Cellular connected unmanned aerial vehicle (UAV) has been identified as a promising paradigm and attracted a surge of research interest recently. Although the nearly line-of-sight (LoS) channels are favorable to receive higher powers, UAV can in turn
cause severe interference to each other and to any other users in the same frequency band. In this contribution, we focus on the uplink communications of cellular-connected UAV. To cope with the severe interference among UAV-UEs, several different scheduling and power control algorithms are proposed to optimize the spectrum efficiency (SE) based on the geometrical programming (GP) principle together with the successive convex approximation (SCA) technique. The proposed schemes include maximizing the sum SE of UAVs, maximizing the minimum SE of UAVs, etc., applied in the frequency domain and/or the time domain. Moreover, the quality of service (QoS) constraint and the uplink single-carrier (SC) constraint are also considered. The performances of these power and resource allocation algorithms are evaluated via extensive simulations in both full buffer transmission mode and bursty traffic mode. Numerical results show that the proposed algorithms can effectively enhance the uplink SEs of cellular-connected UAVs.
Cellular-connected unmanned aerial vehicles (UAVs) have recently attracted a surge of interest in both academia and industry. Understanding the air-to-ground (A2G) propagation channels is essential to enable reliable and/or high-throughput communicat
ions for UAVs and protect the ground user equipments (UEs). In this contribution, a recently conducted measurement campaign for the A2G channels is introduced. A uniform circular array (UCA) with 16 antenna elements was employed to collect the downlink signals of two different Long Term Evolution (LTE) networks, at the heights of 0-40m in three different, namely rural, urban and industrial scenarios. The channel impulse responses (CIRs) have been extracted from the received data, and the spatial/angular parameters of the multipath components in individual channels were estimated according to a high-resolution-parameter estimation (HRPE) principle. Based on the HRPE results, clusters of multipath components were further identified. Finally, comprehensive spatial channel characteristics were investigated in the composite and cluster levels at different heights in the three scenarios.
Millimeter-Wave (mmWave) has been considered as the key enabler for the fifth generation (5G) communications. The link budget and spectral efficiency of mmWave communications can be further enhanced by adopting the massive multiple-input-multiple-out
put (MIMO) exploiting beamforming. Nevertheless, it is essential to design and test mmWave 5G devices under various realistic scenarios, since the uncontrollable radio propagation channels pose intrinsic limitations on system performance. This requires emulating the realistic dynamic mmWave channels in a reproducible manner in laboratories, hence the goal of this paper. In this contribution, the beamforming effect is firstly investigated, showing that the non-dominant clusters existing in the mmWave channels are insignificant with beamforming operations applied in mmWave 5G devices. Thus, an over-the-air (OTA) emulation strategy for dynamic mmWave channels is then proposed based on a dominant-cluster concept using a sectored multiprobe anechoic chamber (SMPAC) setup. The key design parameters including the probe number and the angular spacing of probes are investigated through comprehensive simulations. A cost-effective switch circuit is also designed for this purpose and validated in the simulation. Furthermore, a dynamic mmWave channel measured in an indoor scenario at 28-30 GHz is presented, where the proposed emulation strategy is also validated by reproducing the measured reality.
Power control is becoming increasingly essential for the fifth-generation (5G) and beyond systems. An example use-case, among others, is the unmanned-aerial-vehicle (UAV) communications where the nearly line-of-sight (LoS) radio channels may result i
n very low signal-to-interference-plus-noise ratios (SINRs). Investigations in [1] proposed to efficiently and reliably solve this kind of non-convex problem via a series of geometrical programmings (GPs) using condensation approximation. However, it is only applicable for a small-scale network with several communication pairs and practically infeasible with more (e.g. tens of) nodes to be jointly optimized. We therefore in this paper aim to provide new insights into this problem. By properly introducing auxiliary variables, the problem is transformed to an equivalent form which is simpler and more intuitive for condensation. A novel condensation method with linear complexity is also proposed based on the form. The enhancements make the GP-based power control feasible for both small-and especially large-scale networks that are common in 5G and beyond. The algorithm is verified via simulations. A preliminary case study of uplink UAV communications also shows the potential of the algorithm.
Millimeter wave (mm-wave) communication with large-scale antenna array configuration is seen as the key enabler of the next generation communication systems. Accurate knowledge of the mm-wave propagation channels is fundamental and essential. In this
contribution, a novel complexity-efficient high resolution parameter estimation (HRPE) algorithm is proposed for the mm-wave channel with large-scale uniform circular array (UCA) applied. The proposed algorithm is able to obtain the high-resolution estimation results of the spherical channel propagation parameters. The prior channel information in the delay domain, i.e., the delay trajectories of individual propagation paths observed across the array elements, is exploited, by combining the high-resolution estimation principle and the phase mode excitation technique. Fast initializations, effective interference cancellations and reduced searching spaces achieved by the proposed schemes significantly decrease the algorithm complexity. Furthermore, the channel spatial non-stationarity in path gain across the array elements is considered for the first time in the literature for propagation parameter estimation, which is beneficial to obtain more realistic results as well as to decrease the complexity. A mm-wave measurement campaign at the frequency band of 28-30 GHz using a large-scale UCA is exploited to demonstrate and validate the proposed HRPE algorithm.
In this paper, a recently conducted measurement campaign for unmanned-aerial-vehicle (UAV) channels is introduced. The downlink signals of an in-service long-time-evolution (LTE) network which is deployed in a suburban scenario were acquired. Five ho
rizontal and five vertical flight routes were considered. The channel impulse responses (CIRs) are extracted from the received data by exploiting the cell specific signals (CRSs). Based on the CIRs, the parameters of multipath components (MPCs) are estimated by using a high-resolution algorithm derived according to the space-alternating generalized expectation-maximization (SAGE) principle. Based on the SAGE results, channel characteristics including the path loss, shadow fading, fast fading, delay spread and Doppler frequency spread are thoroughly investigated for different heights and horizontal distances, which constitute a stochastic model.
