Extension of the Code Division Multiple Access/Adaptive Interference Cancellation protocol through analysis and simulation
Date
2021-05
Authors
Sanasi, Paul Nicanor
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Abstract
<p>RFID tags find their application in many areas such as inventory tracking, shipment tracking, vehicle tracking and identification, and animal tracking and identification. Passive RFID tags have been used in most of the applications as they are extremely cost-efficient, and they have a longer lifespan. Previous researchers have developed a CDMA based Adaptive Interference cancellation protocol to increase energy efficiency and reduce multipath effects. In Adaptive Interference Cancellation, we would read the strongest tag and remove its effect and then read the next strongest, remove its
effects and so on. In analyzing the protocol, researchers have used a Rayleigh distribution to establish the relative amplitudes for each of the tags to simulate the effects
of multipath and shadowing for each tag. The Rayleigh distribution, which models received signal strength with no line-of-sight component, is the worst case for many
applications but is not the worst case for assessing the performance of the protocol.</p>
<p>This research aims to extend the Adaptive Interference Cancellation algorithm to a broader group of applications. We evaluate the CDMA based Adaptive Interference Cancellation Protocol with different types of distributions such as Rician fading and Lognormal distributions. Rician fading technique has less fluctuations and a series of
Rice factors due to reflections and Line of Sight which may reduce the performance of the AIC method. We also aim to use standard lognormal distributions to represent extremely strong Line of Sight.</p>
Description
Keywords
Code division multiple access, Adaptive interference cancellation, RFID tags
Citation
Sanasi, P. N. (2021). <i>Extension of the code division multiple access/adaptive interference cancellation protocol through analysis and simulation</i> (Unpublished thesis). Texas State University, San Marcos, Texas.