Advanced WiFi studies: interference avoidance, indoor localization and cloud based management
Advanced WiFi studies: interference avoidance, indoor localization and cloud based management
批准号:
476708-2014
负责人:
Lambadaris, Ioannis
金额:
$2.91万
依托单位:
依托单位国家:
加拿大
项目类别:
Collaborative Research and Development Grants
财政年份:
2015
资助国家:
加拿大
项目状态:
已结题
起止时间:
2015-01-01 至 2016-12-31
中文摘要
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英文摘要
Our reliance on wireless communications/services using the WiFi (IEEE 802.11) standard has been constantly growing during the past decade.
The proposed research will perform studies in the following areas that play a key role on the reliability and performance of WiFi networks (with particular emphasis on systems using the new IEEE 802.11ac standard)
a) Spectral analysis for interference avoidance. The effort will focus on enabling spectral analysis using suitable hardware (chip-sets) that are integrated in current commercially available access points (AP's). The goal is the identification of interfering sources and development of techniques for avoiding interference. Possible techniques may involve per frame spectrum shaping or adaptive channel hoping.
b) Distributed WiFi packet (frame) sniffing. The research will examine packet sniffing (that can be implemented in the APs) and data forwarding to a public domain analyzer. This approach will enable packet sniffing in IEEE 802.11ac environments with MU-MIMO capability. Packet capture and analysis is an important tool for diagnosing anomalies or malfunctions in WiFi networks.
c) Indoor positioning/localization. Highly accurate indoor localization of wireless devices (such as smart phones, tablets etc.) is critical in a WiFi network to enable novel location based services. Current accuracy of positioning techniques are in the range of 5-8m and in some cases the accuracy can be compromised even further. The research in this area will study real-time localization techniques with improved accuracy by employing advanced features of IEEE 802.11ac.
d) Migration of WiFi management to the cloud. The research effort will examine the application of the Software Defined Network (SDN) paradigm for the migration of WiFi management to the cloud. The goal is to integrate (as services/applications) the functionality of spectral analysis for interference avoidance, packet capture/ analysis/ logging and localization that were introduced in a)-c).
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