Effective spectrum sharing requires a nuanced understanding of how radio activity varies not only across frequency and geography but also with altitude, an increasingly important dimension for drone networks and non-terrestrial systems. This paper presents a comprehensive survey of existing spectrum measurement studies in the sub-6 GHz range, identifying major gaps in coverage, such as limited measurements involving altitude variation, a lack of longitudinal datasets, and the absence of publicly available geotagged aerial data. To address these limitations, we conduct a multi-year spectrum monitoring campaign using an aerial platform equipped with software-defined radios (SDRs), operating in both urban and rural areas of Raleigh, NC, USA. The aerial platform enables high-resolution measurements of spectrum activity from the ground up to 300 m. We analyze occupancy patterns across licensed and unlicensed bands, including Long Term Evolution (LTE), 5G (New Radio) (NR), and Industrial, Scientific, and Medical (ISM) bands, and document year-over-year changes that reflect evolving commercial deployments and regulatory trends. We further perform an altitude-dependent analysis of spectrum occupancy and received power across the 89 MHz–6 GHz range, highlighting how three-dimensional measurement perspectives reveal usage patterns that are not observable from ground-level sensing alone. Our results demonstrate that altitude is a critical dimension for spectrum characterization and should be considered in future spectrum policy, sensing strategies, and system design. This study provides both a literature-based and measurement-based foundation for altitude-aware spectrum analytics, supported by a publicly available geotagged dataset to enable reproducible research for emerging aerial networks and non-terrestrial communication systems.

The growing demand for unmanned aerial vehicle (UAV) based aerial connectivity across urban and rural environments highlights the need for a deeper understanding of spectrum occupancy in aerial corridors. In particular, understanding the altitude-dependent behavior of spectrum occupancy in cellular networks is critical, as such understanding could be used to enable beyond visual line of sight (BVLOS) UAV connectivity in the future. While there are existing models for characterizing altitude-dependent interference in the literature, they are not validated by data and need to be compared with real-world measurements. To address these gaps, in this paper, we conduct cellular spectrum occupancy measurements at various sub-6 GHz bands for altitudes up to 300 meters, in both urban and rural environments. To characterize the real-world spectrum occupancy behavior, we introduce two different approaches: a new theoretical model utilizing stochastic geometry with altitude-dependent factors (SOSGAD), and a ray-tracing model tailored to site-specific line of sight (LOS) and non-LOS scenarios. We also derive the asymptotic behavior of the SOSGAD model as the UAV altitude increases. Through comparative analysis, we evaluate how well the SOSGAD and ray-tracing models characterize altitude-dependent spectrum occupancy in both uplink and downlink scenarios.

Advancements in unmanned aerial vehicle (UAV) technology have led to their increased utilization in various commercial and military applications. One such application is signal source search and localization (SSSL) using UAVs, which offers significant benefits over traditional ground-based methods due to improved RF signal reception at higher altitudes and inherent autonomous 3D navigation capabilities. Nevertheless, practical considerations such as propagation models and antenna patterns are frequently neglected in simulation-based studies in the literature. In this work, we address these limitations by using a two-ray channel model and a dipole antenna pattern to develop a simulator that more closely represents real-world radio signal strength (RSS) observations at a UAV. We then examine and compare the performance of previously proposed linear least square (LLS) based localization techniques using UAVs for SSSL. Localization of radio frequency (RF) signal sources is assessed based on two main criteria: 1) achieving the highest possible accuracy and 2) localizing the target as quickly as possible with reasonable accuracy. Various mission types, such as those requiring precise localization like identifying hostile troops, and those demanding rapid localization like search and rescue operations during disasters, have been previously investigated. In this paper, the efficacy of the proposed localization approaches is examined based on these two main localization requirements through computer simulations.

The ever-growing demand for wireless connectivity, coupled with limited spectrum resources, has resulted in spectrum congestion and interference. This research investigates the probability of occupancy in common sub-6 GHz cellular network bands based on measurements conducted in urban and rural environments. Specifically, we analyze the spectrum occupancy of various long-term evolution (LTE), 5thgeneration (5G) and Citizens Broadband Radio Service (CBRS) bands used in the United States, considering both uplink and downlink transmissions at altitudes up to 180 meters. Additionally, we explore the influence of altitude on the probability of spectrum occupancy in these bands. Our findings reveal that the probability of occupancy is generally higher in the downlink compared to the uplink. Moreover, we observe that line-of-sight (LoS) signals play a critical role in higher altitudes. These results provide insights spectrum utilization in various cellular bands across different altitudes, with implications on interference and spectrum coexistence between terrestrial networks and unmanned aerial systems (UASs) in the future.

Due to the scarcity of spectrum resources, the emergence of new technologies and ever-increasing number of wireless devices operating in the radio frequency spectrum lead to data congestion and interference. In this work, we study the effect of altitude on sub-6 GHz spectrum measurement results obtained at a Helikite flying over two distinct scenarios; i.e., urban and rural environments. Specifically, we aim at investigating the spectrum occupancy of various long-term evolution (LTE), 5thgeneration (5G) and citizens broadband radio service (CBRS) bands utilized in the United States for both uplink and downlink at altitudes up to 180 meters. Our results reveal that generally the mean value of the measured power increases as the altitude increases where the line-of-sight links with nearby base stations is more available. SigMF-compliant spectrum measurement datasets used in this paper covering all the bands between 100 MHz to 6 GHz are also provided.

Unmanned aerial vehicles (UAVs) are expected to be used extensively in the future for various applications, either as user equipment (UEs) connected to a cellular wireless network, or as an infrastructure extension of an existing wireless network to serve other UEs. Next generation wireless networks will consider the use of UAVs for joint communication and radar and/or as dedicated radars for various sensing applications. Increasing number of UAVs will naturally result in larger number of communication and/or radar links that may cause interference to nearby networks, exacerbated further by the higher likelihood of line-of-sight signal propagation from UAVs even to distant receivers. With all these, it is critical to study network coexistence of UAV-mounted base stations (BSs) and radar transceivers. In this paper, using stochastic geometry, we derive closed-form expressions to characterize the performance of coexisting UAV radar and communication networks for spectrum overlay multiple access (SOMA) and time-division multiple access (TDMA). We evaluate successful ranging probability (SRP) and the transmission capacity (TC) and compare the performance of TDMA and SOMA. Our results show that SOMA can outperform TDMA on both SRP and TC when the node density of active UAV-radars is larger than the node density of UAV-comms.

Radio dynamic zones (RDZs) are geographically bounded areas where novel advanced wireless technologies can be developed, tested, and improved, without the concern of interfering to other incumbent radio technologies nearby the RDZ. In order to operate an RDZ, use of a real-time spectrum monitoring system carries critical importance. Such a monitoring system should detect out-of-zone (OoZ) signal leakage outside of the RDZ, and if the interference to nearby receivers is intolerable, the monitoring system should be capable of mitigating such interference. This can e.g. be achieved by stopping operations inside the RDZ or switching to other bands for RDZ operation. In this paper, we introduce a spectrum monitoring concept for OoZ signal leakage detection at RDZs, where sensor nodes (SNs) are installed at the boundary of an RDZ and monitor the power leakage from multiple transmitters within the RDZ. We propose a prediction algorithm that estimates the received interference at OoZ geographical locations outside of the RDZ, using the measurements obtained at sparsely located SNs at the RDZ boundary. Using computer simulations, we evaluate the performance of the proposed algorithm and study its sensitivity to SN deployment density.

Physical layer security (PLS) techniques can help to protect wireless networks from eavesdropper attacks. In this paper, we consider the authentication technique that uses fingerprint embedding to defend 5G cellular networks with unmanned aerial vehicle (UAV) systems from eavesdroppers and intruders. Since the millimeter wave (mmWave) cellular networks use narrow and directional beams, PLS can take further advantage of the 3D spatial dimension for improving the authentication of UAV users. Considering a multi-user mmWave cellular network, we propose a power allocation technique that jointly takes into account splitting of the transmit power between the precoder and the authentication tag, which manages both the secrecy as well as the achievable rate. Our results show that we can obtain optimal achievable rate with expected secrecy.

Using radio frequency (RF) coverage from the existing cellular networks is an attractive option to maintain beyond visual line-of-sight (BVLOS) connectivity with drones. These cellular drones can connect with a ground control station (GCS) for control and data delivery wherever cellular service is available. However, RF coverage for these cellular networks has been optimized for the ground users and while they do leak upwards, reliable RF coverage exists to only about 400 feet high. As the drones are becoming more commonly used for activities ranging from emergency responses to aerial deliveries, the base stations covering users both on the ground and in the air with RF transmission cannot scale to the capacity needed to support increasing number of drones. Use of directional beams that are necessary for millimeter wave (mmWave) transmission in the 5G cellular system can reduce interference among users, and hence increase capacity compared to sector based transmissions used for 4G systems without massive MIMO (mMIMO). In this paper, considering the multiplicative capacity gains needed to support large number of drones, we propose a separate mmWave cellular network with optimized coverage for a ''drone corridor'' in the air. We present our current findings in the following areas critical to validating the effectiveness of this proposed network: 1) RF propagation characteristics towards drones in the air compared with propagation towards users on the ground; 2) use of multiple access (MA) technology for increased spectral efficiency for a swarm of drones; 3) optimal design of protected zones and beamforming to secure drone specific wireless communications.

Internet of things (IoT) is one of main paradigms for 5G wireless systems. Due to high connection density, interference from other sources is a key problem in IoT networks. Especially, it is more difficult to find a solution to manage interference in uncoordinated networks than coordinated system. In this work, we consider 3D topology of uncoordinated IoT network and propose interference mitigation scheme with respect to 3D antenna radiation pattern. In 2D topology network, the radiation pattern of dipole antenna can be assumed as onmi-directional. We show the variance of antenna gain on dipole antenna in 3D topology, consider the simultaneous use of three orthogonal dipole antennas, and compare the system performance depending on different antenna configurations. Our simulation results show that proper altitude of IoT devices can extensively improve the system performance.

In millimeter-wave (mm-wave) cellular systems, beamforming antennas are necessary at both the base station (BS) and mobile station (MS) to compensate for high attenuation in mm-wave frequency bands and to extend the transmission range. In space-division multiple access (SDMA) systems, the challenge is the inter-beam interference (IBI) caused by adjacent beams that are formed by the BS in the same cell and BSs in neighboring cells. The beams that are formed toward MSs in each cell may generate significant interference to MSs in neighboring cells, especially for MSs at the cell boundary. In this paper, we propose four different digital precoding techniques (Type-1, Type-2, Type-3 and Type-4) to reduce IBI in mm-wave cellular systems with a hybrid beamformer.

The use of beamforming techniques at the ground station is known to be effective in obtaining coverage extension or SNR gain for communication with unmanned aerial vehicles (UAVs). When a UAV moves, periodic beam tracking is necessary to maintain beam gain. To track beams for multiple UAVs, the ground station needs to receive different preambles from multiple UAVs. In this paper, a Hadamard sequence is considered for designing preambles for multiple UAVs because of its ideal cross-correlation property. A preamble appropriate for a GMSK-based communication system with multiple UAVs is proposed after analyzing the property of received signals in the system with the Hadamard sequence as the input.