In air-to-ground unmanned aerial vehicle (UAV) communications, an accurate channel propagation model is very important for the evaluation and design of communication systems. For this purpose, we have conducted several channel measurement campaigns in the airport area at UHF- and L-band (around 433 MHz and 1.518 GHz). In the line-of-sight (LoS) case, we give the distance-dependent pathloss models for both frequenciy bands. Meanwhile, it is found that the measured pathloss in the LoS scenario has a good agreement with the two-ray propagation model at short link distances. This is because of the strong ground reflection path. In the non-LoS (NLoS) case, we propose the elevation-dependent pathloss model at UHF-band based on the field measurement results. On the other hand, considering that the airframe of the UAV can block the wave propagation during the 3-D rotation in the air and the taking off and landing procedures, we specifically analyze the statistical characteristics of the airframe shadowing loss for the two cases and provide the loss distribution models for the fixed-wing, small-sized UAVs made of wood structure and carbon fiber skins.

Integrated sensing and communication (ISAC) is considered one of the key technologies for next-generation wireless communication. To achieve satisfactory communication and sensing performance simultaneously, it is necessary to maximize compatibility with the existing communication waveform. In this paper, we mainly investigate the ISAC constellation design based on communication waveforms (random waveforms). Firstly, we derive the modulated waveform with constant modulus has a smaller side lobe of periodic auto-correlation function (PACF), i.e., the modulated waveform with constant modulus is more suitable for sensing. To improve the sensing performance of the modulated waveform with non-constant modulus, we propose a ISAC constellation design method based on probabilistic constellation shaping (PCS), which designs the power spectrum of the modulated waveform by adjusting the probabilities of constellation points, thereby reducing the side lobe of PACF. In addition, we design a joint optimization problem between the weighted variance of normalized energy and the communication information entropy (CIE) to obtain the tradeoff between communication and sensing. Finally, we simulate the communication performance and sensing performance of the reshaped waveform, and obtain some interesting conclusions. The simulation results show that, for the modulated waveform with non-constant modulus, the proposed method can reduce the side lobe of PACF, and increase the probability of detection (Pd), along with a minimal loss for CIE and a tiny growth for bit error rate (BER). This work is helpful for the theoretical exploration and system design for ISAC.

Air-to-ground (A2G) communication based on Unmanned aerial vehicle (UAV) is an important part of the future communication system. In this paper, an A2G channel model with UAV three-dimensional (3D) wobbles (pitch, roll, and yaw) based on the geometry-based stochastic model (GBSM) is proposed. On this basis, the UAV’s internal vibration is modeled as a sinusoidal random process, and the UAV wobble caused by the atmospheric flow is modeled as the uniform distribution random process. We derive the channel temporal correlation function (CF) with UAV 3D wobbles, analyze the variation of the temporal CF with different carrier frequencies, and amplitudes of the wobble angles. It is found that, even if the UAV wobbles slightly, the channel temporal correlation will be significantly affected. Numerical results show that the channel CF will decrease rapidly with the increase of the amplitudes of wobble angles and the carrier frequency. Therefore, the coherence time of millimeter wave (mmWave) band is significantly less than that of sub-6 GHz band. The consistency of simulation results and measurement results in published papers ensures the availability of the proposed model. For the MUAVs scenario, when the distance between different UAVs is much greater than the wavelength, the A2G channels between different UAVs and user equipment (UE) on the ground are not correlated to each other, and the temporal auto-correlation function (ACF) of each UAV is the same as that of the SUAV scenario. This work contributes to the theoretical exploration and system design of A2G communication based on UAV.

Integrated sensing and communication (ISAC) is one of the key technologies in the sixth generation wireless communication network (6G). The wireless channel modeling for 6G should not only consider the communication channel, but also include the sensing channel. In this paper, we propose an air-to-ground (A2G) channel model for ISAC based on an unmanned aerial vehicle (UAV). We first calculate the channel impulse response (CIR), which sufficiently considers the characteristics of UAV (e.g., UAV wobbles, moving speed, and moving direction), the movement of scatterers, and the moving of user equipment (UE) on the ground. Secondly, we derive the statistical characteristics of the communication channel, including the space-time-frequency correlation function (STF-CF), the Doppler power spectral density (PSD), and the delay PSD. In addition, we model the echo signals from the UE and the scatterers (including the shared scatterers and the unshared scatterers) and investigate the estimation of time delay and Doppler. In addition, we analyzed the impact of UAV random wobbles, moving direction, and height, along with the scatter distributions on channel propagation characteristics. Finally, we simulate the probability of detection (Pd) and present interesting conclusions on the sensing performance related to the modulated waveform and the sensing signal-to-noise ratio (SNR). The simulation results show that the modulation waveform with constant modulus exhibits superior sensing performance compared to the modulation waveform with non-constant modulus. This work is helpful for the theoretical exploration and system design of ISAC based on UAVs.

Compared with the half-duplex (HD), co-time co-frequency full-duplex (CCFD) technology can effectively improve spectrum utilization. Self-interference (SI) is one of the major factors limiting full-duplex (FD) performance. In this letter, we build the same scattering environment as the field measurement campaign, and simulate the FDSI and the conventional base station-to-base station (B2B) channels using ray-tracing technology. We simulate all the multi-path components (MPCs) and observe the power delay profiles (PDPs), received power, and delay spreads (DS) by changing the angular gap between and the height of the transmitting (Tx) and the receiving (Rx) antennas. The parameters and profiles of the simulated SI channel are consistent with and thus verify the measurement results. To further compare the FD channels and the conventional base station-to-user equipment (B2U) channel, we also compare the measured and simulated SI channels with the 3GPP channel model. It is interesting to find out that the channel characteristics are quite similar in the same scenario.