Unmanned aerial vehicle (UAV)-satellite communication has drawn dramatic attention for its potential to build the integrated space-air-ground network and the seamless widearea coverage. A key challenge to UAV-satellite communication is its unstable beam pointing due to the UAV navigation, which is a typical SatCom on-the-move scenario. In this paper, we propose a blind beam tracking approach for Ka-band UAVsatellite communication system, where UAV is equipped with a hybrid large-scale antenna array. The effects of UAV navigation are firstly released through the mechanical adjustment, which could approximately point the beam towards the target satellite through beam stabilization and dynamic isolation. Specially, the attitude information for mechanical adjustment can be realtimely derived from data fusion of low-cost sensors. Then, the precision of beam pointing is blindly refined through electrically adjusting the weight of the massive antennas, where an array structure based simultaneous perturbation algorithm is designed. Simulation results are provided to demonstrate the superiority of the proposed method over the existing ones.

The millimeter-wave (mm-wave) massive multiple-input multiple-output (MIMO) system has gained much attention for its considerable improvement in system throughput. However, the cost of complex hardware, e.g., radio frequency (RF) chains, hinders it from practical deployment. In this paper, we propose an angle domain hybrid precoding and channel tracking method by exploring the spatial features of the mm-wave massive MIMO channel. The number of the effective spatial beams, or equivalently the RF chains, is enormously decreased via the operation of spatial rotation. The users are then scheduled by the angle division multiple access scheme, which groups users according to their direction of arrivals (DOAs). Meanwhile, a channel tracking method is designed for the subsequent data transmission through a small number of pilot symbols. Specifically, the channel information is divided into the DOA information and the gain information, where the DOA information is tracked by a modified unscented Kalman filter and the gain information is estimated from beam training. Numerical results are provided to corroborate our studies.

Unmanned aerial vehicle (UAV) communications could offer flexible scheduling, improved reliability, enhanced capacity over much wider range, and has become a key part of the space-air-ground integrated network. In this letter, we consider a communication system in millimeter wave band, where UAV serves as an airborne base station with multiple antennas, and propose a new flight control system-based channel tracking method. Specifically, the 3-D geometry channel model is formulated as a combination of the UAV movement state information and the channel gain information, where the former can be obtained by the sensor fusion of the flight control system, while the latter can be estimated through the pilot transmission. Simulation results are provided to verify the effectiveness of the proposed method.

Integrated sensing and communications (ISAC) is a key technique for UAV communications. In this paper, we consider the ISAC design for UAV aided communications. Firstly, we build the spatial model under the jittering effects. Meanwhile, we analyze the effect of the UAV movement and attitude variation to the channel. Then, we propose an efficient channel estimation method by utilizing the ISAC technique, where the UAV sensing, the communications, and the control are jointly considered to benefit the system performance. Finally, we provide various simulation results to verify the performance of the proposed method.

Unmanned aerial vehicle (UAV) communications plays an important role in building the space-air-ground network and realizing the seamless wide-area coverage thanks to its longrange connectivity, high maneuverability, flexible deployment, and low latency. Different from the traditional ground-only communications, the control techniques tightly impact UAV communications, which could be jointly designed to enhance the performance of data transmission. In this paper, we explore the opportunities and challenges of combining the communications and control in UAV systems. For single-UAV scenario, we introduce a new frequency-dependent three-dimensional (3D) channel model. We then show how to perform channel tracking with flight control system as well as how to mechanically and electronically formulate the transmission beams. For multi-UAV scenario, we present new techniques as cooperative communications, selfpositioning, trajectory design, resource allocation, and seamless coverage. In the end, we provide some interesting discussions over communication protocol, secrecy, 3D dynamic topology heterogeneous network, and low-cost design for practical UAV applications.

In this paper, we propose a practical integrated sensing and communications (ISAC) framework to sense dynamic targets from clutter environment while ensuring users communications quality. To implement communications function and sensing function simultaneously, we design multiple communications beams that can communicate with the users as well as one sensing beam that can rotate and scan the entire space. To minimize the interference of sensing beam on existing communications systems, we divide the service area into sensing beam for sensing (S4S) sector and communications beam for sensing (C4S) sector , and provide beamforming design and power allocation optimization strategies for each type sector. Unlike most existing ISAC studies that ignore the interference of static environmental clutter on target sensing, we construct a mixed sensing channel model that includes both static environment and dynamic targets. When base station receives the echo signals, it first filters out the interference from static environmental clutter and extracts the effective dynamic target echoes. Then a complete and practical dynamic target sensing scheme is designed to detect the presence of dynamic targets and to estimate their angles, distances, and velocities. In particular, dynamic target detection and angle estimation are realized through angle-Doppler spectrum estimation (ADSE) and joint detection over multiple subcarriers (MSJD), while distance and velocity estimation are realized through the extended subspace algorithm. Simulation results demonstrate the effectiveness of the proposed scheme and its superiority over the existing methods that ignore environmental clutter.