stochastic modeling of microwave oven interference in wlans
DESCRIPTION
Marcel Nassar and Brian Evans The University of Texas at Austin, Austin, Texas USA Email: [email protected] , [email protected] Xintian Eddie Lin Intel Corporation, Santa Clara, California USA Email: [email protected]. Microwaves and WLANs. Spectral and Temporal Properties. - PowerPoint PPT PresentationTRANSCRIPT
Stochastic Modeling of Microwave Oven Interference in WLANsMarcel Nassar and Brian Evans
The University of Texas at Austin, Austin, Texas USAEmail: [email protected], [email protected]
Xintian Eddie LinIntel Corporation, Santa Clara, California USA
Email: [email protected]
Microwaves and WLANs
• Microwave Ovens operating in the 2.4GHz unlicensed ISM band interfere with IEEE802.11b/g/n WLANS
• Microwave Interference leads disruptions of transmission or dramatic increase in bit error rates
• Leads to huge degradation in performance for delay sensitive applications such as streaming
Microwave Oven Interference Modeling
Spectral and Temporal Properties
• The proposed model captures the frequency dependence of the noise trace. Thus enabling channel-level simulations.
• The instantaneous statistics of the proposed model and real interference data shows that our model’s prediction provides the best fit.
• Max-hold power spectral density of microwave oven interference indicates that it spans all WLAN bands
Microwave oven interference model will have applications in:• System Simulations• Insight into PHY Layer receiver design• Tuning of MAC Layer parameters for
optimized performance for delay sensitive applications
• The on-time of the oven has also some time where the interference is low
• This is due to frequency drift phenomena
• The spectrogram shows the frequency drift phenomena
• Each WLAN channel observes different temporal noise properties
• The temporal traces exhibits variations as a function of frequency as well
Communication Performance
This research was supported by Intel Corporation
• Accurate modeling leads increase in available information rate
• The decrease in available capacity is significantly less than predicted by other models
• The accurate modeling leads to insights into receiver design and optimization of its parameters
• The available rate increases with distance between the receiver and the oven
• At lower distances, avoidance achieves the best available rate due to the high interference caused by the oven ON-time
• At higher distances, transmitting during the ON-time of the oven provides increase in rate because the pathloss attenuates the oven interference