It is a promising vision to exploit\u00a0white spaces<\/i>, 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\u00a0indoor<\/i>\u00a0white 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\u2014Hong 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.<\/p>\n","protected":false},"excerpt":{"rendered":"
It is a promising vision to exploit\u00a0white 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 […]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[13547],"msr-publication-type":[193716],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-post-option":[],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-474756","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-systems-and-networking","msr-locale-en_us"],"msr_publishername":"ACM","msr_edition":"ACM Transactions on Intelligent Systems and Technology (TIST)","msr_affiliation":"","msr_published_date":"2017-10-01","msr_host":"","msr_duration":"","msr_version":"","msr_speaker":"","msr_other_contributors":"","msr_booktitle":"","msr_pages_string":"","msr_chapter":"","msr_isbn":"","msr_journal":"ACM Transactions on Intelligent Systems and Technology (TIST)","msr_volume":"","msr_number":"","msr_editors":"","msr_series":"","msr_issue":"","msr_organization":"","msr_how_published":"","msr_notes":"","msr_highlight_text":"","msr_release_tracker_id":"","msr_original_fields_of_study":"","msr_download_urls":"","msr_external_url":"","msr_secondary_video_url":"","msr_longbiography":"","msr_microsoftintellectualproperty":1,"msr_main_download":"","msr_publicationurl":"https:\/\/dl.acm.org\/citation.cfm?doid=3059149","msr_doi":"","msr_publication_uploader":[{"type":"url","title":"https:\/\/dl.acm.org\/citation.cfm?doid=3059149","viewUrl":false,"id":false,"label_id":0}],"msr_related_uploader":"","msr_attachments":[{"id":0,"url":"https:\/\/dl.acm.org\/citation.cfm?doid=3059149"}],"msr-author-ordering":[{"type":"text","value":"Xuhang Ying","user_id":0,"rest_url":false},{"type":"text","value":"Jinchen Zhang","user_id":0,"rest_url":false},{"type":"text","value":"Yu Chen","user_id":0,"rest_url":false},{"type":"text","value":"Guanglin Zhang","user_id":0,"rest_url":false},{"type":"text","value":"Minghua Chen","user_id":0,"rest_url":false},{"type":"user_nicename","value":"Ranveer Chandra","user_id":33344,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Ranveer Chandra"}],"msr_impact_theme":[],"msr_research_lab":[],"msr_event":[],"msr_group":[],"msr_project":[171068,170158],"publication":[],"video":[],"download":[],"msr_publication_type":"inproceedings","related_content":{"projects":[{"ID":171068,"post_title":"Dynamic Spectrum and TV White Spaces","post_name":"dynamic-spectrum-and-tv-white-spaces","post_type":"msr-project","post_date":"2012-11-30 10:07:58","post_modified":"2022-10-11 15:37:52","post_status":"publish","permalink":"https:\/\/www.microsoft.com\/en-us\/research\/project\/dynamic-spectrum-and-tv-white-spaces\/","post_excerpt":"The Spectrum Opportunity Microsoft is working with key partners around the world to ensure consumers have access to an increasing range of connected devices. To meet growing consumer demand and address other policy challenges, we must consider multiple approaches which can be used that enable opportunistic, dynamic use of spectrum. Real World Stories While innovative uses of the radio spectrum \u2013 the building blocks of wireless connectivity \u2013 drive economic development, new business growth, policy…","_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/171068"}]}},{"ID":170158,"post_title":"Networking Over White Spaces (KNOWS)","post_name":"networking-over-white-spaces-knows","post_type":"msr-project","post_date":"2008-12-19 20:10:09","post_modified":"2021-04-12 22:35:02","post_status":"publish","permalink":"https:\/\/www.microsoft.com\/en-us\/research\/project\/networking-over-white-spaces-knows\/","post_excerpt":"The next generation of wireless networks will include software defined radios, cognitive radios, and multi-radio systems which will co-exist harmoniously while operating over a very wide range of frequencies. Under the umbrella of the KNOWS project we are revisiting \"classical\" wireless networking problems and designing new solutions that incorporate and build upon recent advances in software and hardware technologies for networking over the recently opened white spaces spectrum. 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