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Wireless networks in agricultural environments are unique in many ways. Recent measurements reveal that the dynamics of crop growth impact wireless propagation channels with a long-term seasonal pattern. Additionally, short-term environmental factors, such as strong wind, result in variations in channel statistics. Next-generation agricultural fields, populated by autonomous tractors, drones, and high-throughput sensing systems, require high-throughput connectivity infrastructure, resulting in the future deployment of high-frequency networks, where they have not been deployed before. More specifically, when millimeter-wave (mmWave) communication systems, a viable candidate for 5G and 6G high-throughput solutions, are deployed for higher throughput, these issues become more prominent due to the relatively small wavelength at this frequency band. To improve coverage in the mmWave spectrum in agricultural settings, reconfigurable intelligent surfaces (RISs) are a promising solution with low energy consumption and high cost efficiency when compared to half-duplex active relays with multiple antennas. To ensure link resiliency under dynamic channel behavior, an adaptive RIS for broadband wireless agricultural networks (AgRIS) at mmWave band is designed in this work. AgRIS relies on output from a time-series model that forecasts the short-term wind speed based on measured wind data, which is readily available in most farms. The temporal correlation between link reliability and wind speed is demonstrated through extensive field experiments. Our simulation results demonstrate that AgRIS with a small footprint of 11 × 11 elements can help mitigate the adversarial effects of wind-induced signal level drop by up to 8 dB and provides high energy efficiency of 1 Gbits/joule. 

Current regulations leave a few television (TV) white spaces in populated urban areas where spectrum shortage is mostly experienced. As TV set feedback becomes essential in the next generation terrestrial TV standard, an opportunistic TV spectrum sharing based on TV receiver activity information and transmit power control is proposed to exploit the underutilized active TV channels. Based on investigation of the spatial–spectral–temporal characteristics of TV receiver activities, analytical models are developed to capture the spatio-temporal distributions of available spectrum and corresponding capacity. The influence of multiple factors, such as feedback delay, spectrum handover overhead, ranking order, and distribution of TV channel popularity are discussed and modeled. The proposed power control mechanism is verified through experiments at representative campus and residential environments. Empirical data-based simulations and geographic analyses are conducted to evaluate the developed models and further profile the spectrum opportunities within a cell, across New York city (NYC) and other 273 cities in the United States. In NYC, the proposed solution provides a 3.8 – 11.7 -fold increase of average spectrum availability, and 2.5 – 6.6 -fold increase of capacity from current regulations. By investigating the feasibility and prospects of this approach, this paper intends to motivate further discussions in policy, business, and privacy aspects to reach its significant potential.