Unmanned Aerial Vehicle Signal Research Articles

NOMA-Based Energy-Efficiency Optimization for UAV Enabled Space-Air-Ground Integrated Relay Networks

In this paper, an unmanned aerial vehicle (UAV)-enabledspace-air-ground integrated relay system, in which UAV is equipped with phased-array antennas to receive satellite’s signal while utilizing non-orthogonal multiple access (NOMA) schemes to transmit data to land-based users, is proposed. For UAV signal collection, a detection-vector optimization problem can be addressed by introducing a serial of transformations into a second-order cone programming problem. Furthermore, the UAV-ground NOMA communication is summarized into a max-min problem in terms of UAV’s energy efficiency (EE), which is a fractional mixed-integer non-convex problem and has been widely recognized as hard work. Thus, a two-step solution is proposed. Firstly, we transfer the max-min fractional problem into a subtractive one. After that, the transformed problem is further divided into three sub-problems, which are used for jointly performing UAV trajectory optimization, NOMA scheduling optimization, and NOMA power allocation. In addition, the non-convexity of the above-mentioned problem is well solved by using the proposed iterative algorithm, achieving a rapid convergence. Numerical results illustrate the superiority of the proposed EE-NOMA scheme, which achieves three times higher energy-efficient than the conventional spectrum efficiency scheme, and NOMA is shown to globally outperform the orthogonal multiple access in UAV EE circumstance.

Research on anti-jamming beamforming with multi-UAV relays

As the common means of field emergency communication, the unmanned aerial vehicle (UAV) relay plays an important role in both civil and military fields. With the diversification of requirements and the limitations of single operation, multi-UAV cooperative work has attracted extensive attention. However, due to the UAV signal’s universality of broadcast and the limitation of power, information transmission is more likely to be interrupted. Therefore, in the presence of interference, this paper adopts forward amplification protocol under UAV relay transmission model. And two beamforming methods are proposed based on minimizing transmission power and maximizing communication rate of UAV relays. Then, we establish the power-constrained maximum security rate optimization problem with UAV relays, and deduce the corresponding beamforming weight vector and the optimal rate of safety. Finally, the simulation results show the effectiveness and accuracy of the proposed beamforming method.

Electrostatic Signal analysis of rotor UAV

With the rapid growth of unmanned aerial vehicle(UAV) market, incidents of small UAV flying without license or without permission frequently occur, which bring serious hidden dangers to the security of civil airports, sensitive targets and major activities. Rapid and accurate detection and recognition of small UAVs is the basis and premise of countermeasures against small UAVs. However, due to the fact that the production materials of small UAVs are mostly composite materials with good wave-absorbing and wave-penetrating properties and small size, the existing detection technologies such as radar and laser cannot effectively detect the signals of UAVs, so the detection accuracy is very low and the amount of information that can be obtained is small. In this paper, the most typical type of small UAV, rotor UAV, is taken as the research object to study the electrostatic signal of rotor UAV, which provides a theoretical basis for the electrostatic detection of rotor UAV.

Uplink Cooperative Interference Cancellation for Cellular-Connected UAV: A Quantize-and-Forward Approach

Aerial-ground interference is the main obstacle to achieving high spectral efficiency in cellular networks with both traditional terrestrial users and new unmanned aerial vehicle (UAV) users. Due to their strong line-of-sight (LoS) channels with the ground, UAVs could cause/suffer severe interference to/from a large number of non-associated but co-channel base stations (BSs) in their uplink/downlink communications. In this letter, we propose a new cooperative interference cancellation (CIC) scheme for the UAV's uplink communication to mitigate its strong interference to co-channel BSs, which requires only local cooperation between each co-channel BS and its adjacent helping BSs. Specifically, the helping BSs without serving any users in the UAV's communication channel quantize and forward their received signals from the UAV to their aided co-channel BS, which then processes the quantized signals jointly with its own received signal to decode its served terrestrial user's message via canceling the UAV's signal by linear/nonlinear interference cancellation techniques (ICTs). We derive the achievable rates of the proposed CIC scheme with different ICTs as a function of the UAV's transmit power and rate, and thereby unveil the conditions under which the proposed CIC scheme outperforms the existing CIC scheme based on the decode-and-forward (DF) operation of the helping BSs.

Complex-Valued Convolutional Neural Networks Design and its Application on UAV DOA Estimation in Urban Environments

Direction-of-arrival (DOA) estimation is an important task in many unmanned aerial vehicle (UAV) applications. However, the complicated electromagnetic wave propagation in urban environments substantially deteriorates the performance of many conventional model-driven DOA estimation approaches. To alleviate this, a deep learning based DOA estimation approach is proposed in this paper. Specifically, a complex-valued convolutional neural network (CCNN) is designed to fit the electromagnetic UAV signal with complex envelope better. In the CCNN design, we construct some mapping functions using quantum probabilities, and further analyze some factors which may impact the convergence of complex-valued neural networks. Numerical simulations show that the proposed CCNN converges faster than the real convolutional neural network, and the DOA estimation result is more accurate and robust.

Cooperative Downlink Interference Transmission and Cancellation for Cellular-Connected UAV: A Divide-and-Conquer Approach

The line-of-sight dominant air-ground channels have posed critical interference issues in cellular-connected unmanned aerial vehicle (UAV) communications. In this paper, we propose a new base station (BS) cooperative beamforming (CB) technique for the cellular downlink to mitigate the strong interference caused by the co-channel terrestrial transmissions to the UAV. Besides the conventional CB by cooperatively transmitting the UAV's message, the serving BSs of the UAVs exploit a novel interference transmission scheme to effectively suppress the terrestrial interference to the UAV. Specifically, the co-channel terrestrial users' messages are shared with the UAV's serving BSs and transmitted via CB to cancel their resultant interference at the UAV. To balance between the CB gains for UAV signal enhancement and interference cancellation, we aim to maximize the UAV's receive signal-to-interference-plus-noise ratio by jointly optimizing the power allocations at all of its serving BSs for transmitting the UAV's and co-channel terrestrial users' messages. First, we derive the closed-form optimal solution to this problem in a special case and draw useful insights. Then, we propose an algorithm to solve the problem optimally in the general case. As the optimal solution requires centralized implementation with exorbitant message/channel information exchanges among the BSs, we further propose a distributed algorithm that is amenable to practical implementation, based on a new divide-and-conquer approach, whereby each co-channel BS divides its perceived interference to the UAV into multiple portions, each to be canceled by a different serving BS of the UAV with its best effort. Numerical results show that the proposed centralized and distributed CB schemes with interference transmission and cancellation (ITC) can both significantly outperform the conventional CB without applying ITC.

Forming High Gain Wide Beam with NULL Steering Ability to Receive UAV Signal Based on Phased Array Antenna

Successfully achieving the mission of the unmanned aerial vehicle (UAV) requiring a high gain data link between the UAV and the ground control station (GCS). The antenna of the ground station must has a narrow, precisely guided beam towards the UAV. Widening the beamwidth in phased array will be on the expense of reducing the gain and increasing the possibility of receiving the interference signal, this may lead to the failure in achieving the desired link. This paper presents a new method to achieve an automatic forming of the reception beam and automatic tracking of the UAV’s signal in the digital phased array without the need of the complex digital signal processing algorithms used in smart antenna. The proposed approach is based on the complex vector multiplication and phase conjugation technique. The UAV will stay on the beak of the array factor. The resulted array is a combination between retrodirective array and phased array, with beamwidth equal to the field of view without reducing the gain and with null steering ability.