This research effort focuses on the impact that 4G/LTE wireless devices (e.g. cell towers and smart phones) may have on radar altimeters operating in the 4200-4400 MHz spectral band. Based on the identification of this band by the government as a potential candidate for commercial cellular use, the spectral characteristics and potential impact to the operation of these airplane landing radars has become extremely important to a broad audience. The recent crash of the Asiana Airlines flight has added to the focus on the operation of these radars. To obtain this understanding, a significant spectrum measurement campaign will be undertaken focused on appropriate radar altimeter systems and on 4G/LTE systems. The measurements will quantify the effects of 4G/LTE on radar altimeter performance using actual and/or simulated equipment. These measurement results will provide a basis for performing the detailed analysis work required to gauge the level of impact that would be expected under a variety of conditions. This information will need to be quickly and effectively disseminated to others in the wireless research community and importantly to various decision-makers in the telecommunications policy realm.
The need for increased RF spectrum access for wireless broadband applications continues within the commercial and government user domains. Since the usable RF spectrum is fully allocated, the only options available are to: a) increase the efficiency of current spectrum uses; b) re-purpose spectrum to higher value uses; or c) institute spectrum sharing. While the FCC has a database of authorized, licensed spectrum users, the ultimate success of any of these options depends on knowledge of actual RF spectrum utilization in time, frequency, and space. While snap-shot surveys of RF utilization have been performed, and long-term observations of RF use have been made at single locations, the impact of incorporating the spatial dimension to both improve the accuracy of these estimates and model medium-scale geographic variations has not been fully explored. Given the need to obtain mappings and models of the temporal and spatial variations of the RF environment with sufficiently high fidelity to estimate, characterize, and model spectrum utilization, the resulting research objectives are: 1) create a sufficiently low-cost and scalable approach to generating and accessing the necessary high quality RF dataset; 2) provide new methods for analyzing, modeling, and visualizing the resulting large, multi-dimensional information base; and 3) model spectrum activity to test the feasibility of spectrum sharing in candidate bands in order to facilitate decision making and innovation in spectrum repurposing and sharing.
Due to the rapidly expanding adoption of broadband wireless services, a fundamental RF spectrum shortage is developing. In order to apply emerging technologies (e.g. dynamic spectrum sharing) to address this problem, there is a critical need to understand global RF spectrum usage trends. To accomplish this, a three-pronged approach is being pursued: 1) deployment of geographically dispersed, temporally coordinated RF spectrum observatories in multiple U.S. locations, and through international collaboration, in Finland. The spectrum observatories use a common platform generating a single RF spectrum measurement dataset. 2) Development of empirically validated, statistical models of spectrum utilization for different wireless application types based on this dataset. 3) Use of "big data" analytical techniques to mine the dataset to discover temporal and spectral correlations not obvious using traditional approaches. As the models and relationships are refined, they will enable temporal and spectral occupancy predictions to support spectrum sharing for various circumstances and wireless applications. The generation of a high-resolution, multi-location, multi-national spectrum usage dataset using a common, consistent measurement and storage approach is unique and allows direct, unambiguous comparisons of spectrum usage across geographies and demographics. The statistical models of spectrum utilization and the identified similarities and differences between regions and wireless services is unique and informs dynamic spectrum sharing research and related regulatory action with "real-world" data. Importantly, this is the first time that "big data" analytic approaches are being systematically applied to RF utilization data providing new insights motivating novel dynamic spectrum sharing approaches and improved spectrum efficiency.
