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IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)

Beamforming and Power Allocation Design for Secure Backscatter Communication

Eoin Campbell, Mohammadali Mohammadi, Deepak Mishra, Michail Matthaiou

Published Jul 7, 2025• 0 citations
Publisher

Abstract

In this paper, we investigate the physical layer secrecy (PLS) performance of a bi-static backscatter communication (BackCom) system, where a tag reliably communicates with a reader node by reflecting the radio frequency (RF) signal emitted by a source, while a malicious eavesdropper (Eve) attempts to intercept the transmission. To enhance the system's security, we propose an artificial noise (AN) injection scheme, in which the RF source transmits AN to confuse Eve while concurrently serving a legitimate communication user (CU). The objective is to maximize the tag's secrecy spectral efficiency (SSE) by jointly optimizing power allocation and beamforming for both the information signal and AN, subject to practical constraints including a minimum spectral efficiency (SE) requirement for the CU and a total power budget at the RF source. To tackle the resulting non-convex optimization problem, we develop an efficient algorithm based on alternating optimization (AO) to obtain a high-quality suboptimal solution. Simulation results confirm that the proposed design significantly improves secrecy performance compared to conventional schemes based on the null-space projection (NSP) technique.

DOI
10.1109/spawc66079.2025.11143295

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In this paper, we investigate the physical layer secrecy (PLS) performance of a bi-static backscatter communication (BackCom) system, where a tag reliably communicates with a reader node by reflecting the radio frequency (RF) signal emitted by a source, while a malicious eavesdropper (Eve) attempts to intercept the transmission. To enhance the system's security, we propose an artificial noise (AN) injection scheme, in which the RF source transmits AN to confuse Eve while concurrently serving a legitimate communication user (CU). The objective is to maximize the tag's secrecy spectral efficiency (SSE) by jointly optimizing power allocation and beamforming for both the information signal and AN, subject to practical constraints including a minimum spectral efficiency (SE) requirement for the CU and a total power budget at the RF source. To tackle the resulting non-convex optimization problem, we develop an efficient algorithm based on alternating optimization (AO) to obtain a high-quality suboptimal solution. Simulation results confirm that the proposed design significantly improves secrecy performance compared to conventional schemes based on the null-space projection (NSP) technique.
Backscatter communication (BackCom) is widely adopted in Internet of Things (IoT) thanks to its characteristics of low power consumption and low cost. However, it is vulnerable to jamming due to double channel fading of backscattering signal, and the lack of encryption capability in tags increases the risk of eavesdropping. In this paper, we propose a monostatic BackCom system with a multi-antenna reader under hybrid attack, which leverages artificial noise (AN) to degrade eavesdropper’s channel capacity. We also design the transmit beamforming and the combiner to enhance the secrecy rate of the system. Specifically, we formulate a secrecy rate maximization problem with transmit power constraint, which is difficult to solve due to its non-convexity and coupled variables. Hence, we divide it into two subproblems through decoupling the variables and solve them alternately to obtain an overall suboptimal solution. Finally, our numerical results validate our optimization scheme by comparing it with selected benchmarks and showing the fast convergence speed of the proposed algorithm.
Backscatter communication (BackCom) has emerged as a sustainable and green paradigm for large-scale Internet of Things deployments, enabling energy-efficient and low-cost connectivity. However, its open nature makes it highly vulnerable to hybrid attacks combining jamming and eavesdropping. This paper investigates a novel physical-layer security framework for secure data collection in multi-tag monostatic BackCom systems under hybrid attacks. We formulate a joint optimization problem of the transmit precoder, artificial noise, and receive combiner to maximize the sum-secrecy spectral efficiency. To address this, semidefinite relaxation and mixed max-min fractional programming are employed to obtain the optimal precoder and artificial noise, while a closed-form solution is derived for the receive beamformer. By integrating these into a block coordinate descent framework, we develop an iterative algorithm with guaranteed convergence to a near-optimal solution. Simulation results validate the robustness of the proposed design and show substantial performance enhancement, achieving up to 26.45dB gain over conventional benchmarks and 0.47dB over the existing scheme.
This paper considers the physical layer security (PLS) and covertness of the signal transmission in a multiple-input single-output downlink adopting ultra-high reliability and low latency communication (URLLC). In the considered system, Alice transmits confidential signals to Bob in the presence of a multi-antenna eavesdropper (Eve) and a multi-antenna watchful adversary (Willie). Although artificial noise (AN) is a common PLS technique for protecting the confidential signal from wiretapping, it may reduce the communication covertness due to the additional signal emission. For maximizing the achievable secrecy rate, we propose an AN-aided secure and covert communication strategy through optimizing the information carrying beamformer and AN jointly subject to the covertness constraint. To tackle the formulated non-convex design problem, we propose a branch-reduce-and-bound (BRB)-based algorithm to solve the considered problem globally. Simulation results validate its efficiency compared with a benchmark algorithm and unveil the importance of exploiting AN.
Extremely large-scale arrays(XL-arrays) have emerged as a promising technology to improve the spectrum efficiency and spatial resolution of future wireless systems. Different from existing works that mostly considered physical layer security (PLS) in either the far-field or near-field, we consider in this paper a new and practical scenario, where legitimate users (Bobs) are located in the far-field of a base station (BS) while eavesdroppers (Eves) are located in the near-field for intercepting confidential information at short distance, referred to as themixed near-field and far-field PLS. Specifically, we formulate an optimization problem to maximize the sum-secrecy-rate of all Bobs by optimizing the power allocation of the BS, subject to the constraint on the total BS transmit power. To shed useful insights, we first consider a one-Bob-one-Eve system and characterize the insecure-transmission region of the Bob in closed form. Interestingly, we show that the insecure-transmission region is significantlyexpandedas compared to that in conventional far-field PLS systems, due to theenergy-spread effectin the mixed-field scenario. Then, we further extend the analysis to a two-Bob-one-Eve system. It is revealed that as compared to the one-Bob system, the interferences from the other Bob can be effectively used to weaken the capability of Eve for intercepting signals of target Bobs, thus leading to enhanced secrecy rates. Furthermore, we propose an efficient algorithm to obtain a high-quality solution to the formulated non-convex problem by leveraging the successive convex approximation (SCA) technique. Finally, numerical results demonstrate that our proposed algorithm achieves a higher sum-secrecy-rate than the benchmark scheme where the power allocation is designed based on the (simplified) far-field channel model.
This paper considers a multiuser multiple-input single-output (MISO) downlink system with simultaneous wireless information and power transfer. In particular, we focus on secure communication in the presence of passive eavesdroppers and potential eavesdroppers (idle legitimate receivers). We study the design of a resource allocation algorithm minimizing the total transmit power for the case when the legitimate receivers are able to harvest energy from radio frequency signals. Our design advocates the dual use of both artificial noise and energy signals in providing secure communication and facilitating efficient wireless energy transfer. The algorithm design is formulated as a non-convex optimization problem. The problem formulation takes into account artificial noise and energy signal generation for protecting the transmitted information against both considered types of eavesdroppers when imperfect channel state information (CSI) of the potential eavesdroppers and no CSI of the passive eavesdroppers are available at the transmitter. Besides, the problem formulation also takes into account different quality of service (QoS) requirements: a minimum required signal-to-interference-plus-noise ratio (SINR) at the desired receiver; maximum tolerable SINRs at the potential eavesdroppers; a minimum required outage probability at the passive eavesdroppers; and minimum required heterogeneous amounts of power transferred to the idle legitimate receivers. In light of the intractability of the problem, we reformulate the considered problem by replacing a non-convex probabilistic constraint with a convex deterministic constraint. Then, a semi-definite programming (SDP) relaxation approach is adopted to obtain the optimal solution for the reformulated problem. Furthermore, we propose a suboptimal resource allocation scheme with low computational complexity for providing communication secrecy and facilitating efficient energy transfer. Simulation results demonstrate the close-to-optimal performance of the proposed schemes and significant transmit power savings by optimization of the artificial noise and energy signal generation.
This paper considers a multiuser multiple-input single-output (MISO) downlink system with simultaneous wireless information and power transfer. In particular, we focus on secure communication in the presence of passive eavesdroppers and potential eavesdroppers (idle legitimate receivers). We study the design of a resource allocation algorithm minimizing the total transmit power for the case when the legitimate receivers are able to harvest energy from radio frequency signals. Our design advocates the dual use of both artificial noise and energy signals in providing secure communication and facilitating efficient wireless energy transfer. The algorithm design is formulated as a non-convex optimization problem. The problem formulation takes into account artificial noise and energy signal generation for protecting the transmitted information against both considered types of eavesdroppers when imperfect channel state information (CSI) of the potential eavesdroppers and no CSI of the passive eavesdroppers are available at the transmitter. Besides, the problem formulation also takes into account different quality of service (QoS) requirements: a minimum required signal-to-interference-plus-noise ratio (SINR) at the desired receiver; maximum tolerable SINRs at the potential eavesdroppers; a minimum required outage probability at the passive eavesdroppers; and minimum required heterogeneous amounts of power transferred to the idle legitimate receivers. In light of the intractability of the problem, we reformulate the considered problem by replacing a non-convex probabilistic constraint with a convex deterministic constraint. Then, a semi-definite programming (SDP) relaxation approach is adopted to obtain the optimal solution for the reformulated problem. Furthermore, we propose a suboptimal resource allocation scheme with low computational complexity for providing communication secrecy and facilitating efficient energy transfer. Simulation results demonstrate the close-to-optimal performance of the proposed schemes and significant transmit power savings by optimization of the artificial noise and energy signal generation.