The shortage of spectrum resources has limited the development of Internet of Things (IoT). Fifth generation (5G) network can flexibly support a variety of devices and services, which makes it possible to combine 5G with IoT. In this paper, a novel multichannel IoT is proposed to dynamically share the spectrum with 5G Communication, where an IoT node including transmitter and receiver is designed to perform 5G communication and IoT communication simultaneously. The subchannel sets allocated for 5G communication and IoT communication are defined by two complementary spectrum marker vectors, respectively. Two independent spectrum sequences are generated by calculating the inner product of spectrum marker vector, pseudo-random (PR) phase and power scaling vector. Two time-domain fundamental modulation waveforms (FMW) generated by the inverse fast fourier transform (IFFT) of the spectrum sequences are used to modulate 5G data and IoT data, respectively. The receiver can detect the data using the same spectrum marker vectors as the transmitter. The BER performances of the system using binary modulation and cyclic code shift keying (CCSK) modulation in the cases of spectrum marker error and multiple access are analyzed, respectively. A subchannel and power optimization unit is formulated as a joint optimization problem, which seeks to maximize the 5G throughput under the constraints of minimal IoT throughput, maximal power and maximal interference. An alternative optimization problem is proposed to maximize the IoT throughput while guaranteeing the minimal 5G throughput. A joint optimization algorithm based on Lagrange dual decomposition is proposed to achieve the optimal solution. Simulation results indicate that the proposed IoT can improve the 5G throughput significantly while the IoT throughput is guaranteed.

Satellite communication plays a crucial role in supplementing blind areas and enhancing ubiquitous coverage, to meet the ubiquitous connectivity demands of the future 6G Internet of Things (IoT). As a vital means for integrated space-ground and the intelligent interconnectivity of everything in the future 6G system, Direct-to-Smartphone technology has emerged as a global development hotspot and got widespread attention. This paper analyzes various technical routes and numerous technological challenges of Direct-to-Smartphone technology, and innovatively proposes key technical solutions, such as air interface adapting to high-dynamics, spaceborne ultra-large array multi-beam antennas, on-demand scheduling of extremely narrow beams for random access (RA), and high-integration smartphone design. These solutions support to realize Direct-to-Smartphone technology to adapt the high-dynamic characteristic of Low Earth Orbit (LEO) satellites, provide all-area broadband service, satisfy high-performance and miniaturized. Finally, this paper outlines three potential development directions for Direct-to-Smartphone technology.

In this paper, we investigate unmanned aerial vehicle (UAV) assisted physical layer security in multi-beam satellite enabled vehicle communications. Particularly, the UAV is exploited as a relay to improve the secure satellite-to-vehicle link, and simultaneously serves as a jammer by deliberately generating artificial noise (AN) to confuse Eve. The satellite beamforming (BF) and UAV power allocation (PA) are jointly optimized to maximize the secrecy rate of the legitimate user within a target beam while guaranteeing the quality of service (QoS) of users within other beams. Since the problem is nonconvex, we first convert it into an equivalent two-stage problem. Then, the outer-stage problem is solved by using one-dimensional search, and the inner-stage problem is transformed to a bi-convex problem by using the semi-definite relaxation (SDR) and Charnes Cooper transformation. To solve the inner-stage bi-convex problem, we propose an iterative alternating optimization algorithm, where the optimal BF is obtained by semi-definite programming (SDP), and the optimal UAV PA is subsequently obtained by solving the reformulated fractional programming problem with an iterative Dinkelbach method. The tightness of SDR and the complexity of our proposed approach are analyzed, and extensive simulations are carried out to evaluate the effectiveness of our proposed approach.

In 5G-based cognitive radio, the primary user signal is more active due to the broad frequency band. The traditional cooperative spectrum sensing only detects one characteristic of PU using one kind of detector, which may decrease the sensing performance when the wideband PU is in severe fading channel. In this paper, a multi-modal cooperative spectrum sensing is proposed to make an accurate decision through combining multi-modal sensing data of the PU signal, such as energy, power spectrum, and signal waveform. Each secondary user (SU) deploys multiple kinds of detectors, such as energy detector, spectral detector and waveform detector. The multi-modal sensing data from different detectors are sent to a fusion center. In the fusion center, the local decision is achieved through the Bayesian fusion, while the global decision is determined by the DS fusion. The sensing credibility of each detector can be fully considered in the DS fusion, in order to avoid the performance difference of different detectors. Weight DS fusion is also proposed to improve the decision performance through decreasing the sensing impact of malicious SU while increasing the fusion proportion of dominant SU. The simulation results have shown that the proposed multimodal cooperative spectrum sensing can achieve better sensing performance in fading channel.

Unmanned aerial vehicles (UAVs) equipped with integrated sensing and communication (ISAC) technology have been employed in the field of communication. In this paper, we propose an ISAC-UAV assisted secure communication system amidst multiple eavesdroppers. In each time slot, we implement ISAC and communication functions. Since there are multiple eavesdroppers in the system, jammer UAV is required to send jamming signals to the eavesdroppers. During the ISAC process, the source UAV identifies multiple eavesdroppers, relaying their position information to a jammer UAV. During the communication process, multiple eavesdroppers attempt to intercept the communication link between source UAV and users. We use the center of all users as the horizontal location of the jammer UAV. To maximize the secure data transmit rate, we propose a joint optimization problem involving user scheduling, transmit power, and source UAV trajectory. We break down the non-convex optimization problem into three subproblems, and then achieve the suboptimal solution to the original problem through iteratively optimizing these subproblems. Simulation results indicate that the proposed solution can achieve significant secure transmit rate even in the presence of multiple eavesdroppers.

We propose a robust transceiver design for a covert integrated sensing and communications (ISAC) system with imperfect channel state information (CSI). Considering both bounded and probabilistic CSI error models, we formulate worst-case and outage-constrained robust optimization problems of joint transceiver beamforming and radar waveform design to balance the radar performance of multiple targets while ensuring the communications performance and covertness of the system. The optimization problems are challenging due to the non-convexity arising from the semi-infinite constraints (SICs) and the coupled transceiver variables. In an effort to tackle the former difficulty, S-procedure and Bernstein-type inequality are introduced for converting the SICs into finite convex linear matrix inequalities (LMIs) and second-order cone constraints. A robust alternating optimization framework referred to alternating double-checking is developed for decoupling the transceiver design problem into feasibility-checking transmitter- and receiver-side subproblems, transforming the rank-one constraints into a set of LMIs, and verifying the feasibility of beamforming by invoking the matrix-lifting scheme. Numerical results are provided to demonstrate the effectiveness and robustness of the proposed algorithm in improving the performance of covert ISAC systems.