Symbiotic radio (SR) has emerged as a spectrum and energy-efficient paradigm to support massive Internet of Things connections. This paper investigates secure transmission in a multi-antenna artificial noise (AN)-assisted SR network under both parasitic SR (PSR) and commensal SR (CSR) setups, with a particular focus on the challenges posed by the presence of a passive eavesdropper. Specifically, the transmitter allocates part of its power for AN generation to disrupt the eavesdropper deliberately without affecting the legitimate receiver. To evaluate the secrecy performance in both setups, new approximate closed-form expressions for the secrecy outage probability in primary and backscatter links are derived using the Gauss-Chebyshev quadrature method. The secrecy diversity orders of the system are studied by analyzing the asymptotic behaviours in the high signal-to-noise ratio regime. Furthermore, the secrecy performance under imperfect channel state information is investigated to evaluate the robustness of the proposed scheme in practical scenarios. Monte Carlo simulations are performed to validate the correctness and effectiveness of the analytical results, which demonstrate that the CSR setup provides stronger secrecy performance than the PSR setup in primary signal decoding.

In this paper, we explore the utilization of double-irregular intelligent reflecting surfaces (IRS) for secure wireless transmissions, where "irregular" refers to the non-uniform arrangement of IRS elements on an expanded grid surface. The main objective is to maximize the secrecy rate by optimizing the arrangement of IRS micro-units and their phase shift matrices, subject to the transmission power constraint. Unlike previous research, this paper introduces the deployment of two IRSs with irregular distributions in a secure communication system, taking into account their reflective interaction. Additionally, the paper addresses both discrete and continuous phase considerations for IRS elements. Toward this end, we first propose a tabu search algorithm to simultaneously optimize the distribution matrices of both IRSs. Specifically, it employs alternating optimization techniques: for discrete phase adjustments, a cross-entropy method is applied, while for continuous phase shifts, a simulated annealing algorithm is used. Numerical results show that the proposed scheme significantly outperforms the regular scheme in enhancing the secrecy performance of the proposed system. Moreover, the suboptimal solutions found are closer to the optimal solution when leveraging irregular scheme.

Mission-critical applications are of significant importance to sixth generation (6G)’s massive and ubiquitous Internet of things (IoT) communications. The mission-critical applications mostly fall within the scope of finite blocklength (FBL), and in order to assess the information freshness, age of information (AoI) has been introduced. However, packet error is inevitable in the FBL regime, which exerts impacts on the time for successful packet transmission, and thus increases the AoI. To optimize the performance of AoI, the management of queue packets is an effective way. Motivated by optimizing the AoI performance in the FBL regime, we consider a system equipped with a single buffer, and propose two schemes of packet management in this article. We subsequently derive the closed-form expressions for the average AoI and the average peak AoI and we discuss the relationship between AoI and the factors, i.e. the blocklength, data generation rate and signal-to-noise ratio. Afterwards, we give the optimal blocklength expression associated with the optimal AoI. In order to examine the information timeliness in the network under the proposed schemes, the closed-form expressions of the average delay are deduced. The simulation results validate the theoretical analysis and demonstrate the advantage of the proposed scheme in terms of the performance of AoI, delay, and their trade-off.

Employing ambient backscatter communication (AmBC) technology in Intelligent Transportation Systems (ITS) has emerged as an appealing solution to boost the awareness of crosswalks. However, the AmBC-based ITS is expected to face serious security threats due to the presence of malicious eavesdroppers. In this paper, we investigate the secure multi-antenna transmission in an AmBC-based ITS coexisting with a passive eavesdropper with jamming. Specifically, a cooperative jammer is placed in the system to deliberately disrupt the eavesdropper without affecting the legitimate receiver. In order to characterize the performance of the proposed scheme, new approximate closed-form expressions of secrecy outage probability (SOP) are derived by adopting the Gauss-Chebyshev quadrature. Additionally, the asymptotic behavior of SOP at the high signal-to-noise ratio (SNR) regime is also studied to provide more insights into the system design. We also derive the asymptotic SOP, when the number of transmit antennas tends to infinity. Monte Carlo simulations are provided to demonstrate the validity of our analytical results and to show that 1) the secrecy performance can be significantly improved by allocating part of the transmit power to perform cooperative jamming and 2) the optimal power allocation factor is related to the total transmit power.

Ambient backscatter communication (AmBC) has emerged as a paradigm distinguished by its energy-efficient attributes and low-power dynamics, ideally suited to address the vast expanse of the Internet of Things (IoT). Unmanned aerial vehicles (UAVs) deployed with flexibility can effectively establish wireless connections for isolated IoT devices through AmBC. This paper delves into the exploration of secure transmission within a UAV-assisted AmBC network, particularly addressing the challenges posed by the presence of a passive eavesdropper. Specifically, a UAV is utilized as an aerial base station to offer services to an isolated ground user, an AmBC tag transmits its information to its associated receivers by leveraging the UAV’s radio frequency (RF) signals. Furthermore, a multi-antenna cooperative jammer is integrated within the system to intentionally interfere with the eavesdropper without affecting legitimate receivers. To characterize the secrecy performance, the expressions of secrecy outage probability of the air-ground link and backscatter link are both deduced leveraging a two-layer Gaussian-Chebyshev quadrature. Moreover, the asymptotic behaviors under the high signal-to-noise ratio (SNR) regime are also analyzed. Monte Carlo simulations are performed to validate the correctness and effectiveness of the analytical results.

Orthogonal Time Frequency Space (OTFS) modulation has been proposed to provide seamless and reliable communication in high-mobility environments. In particular, OTFS modulation enables the delay-Doppler (DD) domain model to be represented sparsely so that the compressed sensing (CS) algorithms can be applied in channel estimation to get more accurate channel state information (CSI). However, conventional CS algorithms in OTFS channel estimation assume that channel sparsity$K$is known, which is not available in some practical applications. In this paper, we propose the sparsity adaptive matching pursuit (SAMP) algorithm for OTFS channel estimation without prior information of the channel sparsity$K$, and we further propose a variable step-size backtracking sparsity adaptive matching pursuit (VSB-SAMP) to improve both accuracy and reconstruction speed. We first formulate the channel estimation problem as a sparse signal recovery problem. Then, the SAMP algorithm is introduced to solve the problem that channel sparsity is unknown. Furthermore, a VSB-SAMP is proposed to accelerate reconstruction speed. Simulation results show that the proposed algorithm can achieve accurate channel state information with less iterations.

This paper investigates the power allocation problem for secure multiple-input single-output transmission with the injection of artificial noise (AN), in the presence of an unknown eavesdropper (Eve). Two power allocation schemes, the optimal adaptive power allocation (OAPA) and suboptimal fixed power allocation (SFPA) schemes, are proposed to enhance the physical layer security of the considered system. Since the noise power at Eve is unknown, both power allocation schemes are designed for the worst-case scenario in which the noise power at Eve is assumed to be zero, aiming to minimize the secrecy outage probability (SOP). To characterize the performance of the proposed power allocation schemes, approximate closed-form expressions for average SOP under a preset noise power level are derived by applying Gauss-Chebyshev quadrature. We also address the worst-case secrecy outage performance for the proposed OAPA and SFPA schemes. Our analytical and numerical results show that, compared with the exhaustive search method that requires Eve’s prior information, the proposed OAPA scheme exhibits comparable secrecy outage performance without Eve’s prior information. Additionally, the SFPA scheme, also without Eve’s prior information, is capable of achieving almost the same worst-case SOP as the OAPA scheme, with a much lower implementation complexity.

Ultra-dense network (UDN) is emerging as a promising technology to satisfy the explosive data traffic requirement in the fifth generation wireless communication systems. In order to facilitate system design and evaluate performance, this paper develops a tractable analysis framework of K-tier UDNs over Nakagami-m fading channels, in which the base stations (BSs) of each tier have a particular spatial density and transmit power. Using stochastic geometry, we derive the closed-form expression of coverage probability for a typical user. The analytical expression reveals the signal-to-interference-plus-noise ratio (SINR) invariance property of UDNs with Rayleigh fading also holds in Nakagami-m fading scenario when each tier has the same fading parameter. The asymptotic expression with a simple form is also provided, from which it is convenient to observe the effects of system parameters on the coverage probability. The simulation results verify the asymptotic form is very accurate for moderate SINR targets, e.g., above 5 dB. The average outage rate of a typical user is also provided. Furthermore, an effective algorithm is proposed to find the optimal SINR threshold, maximizing the average outage rate with appropriate requirements of coverage probability.

This paper investigates power allocation problem for secure multiple-input single-output transmission with artificial noise (AN). With an unknown eavesdropper, we propose an optimal adaptive power allocation scheme, which adaptively adjust the power allocation factor (PAF) according to the instantaneous channel state information of the legitimate channel. On this basis, we derive a closed-form expression for the optimal PAF aiming to minimize the secrecy outage probability (SOP). A suboptimal fixed power allocation scheme is also proposed to reduce system complexity. Moreover, exact closed-form expressions of SOP for both schemes are also obtained.

In this paper, we investigate the physical layer security of an underlay cognitive decode-and- forward (DF) relay network, in which one secondary transmitter (ST) exchanges confidential information with one secondary destination (SD) with the aid of multiple cognitive DF relays by sharing the licensed spectrum of one primary user (PU), and multiple colluding eavesdroppers attempt to intercept the secondary transmission. Due to deep fading, it is assumed that there is no ST-SD link, one of the cognitive relays is selected to convey the confidential information, while the others emit artificial noise (AN) in an effort to confuse the eavesdroppers. In the absence of the eavesdroppers' channel information state (CSI), we analyze the secrecy outage performance under two opportunistic relay selection schemes, which are the conventional relay selection (CRS) and the best relay selection (BRS) schemes. We derive novel closed-form expressions for the secrecy outage probability with these two relay selection schemes. Simulation results are provided to verify our analysis, and shows that the secrecy performance of the propose BRS scheme significantly outperforms the CRS one.

In this study, non‐orthogonal multiple access (NOMA)‐based coordinated direct and relay transmission (CDRT) is considered, where a base station ( BS ) directly communicates with two cell‐centre users (CCUs) while communicating with a cell‐edge user (CEU) via a relay. A novel dynamic scheme is proposed, in which the CCU close to the BS will act as a relay to assist the CEU in the second phase if it can obtain the prior information of the CEU in advance, otherwise it will switch to the receiving mode. To evaluate the system performance of the proposed scheme, the closed‐form expressions of the outage probability, diversity order and ergodic sum rate (SR) are, respectively, derived. Simulation results demonstrate that the proposed scheme attains greater diversity order for the CEU as well as superior outage performance without performance loss of the ergodic SR, compared with conventional one in NOMA‐based CDRT. In addition, a suboptimal power allocation (SPA) for this dynamic scheme is put forward, for which the closed‐form expression is also obtained. It is also indicated that the presented SPA for dynamic scheme achieves near‐optimal ergodic SR performance at high SNR region.

Acquisition of accurate channel state information (CSI) at transmitters results in a huge pilot overhead in massive multiple input multiple output (MIMO) systems due to the large number of antennas in the base station (BS). To reduce the overwhelming pilot overhead in such systems, a structured joint channel estimation scheme employing compressed sensing (CS) theory is proposed. Specifically, the channel sparsity in the angular domain due to the practical scattering environment is analyzed, where common sparsity and individual sparsity structures among geographically neighboring users exist in multi-user massive MIMO systems. Then, by equipping each user with multiple antennas, the pilot overhead can be alleviated in the framework of CS and the channel estimation quality can be improved. Moreover, a structured joint matching pursuit (SJMP) algorithm at the BS is proposed to jointly estimate the channel of users with reduced pilot overhead. Furthermore, the probability upper bound of common support recovery and the upper bound of channel estimation quality using the proposed SJMP algorithm are derived. Simulation results demonstrate that the proposed SJMP algorithm can achieve a higher system performance than those of existing algorithms in terms of pilot overhead and achievable rate.

To improve physical (PHY) layer security of a wireless relay system in the presence of an eavesdropper, a two-phase cooperative relaying scheme is investigated in this paper. In phase I, the source transmits confidential message, simultaneously, it cooperates with the friendly jammers and destination to create jamming signal at the eavesdropper without affecting the forwarding relay which is preselected. In phase II, the forwarding relay retransmits the decoded signal, meanwhile, the particular relay cooperates with the friendly jammers to create jamming signal at the eavesdropper without affecting the destination. We focus on the investigation of optimal power allocation for maximizing achievable secrecy rate subject to a total power constraint. Optimal relay selection and suboptimal relay selection schemes are also proposed. It is shown that as the number of relays increases, both secrecy rate and the performance of suboptimal relay selection scheme improve significantly. Numerical results are presented to validate the derived analytical results and compare them to existing work.