system parameters on the outage performances. Besides, we proposed a power allocation optimization technique to achieve an outage-optimal performance. Through representative Monte-Carlo simulations, we have verified the analytical results. Finally, we compared the performance of the proposed system against a benchmark OMA-based system.

Analysis of Multi-Tag Ambient Backscatter Communication Under Time-Selective Fading

Ambient backscatter communication (AmBC) is a new technology that has emerged as a potential option for Internet of Things (IoT) applications wherein the sensors and other miniature devices require low power for communication. We proposed a selection combining (SC) diversity scheme and analyze the outage performance of the AmBC system consisting of a moving reader and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$M$ </tex-math></inline-formula> multiple tags. Particularly, we carried out the analysis under time-selective links along with imperfect channel estimation and the outage probability expression is derived. Our results indicate that as the number of tags increases, the probability of an outage lowers drastically and it gets worse with an increase in the speed of the reader as well as estimation error. Furthermore, an asymptotic equation is obtained for the high signal to noise ratio (SNR) case. The derived analytical expressions are validated using Monte Carlo (MC) simulations.

Design of Intelligent Reflecting Surface (IRS)-Boosted Ambient Backscatter Systems

Passive technologies like ambient backscatter communication (AmBC) and intelligent reflecting surface (IRS) hold enormous potential for ubiquitous connectivity of Internet of Things (IoT) devices in future wireless networks. However, despite many research efforts, AmBC has so far been unable to fulfil its potential for widespread deployment, due to the weakness of backscatter signal in the presence of strong direct-link interference from the original RF source. This limits the bit error rate (BER) and hence the transmission rate and range of AmBC systems. Meanwhile, the IRS offers new degrees of freedom in enhancing a variety of systems by transforming their propagation medium and signals. In this work, we devise a novel scheme to improve the detection performance of an AmBC system using an IRS located in its proximity. The IRS augments the backscatter signal quality at the receiver by adjusting its phase shifts to balance signal strengths, ultimately improving the performance of energy detection at the receiver. Our results clearly show that an IRS of reasonable size can considerably improve the BER performance of ambient backscatter, which is an important improvement for low power IoT systems.

Resource Allocation in NOMA-Assisted Ambient Backscatter Communication System

This paper considers a non-orthogonal multiple access (NOMA)-assisted ambient backscatter communication (AmBC) system. To maximize the achievable sum rate (ASR) of the AmBC system, a joint optimization problem over a backscatter device (BD) grouping strategy, reflection coefficients, and decoding order is formulated, where the BD grouping strategy contains the number of BD groups and the BD allocation strategy. The BD grouping strategy, the reflection coefficients, and the decoding order are all intertwined, and the global search is extremely complex. As a result, we propose a four-step optimization algorithm. First, we give the closed-form optimal solution of the BD decoding order and reflection coefficient for a given grouping strategy. Then, for a given number of BD groups, we propose a low-complexity BD allocation strategy based on the complexity–performance trade-off. Finally, the number of BD groups with the largest ASR is selected as the global optimal number of BD groups. The simulation results show that the proposed four-step optimization algorithm is better than the benchmark solution.

IRS-Assisted Ambient Backscatter Communications Utilizing Deep Reinforcement Learning

We consider an ambient backscatter communication (AmBC) system aided by an intelligent reflecting surface (IRS). The optimization of the IRS to assist AmBC is extremely difficult when there is no prior channel knowledge, for which no design solutions are currently available. We utilize a deep reinforcement learning-based framework to jointly optimize the IRS and reader beamforming, with no knowledge of the channels or ambient signal. We show that the proposed framework can facilitate effective AmBC communication with a detection performance comparable to several benchmarks under full channel knowledge.

Ambient Backscatter Communication Design over DCSK Signals

In this paper, a novel ambient backscatter communication system is proposed, in which Differential Chaos Shift Keying (DCSK) modulation signals are adopted as ambient RF source. In order to cancel out the strong direct-link interference as well as reduce the noise impact, a joint design of modulation waveform and signal detector is proposed, and averaging operation is applied to suppress the noise. By comparing correlation values obtained from the reference and information-bearing signals, information bits can be recovered without setting the detection threshold, resulting in reduced detector complexity. The bit error rate (BER) expression over Rayleigh fading channel is derived. The effects of various parameters on the BER performance are also analyzed. Finally, simulation results are provided to verify the advantages of the proposed system.

Enhancing Ambient Backscatter Communication Utilizing Coherent and Non-Coherent Space-Time Codes

Ambient backscatter communication (AmBC) leverages the existing ambient radio frequency (RF) environment to implement communication with battery-free devices. The key challenge in the development of AmBC is the very weak RF signals backscattered by the AmBC Tag. To overcome this challenge, we propose the use of orthogonal space-time block codes (OSTBC) by incorporating multiple antennas at the Tag as well as at the Reader. Our approach considers both coherent and non-coherent OSTBC so that systems with and without channel state information can be considered. To allow the application of OSTBC, we develop an approximate linearized and normalized multiple-input multiple-output (MIMO) channel model for the AmBC system. This MIMO channel model is shown to be accurate for a wide range of useful operating conditions. Two coherent detectors and a non-coherent detector are also provided based on the proposed AmBC channel model. Simulation results show that enhanced bit error rate performance can be achieved, demonstrating the benefit of using multiple antennas at the Tag as well as the Reader.

Performance Analysis of Ambient Backscatter Systems With LDPC-Coded Source Signals

Ambient backscatter communication (AmBC), a promising solution to future Internet of Things (IoT), has attracted increasing attention from both academia and industry in recent years. AmBC systems enable communications between RF-powered devices (e.g., tags and sensors) and AmBC receivers by utilizing ambient RF source signals from existing communication systems. Thus it offers a low-cost and energy-efficient means of communications for future IoT applications. In the current AmBC research, the impact of using channel coding on existing primary networks in terms of the bit-error-rate (BER) performance of the AmBC systems are mostly ignored. Low-density parity-check (LDPC) codes that offer fast encoding and decoding process have been proposed as promising channel codes in the fifth-generation (5 G) networks. In this paper, we investigate the BER performance of an AmBC system that uses LDPC-coded RF source signals. We have analytically derived the BER upper and lower bounds of both the RF source and tag signals for our proposed AmBC system. Simulation results show that the BERs of both signals decrease significantly, compared to conventional AmBC systems with uncoded RF source signals.

Joint Channel, Carrier Frequency Offset and I/Q Imbalance Estimation in Ambient Backscatter Communication Systems

Ambient backscatter communication systems (ABCSs) have been gaining popularity as a green alternative to conventional communication systems. To deploy such systems, it is important to acquire the channel state information (CSI) and to account for hardware imperfections such as carrier-frequency offsets (CFOs) and inphase/quadrature (I/Q) imbalance. In this work, we present two algorithms for the joint estimation of the channel, CFO and I/Q imbalance at the receivers of ABSCs. The first algorithm is the pilot-based maximum-likelihood estimator, while the second is a semi-blind estimator based on the expectation maximization (EM) framework. While both estimators converge to their respective Cramer-Rao bounds, the EM algorithm provides significantly higher estimation accuracy, leading to better bandwidth utilization.