This paper addresses the challenge of energy-constrained maritime monitoring networks by proposing an unmanned aerial vehicle (UAV)-enabled integrated sensing, communication, powering and backhaul transmission scheme with a tailored time-division duplex frame structure. Within each time slot, the UAV sequentially implements sensing, wireless charging and uplink receiving with buoys, and lastly forwards part of collected data to the central ship via backhaul links. Considering the tight coupling among these functions, we jointly optimize time allocation, UAV trajectory, UAV-buoy association, and power scheduling to maximize the performance of data collection, with the practical consideration of sea clutter effects during UAV sensing. A novel optimization framework combining alternating optimization, quadratic transform and augmented first-order Taylor approximation is developed, which demonstrates good convergence behavior and robustness. Simulation results show that under sensing quality-of-service constraint, buoys are able to achieve an average data rate over 22 bps/Hz using around 2 mW harvested power per active time slot, validating the scheme’s effectiveness for open-sea monitoring. Additionally, it is found that under the influence of sea clutters, the optimal UAV trajectory always keeps a certain distance with buoys to strike a balance between sensing and other multi-functional transmissions.

In this work, we explore energy-efficient covert underwater acoustic backscatter communications (EC-UABCom) within the framework of the Internet of Underwater Things (IoUT). Specifically, a passive buoy node covertly transmits acoustic information passively to a maritime receiver by reflecting incident acoustic carrier signals from an autonomous underwater vehicle (AUV) transmitter. Simultaneously, the system exploits the uncertainty of underwater noise to mask the covert backscatter information, thereby evading detection by a submarine warden. To optimize the covert strategy, we first derive the warden’s optimal power-detection threshold that minimizes the detection error probability, accounting for underwater noise uncertainty. In response to this optimal detection strategy, we propose an energy-efficient covert policy by jointly optimizing the AUV’s transmit power and the buoy’s reflection coefficient to meet the covertness constraint. We then conduct a performance analysis, providing a closed-form expression for the expected detection error probability at the warden and outage probability at the receiver, thereby revealing their inherent trade-off. Numerical simulations validate the effectiveness of our approach compared to the state-of-the-art methods, demonstrating that higher transmit power and reflection coefficient degrade covertness while improving covert rate performance.

Considering the critical issue of interference management in cell-free massive MIMO with underlaid device-todevice (CF-mMIMO-D2D) maritime systems, in this paper, we propose a novel approach, namely CFD-HetGNN, utilizing the heterogeneous graph neural network (HetGNN) to deal with the joint optimization of beamforming and power allocation for both the CF-mMIMO users and D2D pairs. By modeling the CF-mMIMO-D2D as a heterogeneous graph, we take advantage of the HetGNN to capture the complex interactions among access points, mobile stations and D2D pairs, enabling an efficient solution of interference mitigation. Simulation results demonstrate that the proposed CFD-HetGNN significantly improves the spectral efficiency and achieves superior interference control compared to the traditional approach of matched filtering with equal power allocation (MF-EPA) as well as the learning-assisted methods of convolutional neural network (CNN), deep neural network (DNN) and long short-term memory (LSTM). Additionally, the CFD-HetGNN possess the robust scalability, making it applicable to the large-scale networks with low complexity.

With line-of-sight mode deployment and fast response, unmanned aerial vehicle (UAV), equipped with the cutting-edge integrated sensing and communication (ISAC) technique, is poised to deliver high-quality communication and sensing services in maritime emergency scenarios. In practice, however, the real-time transmission of ISAC signals at the UAV side cannot be realized unless the reliable wireless fronthaul link between the terrestrial base station and UAV are available. This paper proposes a multicarrier-division duplex based joint fronthaul-access scheme, where mutually orthogonal subcarrier sets are leveraged to simultaneously support four types of fronthaul/access transmissions. In order to maximize the end-to-end communication rate while maintaining an adequate sensing quality-of-service (QoS) in such a complex scheme, the UAV trajectory, subcarrier assignment and power allocation are jointly optimized. The overall optimization process is designed in two stages. As the emergency area is usually far away from the coast, the optimal initial operating position for the UAV is first found. Once the UAV passes the initial operating position, the UAV’s trajectory and resource allocation are optimized during the mission period to maximize the end-to-end communication rate under the constraint of minimum sensing QoS. Simulation results demonstrate the effectiveness of the proposed scheme in dealing with the joint fronthaul-access optimization problem in maritime ISAC networks, offering the advantages over benchmark schemes.

In this paper, we study uplink covert communication in a space-air system, where an unmanned aerial vehicle (UAV) transmits sensitive data to a Geosynchronous Earth Orbit (GEO) satellite while preventing the transmission action from being discovered by a warden. We derive the optimal decision threshold of the warden. We investigate the 3-dimensional (3D) beamformer and 3D trajectory design for the transmitter UAV against this optimum warden to maximize the covert transmission rate in the presence of imperfect channel state information and uncertain noise. Due to the non-convex structure and dependence between beamforming vectors and locations of the transmitter UAV, we develop a decoupling method that specifies a feasible flight region of the transmitter UAV at each time slot, enabling the decomposition of the original optimization problem into two sub-problems that optimize the trajectory and beamforming vectors individually. We design an iterative algorithm with a new initialization method to solve the sub-problems alternately with the semi-definite relaxation (SDR) and the successive convex approximation (SCA) technique. Numerical results show that the average covert rate of our design approaches the ideal case without the warden and increases by about 102.3% and 19.1% compared with benchmark schemes that do not employ beamforming or design 2D trajectory, respectively.

Physical layer steganography plays a key role in physical layer security. Yet most works are strongly modulation-sensitive and have to modify the modulation at the baseband. However, these methods cannot work with wireless devices whose baseband modulations cannot be software-defined. To overcome these drawbacks, we propose an analog solution that uses a symbiotic hardware component designed, called Pluggable Cloak, connecting to the radio frequency front end (RFFE) to establish a steganographic symbiotic channel (SSC) over constant envelope physical layer (CE-PHY) in 2.4GHz ISM band, such as Bluetooth, ZigBee and 802.11b Wi-Fi, to hide information. The advantage lies in enabling secure transmission of the deployed devices that are not software-defined with this pluggable hardware. Specifically, Pluggable Cloak analogously modulates the amplitude of CE-PHY, so that sensitive information can be securely sent to a customized receiver without being detected by regular CE receivers. To further protect hidden information from the detection of a malicious adversary, we propose methods to randomize the SSC. We develop a lightweight prototype to evaluate symbiosis, undetectability, and throughput. The results show that the symbol error rates (SERs) of the sensitive data received and regular CE data are lower than$10^{-5}$at the customized receiver. In contrast, the SER of the sensitive data is close to 1 in the adversary, confirming the effectiveness of the SSC technique.

With little or no human intervention, almost every object in Internet of Things (IoT) has ability to communicate, sense, and process information to make everything connected. Noise in complex environment has a great impact on machine-to-machine (M2M) interaction in IoT. Adaptive wavelet threshold function (AWTF)-based M2M Gaussian Noise Removal Method is proposed in this article. First, a bilateral enhanced wavelet threshold function is derived based on the adjustable zeroing window. Further, threshold is used to construct a bilateral enhanced wavelet threshold function, which can eliminate the oscillations in the existing wavelet threshold function. This ensures that there is no break in wavelet coefficients during the reconstruction process and that stable wavelet decomposition and reconstruction can be achieved. The signal-to-noise ratio (SNR) of a signal is estimated based on the variance of the noise-containing signal, and the zeroing window parameters are adjusted adaptively according to the SNR value to eliminate the noisy wavelet coefficients and improve the denoising performance. In addition, when the wavelet coefficients are reconstructed, the proposed algorithm can select a suitable threshold function according to a particular threshold value, which improves the robustness of the algorithm. “Doppler” and “Bumps” standard test signals are used as interactive signals to simulate the proposed algorithms. For “Doppler” signals, the SNR, root mean square error (RMSE), and noise suppression ratio (NSR) of AWTF increased by 8.48%, 42.59%, and 1.69%, respectively, compared with the GDES+ABC algorithm. For “Bumps” signal, the SNR, RMSE, and NSR of AWTF are improved by 11.67%, 24.46%, and 2.99%, respectively, compared with GDES+ABC algorithm. In addition, we also use different modulated signals to carry out real field experiments in Qingdao cruise ship home port, which proves the effectiveness of the proposed algorithm.

This paper studies covert MIMO ambient backscatter communication (AmBC). In contrast to the prior covert AmBC works, we equip all devices with multiple antennas, where a backscatter tag works as a beamformer to hide both his transmission behavior and location from a warden. Technically, we derive two key metrics, namely the Kullback-Leibler divergence (KL divergence) measuring the transmission covertness and the covert rate measuring the transmission efficiency. We reveal that they both increase monotonically w.r.t the number of the tag’s antenna. This tradeoff makes the optimum parameter configuration non-trivial. To this end, we optimize the beamformer of the tag to maximize the covert rate subject to the covertness constraint under perfect knowledge of the warden’s channel state information (WCSI). We use the matrix permutation and semi-definite relaxation (SDR) method to make the formulated non-convex problem convex, and obtain the solution with the barrier method. We also study the impact of imperfect WCSI. To address the uncertain estimate error, we use the S-Procedure to reformulate the constraints linearly and the primal-dual interior-point method for a near-optimal solution. We conduct extensive numerical experiments and confirm that our work outperforms the state-of-the-art ones.

This paper presents a covert ambient backscatter communication (AmBC) system aided by the intelligent reflecting surface (IRS), where an IRS is used as a beamformer to help Tag for covert AmBC. Technically, we derive the expression of the Kullback-Leibler (KL) divergence to measure the detection performance of the warden. To fight against the warden’s detection, we propose a joint IRS’s beamforming and Tag’s reflection coefficient optimization scheme to maximize the covert AmBC rate subject to a key constraint metric of the KL divergence. To solve the non-convex problem, we formulate it as Fractional Programming (FP) for the linear iterations, and use the Majorization-Minimization (MM) algorithm to obtain the optimal parameters of IRS and Tag. Moreover, we investigate the covert performance with the imperfect channel state information of the warden’s link (WCSI) with Tag and IRS. Numerical results show the covert performance of the system, and illustrate the superiority of the IRS’s assistance to the covert backscatter efficiency. The simulations also show that the channel estimated error of Tag-Willie link has a negative impact on the covert backscatter efficiency, while the channel estimated errors of IRS-Willie link have the positive influence on the contrary.

OFDM backscatter is crucial in passive IoT. Most of the existing works adopt phase-modulated schemes to embed tag data, which suffer from three drawbacks: symbol-level modulation limitation, heavy synchronization accuracy reliance, and small symbol time offset (STO) / carrier frequency (CFO) offset tolerability. We introduce SubScatter, the first subcarrier-level frequency-modulated OFDM backscatter which is able to tolerate bigger synchronization errors, STO, and CFO. The unique feature that sets SubScatter apart from the other backscatter systems is our subcarrier shift keying (SSK) modulation. This method pushes the modulation granularity to the subcarrier by encoding and mapping tag data into different subcarrier patterns. We also design a tandem frequency shift (TFS) scheme that enables SSK with low cost and low power. For decoding, we propose a correlation-based method that decodes tag data from the correlation between the original and backscatter OFDM symbols. We prototype and test SubScatter under 802.11g OFDM WiFi signals. Comprehensive evaluations show that our SubScatter outstands prior works in terms of effectiveness and robustness. Specifically, SubScatter has 743kbps throughput, 3.1× and 14.9× higher than RapidRider and MOXcatter, respectively. It also has a much lower BER under noise and interferences, which is over 6× better than RapidRider or MOXcatter.

This paper presents TiScatter, a timespan-based WiFi backscatter system that provides high-throughput communication with a single COTS receiver used. It outperforms the prior works that tradeoff between considerable data rate and practical deployment. To improve the data rate, TiScatter introduces a symbol-level times-pan modulation method that encodes tag data into the timespan between two modulated WiFi codewords in two successive WiFi packets. For decoding, TiScatter for the first time employs the injective feature between the checksum and the modulated codeword positions, which enables the demodulation of both the tag and original WiFi data using only one COTS receiver. This makes TiScatter more practical. Furthermore, we design TiScatter+ that shows these advantages while providing an even higher throughput under 802.11b excitations. We prototype our design, and comprehensive evaluations demonstrate that TiScatter shows a throughput over 100× higher than prior single-receiver backscatter systems like FS-Backscatter. It even has a better BER and throughput than the prior double-receiver backscatter systems like MOXcatter. Specifically, TiScatter provides 1) 2× higher peak throughput than MOXcatter and 2) an order of magnitude lower BER than MOXcatter with the presence of substantial interferences. In addition, TiScatter+ can deliver a throughput 3× higher than TiScatter under 802.11b ambient excitations. Our evaluation also confirms that TiScatter is generic and applicable to excitations under diverse WiFi standards (e.g., 802.11b/g/n).

This paper presents a unicast beamforming network for covert ambient backscatter communications (AmBC). Different from the prior covert backscatter works using artificial noise or a power-variable RF source, our work achieves covertness by arming the backscatter tag with multiple antennas. The tag uses a subset of its antennas to modulate covert information on backscattered RF signals while using the other antennas to modulate overt message as a cover to hide the covert transmission from the warden. We first derive the warden’s optimum detection threshold to minimize the detection error probability. To fight against the optimum warden, the tag changes impedance matching on each antenna to vary the reflected power and make the reflected overt and covert signals beamforming at space. We derive the optimum beamforming vectors by solving the problems of maximizing the covert rate at the receiver and the detection error probability at the warden, respectively. To address the non-convex constraints, we use semi-definite relaxation (SDR) and obtain near optimal parameters by designing binarySearch algorithms. Numerical results confirm the superiority of our work to the state-of-the-art one, and the existence of tradeoffs between the covert rate and the detection error probability.

In this work, we study the covert communications in ambient backscatter systems (ABS) with uncontrollable RF source on AWGN channels. In contrast to the prior works impractically assuming the existence of acontrollableRF excitation source, our work arms the receiver of covert information with the full-duplex ability. The covert receiver can emit artificial noise (AN) with variable power to cover up the modulation action of a tag on the excitation signals while receiving the backscattered information. Specifically, we first derive the warden’s optimum power-detection threshold that minimizes the detection error probability. To against the optimal warden, we design the covert backscatter communication policy that determines the feasible region of the AN power at the covert receiver depending on the transmission power of the RF source and the reflection coefficient of the tag and guarantees the covertness constraint. We analyze the performance of the policy and provide the closed-form maximum covert rate and maximum detection error probability at the warden, revealing their tradeoff. The numerical analysis shows the increasing transmission power of the RF source and tag’s reflection coefficient would degrade the covertness of ABS when the covert receiver has to increase the AN power.