Recognizing the coverage limitations of traditional reconfigurable intelligent surface (RIS), the simultaneously transmitting and reflecting RIS (STAR-RIS) with the ability to provide coverage on both sides of the surface, has been regarded as a promising technology especially for the integrated indooroutdoor communication environment. In this paper, we investigate a STAR-RIS assisted unmanned aerial vehicle (UAV)-enabled integrated sensing and communication (ISAC) system in the presence of imperfect channel state information (CSI). Specifically, the UAV serves as an aerial base station to provide communication services to outdoor users, as well as positioning for indoor users. To maximize the communication sum-rate while satisfying the sensing beampattern gain requirement, the UAV’s trajectory, beamforming, and the STAR-RIS transmission/reflection coefficients are jointly optimized. Meanwhile, the UAV’s flight safety, the maximum flight duration, and the minimum communication rate for each user are also considered. An online decision-making framework that utilizes deep reinforcement learning (DRL) is proposed to address the sum-rate maximization problem with imperfect CSI. Furthermore, in order to decouple the continuous optimization variables and improve the applicability of the system, we introduce a twin-twin-delayed deep deterministic policy gradient algorithm based on self-attention mechanism (SA-TTD3), which utilizes dual agents to decouple and optimize variables, and incorporates attention mechanisms to improve applicability. The numerical results indicate that the proposed SA-TTD3 algorithm significantly improves the performance of the ISAC system compared with the baseline schemes.

This paper proposes an integrated communication and jamming system design to address the requirements of secure information transmission and interference in modern electronic warfare environments. We develop a signal transmission system capable of generating band-limited white noise-like spectral characteristics within target frequency bands, and introduce an intelligent superposition algorithm that achieves high-precision disguise of band-limited white noise through optimized configuration of carrier signal frequencies and amplitudes. The system employs Non-Orthogonal Multiple Access (NOMA) technology for signal demodulation, transmitting multiple signals carrying identical information over the same time-frequency resource, and enhances reception reliability through successive interference cancellation. We analyze the impact of key parameters—including superimposed signal quantity, adjacent signal power differential, signal-to-noise ratio, and transmission time interval—on spectral similarity and bit error rate performance. Simulation results demonstrate that the proposed intelligent superposition algorithm achieves significantly higher spectral similarity compared to random allocation methods, while ensuring communication reliability with appropriate parameter configurations. This scheme is particularly applicable to military communication scenarios requiring simultaneous covert communication and jamming capabilities, offering substantial practical value for tactical operations.

Unmanned aerial vehicle ad hoc networks (UANET) possess several advantages, such as distributed operation, self-organisation and long-range communication, leading to an exten-sive application in the field of Internet of Things (IoT). However, in practical UANET assisted IoT network scenarios, high degree of dynamism in UAV network topology, coupled with the complex and harsh conditions, adversely affects communication quality. Cluster networking is a well-established and highly effective technique for both organizing and managing UANET. The primary goal of cluster networking is to enhance the networks connectivity and stability by dividing nodes into clusters. This paper presents a novel weighted cluster networking mechanism, which aims to improve the performance of networks. The proposed mechanism involves two primary stages. In the initial networking stage, lowest identification number algorithm is employed to group the nodes. Subsequently, a weighted networking stage utilizes four metrics to enhance the clustering process. The optimal number of clusters is then determined by solving an optimization problem. Simulation results show that our proposed mechanism improves throughput, reduces delays and has better stability and scalability than traditional algorithms.

As an important part of Internet of Things (IoT), the Internet of Vehicles (IoV) has been widely used in traffic intersection control, automatic driving, intelligent navigation, etc. However, due to the dynamic topology and high mobility, IoV faces the challenge of frequent disconnections, which will lead to deterioration in the performance of data dissemination. Motivated by the above, air-to-ground (A2G) integrated IoV is used to bridge the communication gaps between terrestrial vehicles to achieve efficient information transmissions. This paper investigates the application of low altitude platform stations (LAPSs) and reconfigurable intelligent surface (RIS) in A2G integrated IoV, where multiple relaying LAPSs equipped with RISs are adopted to improve the spatial multiplexing gain and create the smart radio environment. To make full use of the advantages of LAPS-and-RIS enhanced transmissions, we formulate a weighted sum rate (WSR) maximization problem by jointly considering the location, power, and phase shift. To tackle this challenging non-convex problem, we design an iterative optimization scheme, where three optimization variables are processed in turn. Simulation results demonstrate that the proposed WSR maximization scheme can significantly improve the communication performance in comparison with other state-of-the-art schemes and the baseline scheme.

Industrial Internet of Things (IIoT), regarded as an important technology for Industry 4.0, has the capability to connect massive IoT devices anywhere and at anytime in manufacturing industry. Enabling such a huge network requires message delivering among sensors, actuators, controllers, and the remote control to be seamless and reliable. However, IIoT wireless environment typically faces challenges such as blockage caused by IoT obstacles. To tackle the above issue, the unmanned aerial vehicle (UAV) and the reconfigurable intelligent surface (RIS) are exploited in this paper, which can provide favorable air-to-ground links and further rebuild the wireless channels. Moreover, the device-to-device (D2D) communication technique is introduced to enable direct information exchange between IoT devices. Specifically, we consider both the communication between the UAV and the cellular users (e.g., fixed IoT infrastructures) as well as the communication between D2D users (e.g., mobile IoT devices). Instead of only considering throughput, we focus on energy efficiency optimization for D2D users while guaranteeing the quality of service for cellular users, since energy-efficient transmission or green communication is important for IIoT scenarios. The transmit power, channel allocation parameters, and RIS’s reflection coefficients are jointly optimized to maximize energy efficiency for D2D users. To solve the formulated optimization problem, both centralized and distributed optimization algorithms based on deep neural networks are provided. Simulation results show that the introduction of RIS can significantly improve system performance. Moreover, the proposed algorithms can approximate the optimal solutions without the need of exhaustive search.

Heterogeneous cellular structure is a potential scheme in the sixth generation (6G) network, where macro and micro base stations (BSs) are collaborated to improve quality of service (QoS) for users. For the conventional heterogeneous cellular networks, data of users is transmitted at one frequency band and perfect channel state information (CSI) is required to beamforming. However, adjacent frequency interference and imperfect CSI decrease the spectrum efficiency (SE) of cellular network and QoS of users. In order to deal with performance loss of SE and QoS, this paper proposes a cognitive radio (CR)-based heterogeneous cellular networks, where opportunistic scheme is applied to improve QoS of users with imperfect CSI. Then, an optimization problem is established, considering both resource allocation and user selection under the constraints of users' QoS requirements. For the convenience of solving, we divide the optimization problem into two suboptimal issues and use an iterative method to approximate the global optimal solution. Numerical results reveal that the proposed scheme can achieve higher SE than the conventional scheme in heterogeneous cellular networks.

In this paper, we investigate the covert communications in uplink nonorthogonal multiple access (NOMA) systems with the random power allocation and multi-carrier modulation scheme to confront a two-phase detector. In the NOMA system, a covert user (CU) and a reliable user (RU) transmit messages to Bob, in the presence of a warden (Willie) who tries to detect CU's transmission behavior. A two-phase detector, i.e., energy detection and similarity detection phases, is designed to improve the detection performance. In addition, we propose a random power allocation and multi-carrier modulation scheme to cover CU's transmissions. For the proposed scheme, the expected minimum detection error probability (EMDEP) and connection outage probabilities (COPs) at RU and CU are derived in closed-form expressions. The maximum expected covert rate (ECR) is analyzed under covertness and reliability constraints. Numerical results show that the proposed two-phase detector has a lower EMDEP, and the multi-carrier modulation scheme improves the covertness performance.

Stability and security are critical to modern wireless communication systems, which have attracted more and more attention in recent years. In this paper, physical layer security (PLS) between the transmitter and the legitimate user (LU) is greatly enhanced by inventing a robust directional modulation (RDM) scheme based on a relaxation phase constraint. Unlike the conventional perfect channel state information (CSI) assumption, the estimation error of LUs' azimuths is assumed, which corresponds to a more practical scenario. Moreover, the influence of the imperfect CSI on the design of artificial noise (AN) vector is investigated. Accordingly, a specific strategy to introduce AN at the transmitter is proposed with imperfect CSI. Numerical simulations suggested that the RDM scheme based on the relaxation phase constraint possesses great potential for the enhancement of security of wireless communications.

Based on the concept of constructive interference (CI), multiuser interference (MUI) has recently been shown to be beneficial for communication secrecy. A few CI-based secure precoding algorithms have been proposed that use both the channel state information (CSI) and knowledge of the instantaneous transmit symbols. In this article, we examine the CI-based secure precoding problem with a focus on smart eavesdroppers that exploit statistical information gleaned from the precoded data for symbol detection. Moreover, the impact of correlation between the main and eavesdropper channels is taken into account. We first modify an existing CI-based precoding scheme to better utilize the destructive impact of the interference. Then, we point out the drawback of both the existing and the new modified CI-based precoders when faced with a smart eavesdropper. To address this deficiency, we provide a general principle for precoder design and then give two specific design examples. Finally, the scenario where the eavesdropper's CSI is unavailable is studied. Numerical results show that although our modified CI-based precoder can achieve a better energy-secrecy trade-off than the existing approach, both have a limited secrecy benefit. On the contrary, the precoders developed using the new CI-design principle can achieve a much improved tradeoff and significantly degrade the eavesdropper's performance.

While constructive interference offers indirect advantages in physical layer security by reducing the transmit power required to achieve a desired performance level, additional gains are possible by choosing the symbols to degrade the eavesdropper's ability to decode the desired data. An algorithm was recently proposed for this purpose, but it assumes an eavesdropper that employs simple nearest-neighbor decoding, and that only exploits a portion of the space available for destructive interference (DI). In this paper, we modify the technique to exploit the full DI region, but we show that even with this improvement, the general approach is vulnerable to an intelligent eavesdropper who can perform maximum likelihood detection. Based on this observation, we propose an alternative approach that, while requiring increased transmit power, can yield the best possible security.

Unlike many existing studies on physical layer security which use multi-antenna techniques to improve the transmission security, this paper exploits the multipath wireless channel to achieve secure transmission. Specifically, we consider a time-reversal transmission system where the signal waveform is designed as the conjugated time reversed counterpart of the wireless multipath channel. Thus, the wireless channel acts as a matched filter that can boost the signal power at the intended receiver. To further improve the transmission security, we also inject a time-domain artificial noise which causes no interference to the intended receiver's signal detection. As for the eavesdroppers, we assume that their specific number and locations are unknown and use the homogenous Poisson point process (HPPP) to model the distribution of them. First, we study the average achievable rate of the intended user and a given eavesdropper, respectively. Then, based on the HPPP model, we can obtain the secrecy outage probability under a given density of eavesdropper. With a given requirement on the secrecy outage probability, we can finally obtain the optimal energy allocation parameter and the corresponding maximum secure transmission rate. Numerical results are presented to show that the proposed scheme can guarantee the transmission security under various system parameters.

This paper studies the secrecy energy efficiency problem for a massive multiple-input multiple-output (MIMO) relaying system. Specifically, the imperfect analog-to-digital converters (ADCs), i.e., ADCs with limited resolution, are employed at the relay, which will cause quantization noise. For the relay strategy, we adopt the amplify-and-forward (AF) relaying protocol. Meanwhile, a null-space artificial noise (AN) is also injected by the relay. To measure the quantization noise, we use the additive quantization noise model (AQNM), which models the quantization error as independent Gaussian noise. Based on this model, the ergodic secrecy rate of the considered relaying system is studied. To maximize the ergodic secrecy rate, we study the power allocation problem at the relay, which allocates power between the forwarded signal and the null-space AN. With the derived optimal power allocation parameter, we then focus on the secrecy energy efficiency, that is, the secrecy rate normalized by the total power consumed at the relay. By using a reasonable energy consumption model, the energy consumption of the ADCs and the transmit power are both included. Numerical results are provided to show that low-resolution ADCs with quantization bits being one or two can achieve the highest secrecy energy efficiency. In addition, higher-resolution ADCs are preferred when the number of antennas becomes smaller.

In order to secure the primary privacy information and provide quality-of-service provisioning for the secondary system, we propose a secondary encryption secure transmission scheme. In the proposed scheme, the primary system utilizes the secure secondary messages to encrypt the primary confidential messages and the secondary system can acquire some spectrum opportunities. Specifically, when the primary system is secure, the primary information can be directly transmitted; when the primary system is insecure while the secondary messages can be securely transmitted, the primary system utilizes the secure secondary messages to encrypt the primary information; otherwise, the spectrum will be utilized for secondary transmission. For the proposed scheme, we investigate the performances of the primary ergodic secrecy rate and the average secondary throughput. Numerical results have demonstrated that the secondary encryption secure transmission scheme can secure the primary privacy messages and improve the secondary transmission throughput.

Physical layer security is a promising technology for secure communication by using wiretap encoding or physical-layer secret key generation. Most of the existing research works study these two techniques separately, which however cannot fully utilize the radio resource. In this paper, we combine the two techniques by using a channel-aware threshold-based approach. Specifically, when the estimated channel gain is larger than the threshold, the wiretap encoding is adopted; otherwise, the secret key generation is performed. For given constraints on security and reliability, we respectively derive the effective secrecy rate of the two techniques and then obtain the secrecy throughput of the proposed scheme through simulations. Numerical results show that the proposed scheme can effectively combine the two techniques and enhance the average secrecy throughput.

Physical layer security (PLS) has emerged as a promising technique to guarantee the secrecy of wireless communication against eavesdroppers. Although extensive studies have been devoted to the PLS-based transmission design, the combination of this physical layer technique and network layer mechanisms such as routing still remains an open problem. This paper concentrates on the security issue for the cognitive radio networks. Specifically, we focus on the routing protocol design for the artificial-noise-aided multi-hop multi-antenna secondary communication against randomly distributed eavesdroppers. We first derive the closed-form expression of secure connection probability (SCP) for a single hop link. We optimize the power allocation between the information signal and artificial noise to obtain the maximum SCP of each link. Then a secure routing problem is formulated whose objective is to find the multi-hop path having the highest secrecy throughput. An optimal routing strategy based on a revised Bellman-Ford algorithm is proposed. We also propose a suboptimal strategy based on the Dijkstra algorithm with lower complexity. From numerical results we find that the selected route always makes a detour around the primary user to enhance the secrecy throughput.

Conventional time-division duplex (TDD) orthogonal frequency division multiplexing (TDD-OFDM) system is vulnerable to the pilot spoofing attack as it mainly relies on employing the deterministic pilot to capture the channel state information (CSI). To solve the abovementioned issue, we in this paper propose an independent component analysis (ICA) based channel identification and estimation (ICA-CIE) mechanism which uses randomized pilot to paralyze the pilot spoofing attack. Specifically, we first convert the pilot spoofing attack to the pilot jamming attack by exploiting pilot randomization. Then, an eigenstructure-based detector (EID) is proposed to realize efficient pilot jamming attack detection. In particular, on one hand, Least Square (LS) method is adopted if no jamming attack is detected. On the other hand, if jamming attack is detected, we further design a channelseparation oriented joint approximate diagonalization of eigenmatrices (CS-JADE) algorithm for channel estimation and identification. Therein, an optimization problem is first formulated to optimize the fourth-order statistical information of the observation data, after which a pilot signal reconstruction scheme is further developed to help identify true sub-channels from the optimization output. Simulation results demonstrate that our proposed ICA-CIE mechanism can achieve highly-accurate channel estimation for the legitimate transceiver pair only by using 6 OFDM symbols within the coherence time. Moreover, we also observe that the estimation accuracy of our proposed mechanism is immune to Eve's transmit power, which further verifies superiority of our proposed mechanism.

Relay transmission can expand the coverage area and improve the communication reliability. However, it may face higher eavesdropping risk due to the additional relay-destination retransmission, which provides eavesdroppers with a second chance to intercept the confidential message. To guarantee the communication secrecy, specially designed transmission strategies are needed. In this paper, we concentrate on the secrecy assurance of a relay network, which is surrounded by colluding eavesdroppers with unknown locations. Specifically, we aim to maximize the secrecy rate by jointly optimizing the power allocation and relay placement. First, we derive the exact expression of the secrecy outage probability. After imposing a constraint on the outage probability, we formulate a secrecy-rate- maximization problem, which is difficult to solve. By using an upper bound, we transform the original problem into a new one, the solution to which is also feasible for the original problem. We then obtain the optimal power allocation between the source and the relay and find the relay's best location to maximize the secrecy rate. It is noted that the derived optimal power allocation is independent of the instantaneous channel state information (CSI), which avoids the frequent change of transmit power and lowers the system complexity. Finally, numerical results are presented to validate our analyses.

Cyber-physical system (CPS), regarded as the next generation of engineered system, has the capability to interact with the real physical world. Applications of CPS span various fields such as medical monitoring, traffic control, and smart grid. With such widespread applications, privacy assurance is becoming more and more important since what the CPS connects are people and the real world. Any leakage of private information will cause serious consequences. In this paper, we focus on enhancing the secrecy of wireless communications in CPS by use of physical layer security techniques. Specifically, we study an amplify and forward (AF) relay network where all devices are equipped with a single antenna. We propose a privacy-enhanced waveform design approach aided by artificial noise (AN) to enhance the communication secrecy in a wireless environment with multipath receptions. First, we consider the case with perfect eavesdropper's channel state information (CSI). We optimize the AF coefficient for forwarding the informationbearing signal and the AN covariance to maximize the achievable secrecy rate. The optimal solution is obtained by solving a series of semidefinite programs. Then, a more practical scenario with imperfect eavesdropper's CSI is studied. We develop a robust waveform design method and obtain the lower bound of the achievable secrecy rate. Numerical results are presented to show the effectiveness of our proposed algorithms.

Noise aggregation is an efficient way of aggregating the inherent noises introduced during wireless transmissions over multiple channels to degrade the eavesdropper's channel quality. While the performance of channel aggregation has not been thoroughly studied over wireless fading channels, we in this paper concentrating on analyses of its achievable average secrecy rate with emphasis on binary symmetric channel (BSC), whose cross-over probability is a time-varying process. The advantage of noise aggregation over traditional transmission in fading environments is demonstrated by our analyses and simulations. Simulation results show that the noise aggregation scheme can achieve a remarkable increase in terms of average secrecy rate even if the eavesdropper has better average channel quality than the legitimate receiver.

In the underlay cognitive radio network, the secondary users are allowed to transmit concurrently with the primary users , which shows great potential to relieve the spectrum scarcity problem. However, it raises significant security issues at the physical layer due to the spectrum sharing approach. Different from most present research, in this paper we study the secure communication problem between secondary users where the primary receiver is a curious passive adversary, i.e., an eavesdropper. Specifically, we consider the worst but common case where the primary receiver can decode the messages from its primary transmitter successfully before trying to decode secondary user's confidential messages. To protect these messages from being eavesdropped, we employ a fullduplex secondary receiver who can broadcast jamming signals to degrade eavesdropper's channel quality while guaranteeing the quality of service (QoS) for primary transmission. Following this framework, we formulate a secrecy capacity maximization problem and obtain the optimal power allocation scheme to allocate power between the secondary transmitter and the fullduplex secondary receiver. Simulations are presented to show the superiority of the optimal scheme over baseline algorithms.