Grant: Collaborative Research and Development Grants
Ryerson University
$200,000.00
Wavelet Based Cognitive UWB Sensors for Smart Tunnels
FY 2017-18
Summary
The goal of the proposed research project is to enhance the safety of the subway tunnels as well as underground mining environment and to maintain an uninterrupted data transmission between train driver or miners and the controllers using Ultra Wide-Band (UWB) sensor network. Since UWB's wide range of frequency band causes mutual interference with other wireless services such as IEEE 802.11 a, cognitive capabilities will be developed to mitigate the interference within the UWB bandwidth and enhance the monitoring performance. Cognitive radio equipped with spectrum sensing can deal with spectrum scarcity and utilize the spectrum holes without causing harmful interference to the licensed users. Cognitive features enable the proposed UWB sensor network to detect the sources of interfering signals and avoid them in the wavelet based transmitter. Such feature enables the system to eliminate interference with various wireless services of clients in a tunnel environment; e.g. users of mobile devices, PCs and Wi-Fi can enjoy uninterrupted services while commuting in subway. Likewise, wireless communication in underground mines suffer from serious environmental noise and channel impairments. The large mining and electromechanical equipment, with high power and frequent starts, produce additive Gaussian white noise and pulse jamming leading to interference with UWB network. The proposed UWB network can sense the tunnel environment, decides and mitigates the impacts of interfering users on the data transmission. This project incorporates wavelet radio as an integrated part of the UWB sensor network. In terms of multicarrier modulation (MCM), wavelet based MCM can offer more spectrum efficiency and enhance the robustness against noise and inherent interference of conventional OFDM system. Wavelet based UWB channel modeling of tunnels can reduce the number of required coefficients of channel representation with high degree of time-frequency localization compared to the Fourier based method. Due to the complex nature of underground tunnels, cooperative spectrum sensing is proposed to alleviate the effects of shadowing and multipath fading on the UWB sensor network.
Program
Collaborative Research and Development Grants
Recipient
Location
Ontario, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data
As published
Application id
490434-2015
Name nom
Raahemifar, Kaamran
Department département
Electrical and Computer Engineering
Organization id
43
Institution établissement
Ryerson University
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2017
Competition year année de concours
2015
Award amount
200000
Program id
CRDPJ
Program name en
Collaborative Research and Development Grants
Program name fr
Subventions de recherche et développement coopérative
Group en
Research partnerships programs
Group fr
Programmes de partenariat
Committee code
96
Committee name en
RPP Internal Decision Cttee
Committee name fr
Cté de décision interne - PPR
Area of application code
804
Area of application group en
Information and communication services
Area of application group fr
Services d'information et de télécommunications
Area of application en
Communication systems and services (planning, organization, services)
Area of application fr
Systèmes et services de communications (planification, organisation et services)
Research subject code
2508
Research subject group en
Electrical and electronic engineering
Research subject group fr
Génie électrique et électronique
Research subject en
Communications networks
Research subject fr
Réseaux de télécommunications
Partie
2 & 3
Nb partie
3
Application title
Wavelet Based Cognitive UWB Sensors for Smart Tunnels
Keyword
NSERC
Application summary
The goal of the proposed research project is to enhance the safety of the subway tunnels as well as underground mining environment and to maintain an uninterrupted data transmission between train driver or miners and the controllers using Ultra Wide-Band (UWB) sensor network. Since UWB's wide range of frequency band causes mutual interference with other wireless services such as IEEE 802.11 a, cognitive capabilities will be developed to mitigate the interference within the UWB bandwidth and enhance the monitoring performance. Cognitive radio equipped with spectrum sensing can deal with spectrum scarcity and utilize the spectrum holes without causing harmful interference to the licensed users. Cognitive features enable the proposed UWB sensor network to detect the sources of interfering signals and avoid them in the wavelet based transmitter. Such feature enables the system to eliminate interference with various wireless services of clients in a tunnel environment; e.g. users of mobile devices, PCs and Wi-Fi can enjoy uninterrupted services while commuting in subway. Likewise, wireless communication in underground mines suffer from serious environmental noise and channel impairments. The large mining and electromechanical equipment, with high power and frequent starts, produce additive Gaussian white noise and pulse jamming leading to interference with UWB network. The proposed UWB network can sense the tunnel environment, decides and mitigates the impacts of interfering users on the data transmission. This project incorporates wavelet radio as an integrated part of the UWB sensor network. In terms of multicarrier modulation (MCM), wavelet based MCM can offer more spectrum efficiency and enhance the robustness against noise and inherent interference of conventional OFDM system. Wavelet based UWB channel modeling of tunnels can reduce the number of required coefficients of channel representation with high degree of time-frequency localization compared to the Fourier based method. Due to the complex nature of underground tunnels, cooperative spectrum sensing is proposed to alleviate the effects of shadowing and multipath fading on the UWB sensor network.