An adaptive physical-layer security enhancement framework for ambient backscatter communication in industrial IoT

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.

This article investigates physical-layer security (PLS) of a typical wireless-powered communication (WPC) system with the aid of intelligent reflecting surface (IRS) in the presence of a passive eavesdropper for Internet of Things (IoT), and proposes three IRS-aided secure WPC modes. Specifically, in mode-I, the IRS is deployed between hybrid access point (HAP) and wireless user (U) for co-located power station (PS) and access point (AP). In mode-II, the IRS is deployed between AP and U for separate PS and AP, while in mode-III, the IRS is deployed between PS and U for separate PS and AP. For each mode, the optimal phase shift is designed to maximize the reception of energy and information at the legitimate receiver. We comprehensively analyze the performance of each mode, and derive the closed-form expressions of connection outage probability (COP), secrecy outage probability (SOP), and effective secrecy throughput (EST) for each mode, respectively. The theoretical analysis and simulation results reveal that from the perspective of reliability, mode-I can achieve the best COP with the increased number of IRS elements, while mode-II and mode-III have a similar COP. From the perspective of security, mode-II can achieve the best SOP with the increased number of IRS elements, while mode-I and mode-III have a similar SOP. Moreover, under the condition of small transmission power at HAP/PS or small number of IRS elements, mode-I has the best EST, while as the power or the number increases, the EST of mode-II becomes the best one.

Secure communication of intelligent reflecting surface-aided NOMA in massive MIMO networks

In this letter, we investigate a novel ambient backscatter communication (AmBC) system in which an intelligent reflecting surface (IRS) acts as a passive transmitter to communicate with a reader. We are interested in the joint design of the IRS reflecting beamforming and symbol detection to minimize the bit error rate (BER). However, the problem is challenging to be solved optimally, since the BER is related to the clustering-based detector without a concrete close-form expression and the IRS reflecting unit modulus constraint is non-convex. To solve this issue, we propose a novel deep unfolding neural network (DUNN) combining data-driven and model-driven for passive reflecting beamforming design and symbol detection, which is learned to approximate the BER model from the training samples and the unit modulus constraint is satisfied by treating the optimization variables as network parameters. Numerical results demonstrate that the proposed scheme has superior performance of detection.

This letter studies physical layer security (PLS) in non-orthogonal multiple access (NOMA) power line communication (PLC) networks. A source node transmits information to two nodes of near and far users with different power allocations. We consider two different cases of eavesdropping: internal and external. The PLC channel and noise are modeled by correlated log-normal fading and Bernoulli-Gaussian random process, respectively. We derive closed-form expressions for the secrecy outage probability (SOP) of both the internal and external cases by applying Gauss-Chebyshev quadrature, which are verified by Monte Carlo simulations. We observe that higher impulsive noise degrades the SOP while higher channel correlation can improve the SOP. In addition, the analytic results reveal the impact of power allocation on the SOP performance.

Intelligent reflecting surface (IRS), which uses passive reflective elements instead of active radio frequency (RF) chains, is a cost and energy-efficient solution to improve the wireless system performance. With a similar objective, transmit antenna selection (AS) reduces the number of RF chains at the base station while harnessing the benefits of multiple antennas. In our work, we focus on joint optimization of antenna subset and transmit beamforming at the base station, and passive beamforming at the IRS to maximize the receive signal power. For single AS, we first derive a closed-form optimal rule. We then propose a simpler AS rule, which significantly reduces the computational complexity and the number of pilot transmissions required. For a system with Nt antennas at the base station and N IRS elements, the optimal AS rule requires N <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">t</sub> + N <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">t</sub> N pilots. However, the proposed simpler rule requires only 2N <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">t</sub> +N pilots. For subset AS, we develop a manifold optimization based algorithm. To reduce its subset search complexity, which is exponential in the number of RF chains at the base station, we propose an alternating optimization based iterative algorithm. Our numerical results show that the proposed simpler AS rules are near optimal.

In this study, the secrecy outage probability (SOP) of a dual-hop energy harvesting (EH) non-orthogonal multiple access (NOMA) system is investigated. In order to improve the signal quality at the transmitter node, the transmitter antenna selection (TAS) method is applied, while the generalized selection combining (GSC) technique is used to increase the reliability at the users and maximum ratio combining (MRC) is utilized at eavesdropper (EVE). In the system, the relay node harvests energy from the signals received from the base station (BS) and transmits messages to the users with the amplify-and-forward (AF) protocol. In the study, the findings for the SOP are presented with Monte Carlo simulations. The study shows that there is a trade-off between harvested energy, data rate and SOP performance, while power allocation factors have an impact on secrecy performance.

This article introduces a novel strategy for wireless communication security utilizing intelligent reflecting surfaces (IRS). The IRS is strategically deployed to mitigate jamming attacks and eavesdropper threats while improving signal reception for legitimate users (LUs) by redirecting jamming signals toward desired communication signals leveraging physical layer security (PLS). By integrating the IRS into the backscatter communication system, we enhance the overall secrecy rate of LU, by dynamically adjusting IRS reflection coefficients and active beamforming at the base station (BS). A design problem is formulated to jointly optimize IRS reflecting beamforming and BS active beamforming, considering time-varying channel conditions and desired secrecy rate requirements. We propose a novel approach based on deep reinforcement learning (DRL) named Deep-PLS. This approach aims to determine an optimal beamforming policy capable of thwarting eavesdroppers in evolving environmental conditions. Extensive simulation studies validate the efficacy of our proposed strategy, demonstrating superior performance compared to traditional IRS approaches, IRS backscattering-based anti-eavesdropping methods, and other benchmark strategies in terms of secrecy performance.

With the advent of technology and growing demand for energy-efficient technology in wireless communication, there is a need to ponder over the Security aspect of the Wireless Ambient system. In this paper, we have done an Analysis of Physical Layer Security for Ambient Backscatter Communication having Multiple Tags and Mobile sources using Performance Analysis based on Secrecy Outage Probability. More specifically we have derived an equation for SOP considering source mobile and plotted results with varying relative speed and the number of tags.

We consider an intelligent reflecting surface (IRS)-assisted communication system as a cost-effective technique to enhance secrecy rate performance in physical-layer security (PLS) systems. In this letter, the randomized radiation (RR)-based PLS algorithm, which uses active antenna arrays to randomize the radiation pattern, is adopted in IRS through passive beamforming. We show that RR cannot be simply applied to IRS because the secrecy rate is subject to the phase-dependent amplitude variations in IRS. Therefore, we provide an exact and closed-form expression for the secrecy rate of RR using IRS. Based on the analysis, we introduce a constant phase shift into the IRS elements and identify it as a key parameter to optimize the secrecy performance through a genetic algorithm.

Multi-carrier code division multiple access (MC-CDMA)has been considered as a strong candidate for next generation wireless communication system due to its excellent performance in multi-path fading channel and simple receiver structure. However, like all the multi-carrier transmission technologies such as OFDM, the inter-carrier interference (ICI) produced by the frequency offset between the transmitter and receiver local oscillators or by Doppler shift due to high mobility causes significant BER (bit error rate) performance degradation in MC-CDMA system. Many ICI cancellation methods such as windowing and frequency domain coding have been proposed in the literature to cancel ICI and improve the BER performance for multi-carrier transmission technologies. However, existing ICI cancellation methods do not cancel ICI entirely and the BER performance after ICI cancellation is still much worse than the BER performance of original system without ICI. Moreover, popular ICI cancellation methods like ICI self-cancellation reduce ICI at the price of lowering the transmission rate and reducing the bandwidth efficiency. Other frequency-domain coding methods do not reduce the data rate, but produce less reduction in ICI as well. In this paper, we propose a novel ICI cancellation scheme that can eliminate the ICI entirely and offer a MC-CDMA mobile system with the same BER performance of a MC-CDMA system without ICI. More importantly, the proposed ICI cancellation scheme (namely Total ICI Cancellation) does not lower the transmission rate or reduce the bandwidth efficiency. Specifically, by exploiting frequency offset quantization, the proposed scheme takes advantage of the orthogonality of the ICI matrix and offers perfect ICI cancellation and significant BER improvement at linearly growing cost. Simulation results in AWGN channel and multi-path fading channel confirm the excellent performance of the proposed Total ICI Cancellation scheme in the presence of frequency offset or time variations in the channel, outperforming existing ICI cancellation methods.

Intelligent reflecting surface (IRS) is a very promising technology for the development of beyond 5G or 6G wireless communications due to its low complexity, intelligence, and green energy-efficient properties. In this paper, we combined IRS with physical layer security (PLS) to solve the security issue of cognitive radio (CR) networks. Specifically, an IRS-assisted multi-input single-output (MISO) CR wiretap channel was studied. To maximize the secrecy rate of secondary users subject to a total power constraint (TPC) for the transmitter and interference power constraint (IPC) for a single antenna primary receiver (PR) in this channel, an alternating optimization (AO) algorithm is proposed to jointly optimize the transmit covariance R at transmitter and phase shift coefficient Q at IRS by fixing the other as constant. When Q is fixed, R is globally optimized by equivalently transforming the quasi-convex sub-problem to convex one. When R is fixed, bisection search in combination with minorization–maximization (MM) algorithm was applied to optimize Q from the non-convex fractional programming sub-problem. During each iteration of MM, another bisection search algorithm is proposed, which is able to find the global optimal closed-form solution of Q given the initial point from the previous iteration of MM. The convergence of the proposed algorithm is analyzed, and an extension of applying this algorithm to multi-antenna PR case is discussed. Simulations have shown that our proposed IRS-assisted design greatly enhances the secondary user’s secrecy rate compared to existing methods without IRS. Even when IPC is active, the secrecy rate returned by our algorithm increases with transmit power as if there is no IPC at all.

This paper focuses on the bit error rate (BER) performance of intelligent transportation communication system under multipath mobile frequency-selective channels. After presenting the theoretical BER performance formula of single carrier frequency domain equalization (SC-FDE) in the form of double integral, a closed-form approximate upper bound of BER performance was derived，as well as specific analytical expressions for approximate BER performance bounds under typical modulations. Analysis and simulation show that the derived approximate BER bound highly approaches the theoretical one. The bound also indicates that the research about the preferable equalization methods is still necessary.

A physical layer security (PLS) technique called Gray Code Hopping (GCH) is presented offering simplistic implementation and no bit error rate (BER) performance degradation over the main channel. A synchronized transmitter and receiver "hop" to an alternative binary reflected Gray code (BRGC) mapping of bits to symbols between each consecutive modulation symbol. Monte Carlo simulations show improved BER performance over a similar technique from the literature. Simulations also confirm compatibility of GCH with either hard or soft decision decoding methods. Simplicity of GCH allows for ready implementation in adaptive 5th Generation New Radio (5G NR) modulation coding schemes.

End-to-end learning of a communications system using the deep learning-based autoencoder concept has drawn interest in recent research due to its simplicity, flexibility and its potential of adapting to complex channel models and practical system imperfections. In this paper, we have compared the bit error rate (BER) performance of autoencoder based systems and conventional channel coded systems with convolutional coding (CC), in order to understand the potential of deep learning-based systems as alternatives to conventional systems. From the simulations, autoencoder implementation was observed to have a better BER in 0-5 dB E <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">b</sub> /N <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sub> range than its equivalent half-rate convolutional coded BPSK with hard decision decoding, and to have only less than 1 dB gap at a BER of 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-5</sup> . Furthermore, we have also proposed a novel low complexity autoencoder architecture to implement end-to-end learning of coded systems in which we have shown better BER performance than the baseline implementation. The newly proposed low complexity autoencoder was capable of achieving a better BER performance than half-rate 16-QAM with hard decision decoding over the full 0-10 dB E <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">b</sub> /N <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sub> range and a better BER performance than the soft decision decoding in 0-4 dB E <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">b</sub> /N <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sub> range.