This paper proposes a dynamic radio map (DRM) construction method based on a generative adversarial network (GAN) and AOT attention mechanism to address the increasing demand for radio spectrum resources and the difficulty of existing spectrum allocation methods to meet diversified needs. The method utilizes existing static radio maps (SRMs) and a priori information (e.g., transmitting source parameters, building information, and vehicle locations), generates masks through the path occlusion matrix and adds them to the SRMs, and repairs only the masked areas to complete the construction of the DRMs. The AOT attentional mechanism enhances the network's capability of capturing global information and local texture features of the radio maps by setting up sub-kernels with different expansion rates. Ability. The experiments are conducted on the RadioMapSeer dataset. The results show that the proposed AOTGAN algorithm outperforms other comparative algorithms in terms of Root Mean Square Error (RMSE), Normalized Mean Square Error (NMSE), and Structural Similarity (SSIM) and can efficiently capture the dynamic vehicle factors and recover the real DRM.

Abstract To address the issue of low coverage resulting from the challenge of acquiring the optimal deployment position in commonly used distributed deployment algorithms, this study presents a three‐dimensional deployment algorithm for Unmanned Aerial Vehicles (UAVs) based on potential games. First, a local mutually beneficial game model is designed to demonstrate the existence of exact potential games and Nash equilibrium. The Nash equilibrium solution corresponds to the maximum coverage. Next, drawing inspiration from exploration, a solution method called Exploration Spatial Adaptive Play is proposed. It utilizes the maximum utility function value from multiple step sizes in the exploration direction to update the action selection probability, thereby ensuring the optimal deployment position in each decision cycle. To address the issue of sensor position error, a method for processing sensor position errors is proposed. The simulation results demonstrate that the proposed distributed deployment algorithm achieves higher coverage compared to commonly used methods.

By utilizing intelligent mobile terminals, mobile crowdsensing (MCS) can realize the sensing data collection effectively and economically. However, the privacy security and freshness quality of the obtained sensing data are two major concerns to be addressed in MCS, as they directly impact the system security and timeliness performance. In this regard, we focus on improving the data freshness performance and protecting sensing data content, sensing terminals' identification, and location information simultaneously. Accordingly, based on the artificial noise (AN)-based differential privacy and covert communication technologies, we aim to jointly minimize the Age of Information (AoI) metric and weighted privacy preservation budget in the single terminal scenario. Besides, we achieve the goal of average AoI optimization with data computing requirements in multiple terminal systems, where the privacy preservation budget is treated as the critical constraint. Furthermore, by using the backward induction (BI) method and block successive upper-bound minimization (BSUM) approach, we solve the above two optimization problems, respectively. Finally, compared with the listed baselines, the results evaluate the proposed schemes' effectiveness under various simulation settings.

Green communication has attracted lots of attention recently, where NOMA (Non-Orthogonal Multiple Access) is one of the most promising technologies to realize energy-efficient communication. Specifically, by making massive wireless devices connect to the same time-frequency resource, NOMA can enhance the spectrum efficiency. In this paper, to investigate the freshness of the sensing data, we analyze the Age of Information (AoI) performance in NOMA-enabled Mobile Crowdsensing (MCS) circumstance, where the stochastic geometry theory is adopted. Firstly, we focus on the data submission process between mobile workers (MWs) and service provides (SPs), which drives to establish a model of the NOMA-enabled MCS. Then, given the transmission schemes of NOMA and OMA (Orthogonal Multiple Access), the mathematical expressions of the AoI metric are derived in the closed form respectively. Furthermore, simulation experiments are conducted to obtain AoI numerical results under various parameter settings (e.g., power strategies, queue models, and transmission protocols). Finally, the evaluation results not only prove the validness of the established models, but also provide some efficient solutions to achieve the optimal AoI value under the considered NOMA-enabled MCS scenario.

Unmanned aerial vehicles (UAVs) will be widely deployed due to their flexibility, mobility, and miniaturization, providing the necessary support for spectrum sharing between different communication systems in the space–air–ground-integrated IoT network (SAGIN). However, there are potential security threats to spectrum sharing among different communication systems due to the openness of a wireless network, the unreliability of node behavior, and the trust barriers of the networks. In this article, a secure spectrum sharing scheme based on lightweight UAV-blockchain (LUBC) is proposed to address the above security issues. First, a spectrum sharing model based on the overlay mode is developed to improve the spectrum efficiency of SAGIN, where UAVs relay signals from the satellite to the ground users in exchange for spectrum access opportunities and serve their own users simultaneously in the nonorthogonal multiple access (NOMA) mode. Second, a secure spectrum sharing framework based on LUBC is proposed to solve the security and privacy issues of spectrum trading in SAGIN. Then, aiming at maximizing the primary user’s throughput under the premise of meeting the minimum power allocation factor of UAV network, the spectrum auction based on NOMA is formulated as a multirelay selection optimization problem, which is solved by the blockchain-based sequential Vickrey auction mechanism. Finally, the security evaluation and numerical results are conducted to verify the security and effectiveness of the proposed spectrum sharing scheme for SAGIN.

To efficiently and reliably obtain the target data, mobile crowdsensing (MCS) is widely used to provide the sensing data collection service. Currently, despite concerns of sensing network scale and mobility can be addressed to some degree in the MCS manner, the freshness and privacy goals of the sensing data are still not considered simultaneously. We combine the Age of Information (AoI) with security-enhanced technique to establish a novel MCS system, which can guarantee data freshness and security, respectively. Hence, the problem is formatted as a joint AoI optimization and privacy-preservation process. To solve this problem, we utilize game theory to achieve AoI-oriented spectrum access, and homomorphic encryption to encrypt communication data. Finally, security analysis and numerical results show that our proposed approach can effectively ensure the security level and improve the AoI performance at the same time in MCS.

Abstract In this study, the problem of estimating multiple frequency‐hopping (FH) signal parameters in situations in which random observations are missing is addressed. A uniform linear array (ULA) is utilized to receive FH signals, and the missing observations are considered to be equivalent to randomly missing elements in the space‐time matrix obtained from the ULA. Bayesian compressed sensing (BCS) estimates the hopping time of received FH signals by the spatial information from the space‐time matrix and restores the missing observations. The estimated hopping time is implemented as the boundary to divide the signals such that each segment contains a superposition of time‐invariant multiple components. Then, the instantaneous frequency (IF) of multiple components can be estimated precisely by atomic norm soft thresholding (AST) within each segment. After estimating the hopping time and IF, the direction of arrival (DOA) of multiple signals is directly calculated using these two parameters. The simulation results show that the proposed method is superior to existing approaches. Provided that sufficient array elements are available, multi‐FH signal parameters can be estimated with satisfactory accuracy even when a large portion of observations is missing.

Abstract This paper studies unmanned aerial vehicles (UAV) enabled industrial Internet of Things while a UAV dispatched to collect data of low‐power ground sensor nodes (SNs) in multi‐obstacle environment. The authors aim to minimize the completion time while satisfying the communication link constraints of each SN and obstacle avoidance, data collection requirements etc. To this end, the authors first formulate the completion time minimization problem by jointly optimizing the UAV trajectory and collection sequence of SNs. The problem is difficult to be optimally solved, as it is non‐convex. To tackle this problem, the authors first transform the original problem to a Traveling Salesman Problem‐like (TSP‐like) problem based on a hover point that can naturally satisfy the communication link constraints of data collection. The dynamic programming (DP) algorithm to figure out the order in which the UAV collects each SN, which gives the initial path of the UAV traversing each SN from the beginning point to the end point. Next, the authors consider the general scenarios of data collection tasks where the UAV also communicates while flying. The authors construct an equivalent problem with integer variable constraints for the original problem with indicative function constraints. The authors rewrite the non‐convex constraints of the equal problem by introducing slack variables and leveraging the SCA, and add the discrete region threat constraints for the traditional path discretization method. Finally, the simulation results verify the effectiveness of the proposed algorithm under different parameter configurations.

Due to the emergence of non-terrestrial platforms with extensive coverage, flexible deployment, and reconfigurable characteristics, the hybrid satellite-aerial-terrestrial networks (HSATNs) can accommodate a great variety of wireless access services in different applications. To effectively reduce the transmission latency and facilitate the frequent update of files with improved spectrum efficiency, we investigate the performance of cache-enabled HSATN, where the user retrieves the required content files from the cache-enabled aerial node (AN) or the satellite with the non-orthogonal multiple access (NOMA) scheme. If the required content files of the user are cached in the AN, the cache-enabled node would serve directly. Otherwise, the user would retrieve the content file from the satellite system, where the satellite system seeks opportunities for proactive content pushing to ANs during the user content delivery phase. Specifically, taking into account the uncertainty of the number and location of ANs, along with the channel fading of terrestrial users, the outage probability and hit probability of the considered network are, respectively, derived based on stochastic geometry. Numerical results unveil the effectiveness of the cache-enabled HSATN with the NOMA scheme and proclaim the influence of key factors on the system performance. The realistic, tractable, and expandable framework, as well as associated methodology, provide both useful guidance and a solid foundation for evolved networks with advanced configurations in the performance of cache-enabled HSATN.

Satellite-based Internet of Things (IoT) is recognized as a cost-effective approach for global access. In this article, we aim at improving the spectrum efficiency of satellite systems to serve a huge number of IoT devices. To this end, we present a cognitive satellite-terrestrial framework, where a multibeam satellite system with full frequency reuse shares the spectrum with terrestrial networks based on the underlay paradigm. Considering DVB-S2X recommendations, geometric configurations, and channel characteristics, we investigate a robust multigroup multicast beamforming design for the satellite-based IoT coexisting with terrestrial networks in the presence of a phase error on channel state information, and characterize the achievable rate region under the outage probability constraint for the terminal and the power consumption constraint for the satellite. Based on the concept of rate profile, an associated optimization problem is formulated to design robust beamformers and determine the Pareto boundary of the region. To solve the intractable problem, we propose a two-level iterative algorithm on the basis of joint bisection search and penalty function enabled nonsmooth optimization. In particular, we develop a Bernstein-type inequality aided method and a large deviation inequality aided method to obtain a tractable and conservative approximation for the probabilistic constraint, respectively. Numerical results are provided to confirm the validity and superiority of our proposed scheme over the existing approaches and reveal the impact of key parameters on the achievable system performance.

In this article, we investigate the multichannel cooperative spectrum sharing in hybrid satellite-terrestrial Internet of Things (IoT) networks with the auction mechanism, which is designed to reduce the operational expenditure of the satellite-based IoT (S-IoT) network while alleviating the spectrum scarcity issues of terrestrial-based IoT (T-IoT) network. The cluster heads of selected T-IoT networks assist the primary satellite users transmission through cooperative relaying techniques in exchange for spectrum access. We propose an auction-based optimization problem to maximize the sum transmission rate of all primary S-IoT receivers with the appropriate secondary network selection and corresponding radio resource allocation profile by the distributed implementation while meeting the minimum transmission rate of secondary receivers of each T-IoT network. Specifically, the one-shot Vickrey-Clarke-Groves (VCG) auction is introduced to obtain the maximum social welfare, where the winner determination problem is transformed into an assignment problem and solved by the Hungarian algorithm. To further reduce the primary satellite network decision complexity, the sequential Vickrey auction is implemented by sequential fashion until all channels are auctioned. Due to incentive compatibility with those two auction mechanisms, the secondary T-IoT cluster yields the true bids of each channel, where both the nonorthogonal multiple access (NOMA) and time division multiple access (TDMA) schemes are implemented in cooperative communication. Finally, simulation results validate the effectiveness and fairness of the proposed auction-based approach as well as the superiority of the NOMA scheme in secondary relays selection. Moreover, the influence of key factors on the performance of the proposed scheme is analyzed in detail.

With the extensive research of multiantenna technology, beamforming (BF) will play an important role in the future communication systems due to its high transmission gain and satisfying directivity. If we can detect the non-cooperative beams, it is of great significance in counter reconnaissance, beam tracking, and spectrum sensing of multiantenna transmitters. This paper investigates the wireless sensor networks (WSNs), which is used to detect the unknown non-cooperative beam signal. In order to perceive the presence of beam signals without the prior information, we first derive the detection probability based on the sensors’ received signal strength (RSS). Then, based on the strong directivity of the beam signal, we propose an improved “k rank” fusion algorithm by jointly exploiting the energy detection (ED) information and location information of the sensors. Finally, the beam detection performance of different fusion algorithms is compared in simulation, and we find that our proposed algorithm showed better detection probability and lower error probability. The simulation results verify the correctness and effectiveness of the proposed algorithm.

In this paper, we investigate physical layer security for simultaneous wireless information and power transfer in amplify-and-forward relay networks. We propose a joint robust cooperative beamforming and artificial noise scheme for secure communication and efficient wireless energy transfer. Specifically, by treating the energy receiver as a potential eavesdropper and assuming that only imperfect channel state information can be obtained, we formulate an optimization problem to maximize the worst-case secrecy rate between the source and the legitimate information receiver under both the power constraint at the relays and the wireless power harvest constraint at the energy receiver. Since such a problem is non-convex and hard to tackle, we propose a two-level optimization approach which involves a one-dimensional search and semidefinite relaxation. Simulation results show that the proposed robust scheme achieves better worst-case secrecy rate performance than other schemes.

In this paper, we consider a multiuser downlink wiretap network consisting of one base station (BS) equipped with AA antennas, NB single-antenna legitimate users, and NE single-antenna eavesdroppers over Nakagami-m fading channels. In particular, we introduce a joint secure transmission scheme that adopts transmit antenna selection at the BS and explores threshold-based selection diversity scheduling over legitimate users to achieve a good secrecy performance while maintaining low implementation complexity. More specifically, in an effort to quantify the secrecy performance of the considered system, two practical scenarios are investigated, i.e.: in Scenario I, the eavesdropper's channel state information (CSI) is unavailable at the BS, and in Scenario II, the eavesdropper's CSI is available at the BS. For Scenario I, novel exact closed-form expressions for the secrecy outage probability are derived, which are valid for general networks with an arbitrary number of legitimate users, antenna configurations, number of eavesdroppers, and the switched threshold. For Scenario II, we take into account the ergodic secrecy rate as the principle performance metric, and derive novel exact closed-form expressions for the ergodic secrecy rate. In addition, we also provide simple and asymptotic expressions for secrecy outage probability and ergodic secrecy rate under two distinct cases, i.e.: in Case I, the legitimate user is located close to the BS, and in Case II, both the legitimate user and eavesdropper are located close to the BS. Our important findings reveal that the secrecy diversity order is AAmA and the slope of secrecy rate is one under Case I, while the secrecy diversity order and the slope of secrecy rate collapse to zero under Case II, where the secrecy performance floor occurs. Finally, when the switched threshold is carefully selected, the considered scheduling scheme outperforms other well-known existing schemes in terms of the secrecy performance and complexity tradeoff.

In this paper, we investigate the secrecy performance of multiuser dual-hop relay networks where a base station (BS) communicates with multiple legitimate users through the assistance of a trustful regenerative relay in the presence of multiple eavesdroppers. In particular, the maximal ratio transmission scheme is exploited at the BS and a threshold-based multiuser scheduling scheme is employed over the legitimate users, while concerning the imperfect decoding at the regenerative relay. To evaluate the secrecy performance of the considered system, two practical situations are addressed based on the availability of eavesdropper's channel state information (CSI), i.e., Scenario I, where the eavesdropper's CSI is not available at the relay, and Scenario II, where the eavesdropper's CSI is available at the relay. For both the scenarios, we further consider two eavesdropping modes, i.e., colluding eavesdropping and non-colluding eavesdropping. For Scenario I, new exact and asymptotic closed-form expressions for the secrecy outage probability (SOP) are derived. For Scenario II, we derive new exact and asymptotic closed-form expressions for the ergodic secrecy rate (ESR). The asymptotic SOPs demonstrate that the secrecy diversity order is independent of the number of legitimate users NB and eavesdroppers NE, the number of antennas equipped at eavesdroppers AE, as well as the fading factor of the wiretap channel mE. Furthermore, we also determine the secrecy multiplexing gain and the power cost to explicitly quantify the impact of the legitimate channel and wiretap channel on the ESR. Our findings demonstrate that increasing the switching threshold, the number of antennas at the BS, and the number of legitimate users has a positive impact on secrecy performance.