Istvan Z. Kovacs’s research while affiliated with Nokia and other places

Cellular-connected unmanned aerial vehicles (UAVs) have recently attracted a surge of interests in both academia and industry. Understanding the air-to-ground (A2G) propagation channels is essential to enable reliable and/or high-throughput communications 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.

Interference management through power control is essential to optimize the system capacity. With the introduction of aerial user equipments in cellular networks, resulting in an increase of line of sight links, power control is becoming more and more vital to enable the (uplink) high-throughput data streaming and protect the users on the ground. The investigation in [1] shows that in the high signal-to-interference-plus-noise (SINR) regime, geometrical programming (GP) can be used to efficiently and reliably solve the problem. In the low SINR regime, a series of GPs are solved by condensation. However, the condensation method proposed in [1] is non-scalable, which hinders its application to a large-scale network, e.g. a densified network, where many more cells could be jointly optimized. In this communication, by transforming the original problem into a standard form introducing auxiliary variables, a new condensation method is proposed. Its complexity linearly increases with the number of links increasing, which makes the power control practically solvable for both small- and large-scale networks. A case study for the up-link UAV communications in cellular networks is performed using the proposed algorithm.

High-throughput unmanned aerial vehicle (UAV) communication may unleash the true potential of novel applications for aerial vehicles but also represents a threat for cellular networks due to the high levels of generated interference. In this article, we investigate how a beamforming system installed on board a UAV can be efficiently used to ensure high-throughput uplink UAV communications with minimum impact on the services provided to users on the ground. We study two potential benefits of beamforming, namely, spatial filtering of interference and load balancing, considering different beam switching methodologies. Our analysis is based on system-level simulations followed by a series of measurement campaigns in live Long-Term Evolution (LTE) networks. Our results show that using UAVside beamforming has a great potential to increase uplink throughput of a UAV while mitigating interference. When beamforming is used, even up to twice as many UAVs may be served within a network compared with UAVs using omni-directional antennas, assuming a constant uplink throughput target. However, to fully exploit the potential of beamforming, a standardized solution ensuring alignment between network operators and UAV manufacturers is required.

Due to safety concerns, a reliable radio communication link is a key component in the future application of unmanned aerial vehicles (UAVs), as it will enable beyond visual line-of-sight (BVLOS) operations. In terms of cost and deployment time, radio communication for aerial vehicles will greatly benefit from the ready-to-market infrastructure and ubiquitous coverage of cellular networks. However, these are optimized for terrestrial users, and the different propagation environment experienced by aerial vehicles poses some interference challenges. In this article, field measurements and system-level simulations are used to assess interferencemitigation solutions that can improve aerial-link reliability. We then discuss how 5 G New Radio (NR) favors the integration of UAVs into cellular networks, as its flexible air interface and beamforming-suited frequencies facilitate the deployment of interference-management solutions.

The fifth-generation (5G) radio networks will support ultra-reliable low-latency communications (URLLC). In the uplink, the latency can be reduced by removing the time-consuming and error-prone scheduling procedure and, instead, using the grant-free (GF) transmissions. Reaching the strict URLLC reliability requirements with GF transmissions is, however, particularly challenging due to the wireless channel uncertainties and interference from other URLLC devices. As a consequence, the supported URLLC capacity and, hence, the spectral efficiency are typically low. Multi-cell reception, i.e., joint reception and combining by multiple base-stations (BS), is a technique known from long-term evolution (LTE), with the potential to greatly enhance the reliability. This paper proposes the use of multi-cell reception to increase the URLLC spectral efficiency while satisfying the strict requirements using GF transmissions in a 5G new radio (NR) scenario. We evaluate the achievable URLLC capacity for an elaborate multi-cell reception parameter space and multi-cell combining techniques. In addition, we demonstrate that rethinking of the radio resource management (RRM) in the presence of multi-cell reception is needed to unleash the full potential of multi-cell reception in the context of UL GF URLLC. It is observed that multi-cell reception, compared to a single-cell reception, can provide URLLC capacity gains from 205% to 440% when the BSs are equipped with two receive antennas and 53% to 22% when BSs are equipped with four receive antennas, depending on whether the retransmissions are enabled.