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 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.

The cache replacement policy is a crucial phase in caching-based systems that deal with the process of selecting applicable cache contents. In this paper, we propose two novel cache replacement algorithms based on the dataset obtained from a typical wireless femto network. In the first algorithm, called Weighted Least Frequently used with an Adaptive Time Window (WLF-ATW), we aim to make a balance between the network's traffic and the recognition of popular contents. The WLF-ATW algorithm takes the frequency and the recency information of files into account to ascertain the popularity of contents. We suggest another new cache replacement policy namely Fairness Scheduling-based with an Adaptive Time Window (FS-ATW) that is based on fairness scheduling in order to minimize the user's access delay. The novelty of our proposed FS-ATW lies in ranking clients according to their last situations that lead to a further user's experience. The effectiveness of these new algorithms is evaluated from the cache hit ratio, transferred byte volume, user's access delay, user's experience, and load balance. A comprehensive numerical evaluation shows that the performance of the proposed WLF-ATW and FS-ATW algorithms is significantly better than some existing cache replacement strategies.