It is a promising vision to exploit white spaces , that is, vacant VHF and UHF TV channels, to meet the rapidly growing demand for wireless data services in both outdoor and indoor scenarios. While most prior works have focused on outdoor white space, the indoor story is largely open for investigation. Motivated by this observation and discovering that 70% of the spectrum demand comes from indoor environment, we carry out a comprehensive study to explore indoor white spaces. We first conduct a large-scale measurement study and compare outdoor and indoor TV spectrum occupancy at 30+ diverse locations in a typical metropolis—Hong Kong. Our results show that abundant white spaces are available in different areas in Hong Kong, which account for more than 50% and 70% of the entire TV spectrum in outdoor and indoor scenarios, respectively. Although there are substantially more white spaces indoors than outdoors, there have been very few solutions for identifying indoor white space. To fill in this gap, we develop the first data-driven, low-cost indoor white space identification system for White-space Indoor Spectrum EnhanceR (WISER), to allow secondary users to identify white spaces for communication without sensing the spectrum themselves. We design the architecture and algorithms to address the inherent challenges. We build a WISER prototype and carry out real-world experiments to evaluate its performance. Our results show that WISER can identify 30%--40% more indoor white spaces with negligible false alarms, as compared to alternative baseline approaches.

It is a promising vision to utilize white spaces, i.e., vacant VHF and UHF TV channels, to satisfy skyrocketing wireless data demand in both outdoor and indoor scenarios. While most prior works have focused on exploring outdoor white spaces, the indoor story is largely open for investigation. Motivated by this observation and that 70% of the spectrum demand comes from indoor environments, we carry out a comprehensive study of exploring indoor white spaces. We first present a large-scale measurement of outdoor and indoor TV spectrum occupancy in 30+ diverse locations in a typical metropolis Hong Kong. Our measurement results confirm abundant white spaces available for exploration in a wide range of areas in metropolises. In particular, more than 50% and 70% of the TV spectrum are white spaces in outdoor and indoor scenarios, respectively. While there are substantially more white spaces in indoor scenarios than in outdoor scenarios, there is no effective solution for identifying indoor white spaces. To fill in this gap, we propose the first system WISER (for White-space Indoor Spectrum EnhanceR), to identify and track indoor white spaces in a building, without requiring user devices to sense the spectrum. We discuss the design space of such system and justify our design choices using intensive real-world measurements. We design the architecture and algorithms to address the inherent challenges. We build a WISER prototype and carry out real-world experiments to evaluate its performance. Our results show that WISER can identify 30%-50% more indoor white spaces with negligible false alarms, as compared to alternative baseline approaches.