This paper investigates the time scheduling for a backscatter-aided radio-frequency-powered cognitive radio network, where multiple secondary transmitters transmit data to the same secondary gateway in the backscatter mode and the harvest-then-transmit mode. With many secondary transmitters connected to the network, the total transmission demand of the secondary transmitters may frequently exceed the transmission capacity of the secondary network. As such, the secondary gateway is more likely to assign the time resource, i.e., the backscattering time in the backscatter mode and the transmission time in the harvest-then-transmit mode, to the secondary transmitters with higher transmission valuations. Therefore, according to a variety of demand requirements from secondary transmitters, we design two auction-based time scheduling mechanisms for the time resource assignment. In the auctions, the secondary gateway acts as the seller as well as the auctioneer, and the secondary transmitters act as the buyers to bid for the time resource. We design the winner determination, the time scheduling, and the pricing schemes for both the proposed auctionbased mechanisms. Furthermore, the economic properties such as individual rationality and truthfulness, and the computational efficiency of our proposed mechanisms are analytically evaluated. Simulation results demonstrate the effectiveness of our proposed mechanisms.

Unmanned aerial vehicle (UAV)-enabled Internet of Things (IoT) system will play an essential role in future wireless networks, owing to the flexible deployment of the UAVs and the Line-of-Sight (LoS) dominant channels. In this article, we take the limited onboard energy into account and investigate the three-dimensional (3-D) trajectory of the UAV and the transmission scheduling of the ground devices (GDs) for the UAV-enabled IoT system, where multiple GDs transmit data to the UAV in a time-division multiple access fashion. Specifically, taking the angle-dependent probabilistic LoS channel into account, we derive the mathematical expression of the amount of the transmitted data of the GDs and model the energy consumption of the UAV. Next, considering the fairness among the GDs, we aim to maximize the minimum expected amount of the transmitted data of the GDs, and formulate it as an optimization problem, which is further discretized to a problem with a finite number of variables. Due to the nonconvexity of the discretized problem, we transform the problem into a tractable form, and develop an effective iterative algorithm to solve it by using the block coordinate descent and successive convex approximation methods. The convergence and the complexity of the developed algorithm are analytically evaluated. Simulation results demonstrate that our designed 3-D UAV trajectory can effectively improve the minimum expected amount of the transmitted data of the GDs.

Cellular-connected unmanned aerial vehicle (UAV) communications is an enabling technology to transmit control signaling or payload data for UAVs through cellular networks. Due to the line-of-sight dominant air-to-ground channels, efficient interference mitigation is crucial to UAV communications, while the conventional fixed-position antenna (FPA) arrays have limited degrees of freedom to suppress the interference between the UAV and its non-associated co-channel base stations (BSs). To address this challenge, we propose in this letter a new approach by utilizing the six-dimensional movable antenna (6DMA) arrays to enhance the interference mitigation for the UAV. Specifically, we propose an efficient block coordinate descent algorithm to iteratively optimize the antenna position vector, array rotation vector, receive beamforming vector, and associated BS of the UAV to maximize its signal-to-interference-plus-noise ratio. Numerical results show that the proposed 6DMA enhanced cellular-connected UAV communication can significantly outperform that with the traditional FPA arrays and other benchmark schemes in terms of interference mitigation.

As an emerging technique, unmanned aerial vehicle (UAV) aided multi-access edge computing (MEC) network has been improving the performance of the communication network. The novel architecture is beneficial for coverage, flexibility, and reliability. However, reducing network latency is a critical issue. In this paper, we design a UAV-aided network with a millimeter wave (mmWave) backhaul to achieve the multi-access edge computing. The routing problem is formulated and solved first to obtain the optimal routes through the ad hoc link for all users. Then, we formulate the joint trajectory design and resource allocation problem, which is a mixed-integer nonconvex programming, to minimize the network latency. Furthermore, we design a novel iterative algorithm framework to handle this challenging problem. In the outer loop, the proposed problem is separated into the primal problems and master problems by adopting generalized benders decomposition (GBD). In the inner loop, we design the algorithm to solve the continuous nonconvex primal problem by combining the alternating direction method of multipliers (ADMM), Dinkelbach algorithm, and successive convex approximation (SCA) algorithm. The simulation results demonstrate that our proposed algorithm framework is effective and feasible.

This paper presents a unicast beamforming network for covert ambient backscatter communications (AmBC). Different from the prior covert backscatter works using artificial noise or a power-variable RF source, our work achieves covertness by arming the backscatter tag with multiple antennas. The tag uses a subset of its antennas to modulate covert information on backscattered RF signals while using the other antennas to modulate overt message as a cover to hide the covert transmission from the warden. We first derive the warden’s optimum detection threshold to minimize the detection error probability. To fight against the optimum warden, the tag changes impedance matching on each antenna to vary the reflected power and make the reflected overt and covert signals beamforming at space. We derive the optimum beamforming vectors by solving the problems of maximizing the covert rate at the receiver and the detection error probability at the warden, respectively. To address the non-convex constraints, we use semi-definite relaxation (SDR) and obtain near optimal parameters by designing binarySearch algorithms. Numerical results confirm the superiority of our work to the state-of-the-art one, and the existence of tradeoffs between the covert rate and the detection error probability.

In the coming sixth-generation era, space-air-ground integrated network (SAGIN) is a technology with the potential for seamless coverage and high data rate transmission. However, the inherent broadcast nature of wireless communication forces us to consider physical layer security. This paper explores secure communications with the aid of hybrid free space optical/radio frequency (FSO/RF) links in a two-phase uplink transmission. Specifically, in the first-phase transmission, a ground device transmits secrecy data to an unmanned aerial vehicle (UAV) via an RF link, while the UAV emits artificial noise to confuse an eavesdropper. In the second-phase transmission, the UAV sends the secrecy data to a satellite via an FSO link to defend against RF eavesdropping. More specifically, we design two transmission schemes, i.e., slot-based scheme and period-based scheme, which are suitable for transmitting delay-sensitive data and delay-insensitive data, respectively. In order to maximize the average secrecy rate of the system, the trajectory and power allocation of the UAV are jointly optimized. The objective functions of these two schemes are both non-convex, which are mathematically intractable to tackle by the interior-point method. Therefore, we use block coordinate descent and successive convex approximation techniques to obtain approximate solutions. Numerical results reveal the impact of the UAV trajectory and power allocation optimization on the average secrecy rate during different flight periods in different schemes. In addition, other benchmark schemes are considered for comparison, and the results indicate that our proposed schemes can achieve higher average secrecy rates.