Performance analysis of Doppler shift effects on OFDM-based and MC-CDMA-based cognitive radios

2013 ◽  
pp. n/a-n/a ◽  
Author(s):  
Salem Bindhaiq ◽  
Sharifah Kamilah Syed-Yusof ◽  
Haleh Hosseini
Keyword(s):  
Performance Analysis ◽  
Doppler Shift ◽  
Cognitive Radios

Performance analysis of digital delay lock loops in the presence of Doppler shift

1996 ◽  
Vol 44 (6) ◽  
pp. 668-674 ◽  
Author(s):  
Nan-Yang Yen ◽  
Szu-Lin Su ◽  
Sheng-Cheng Hsieh
Keyword(s):  
Performance Analysis ◽  
Doppler Shift

scholarly journals Performance Analysis of Different Types of Sensor Networks for Cognitive Radios

2012 ◽  
Vol 2012 ◽  
pp. 1-15 ◽  
Author(s):  
Chunxuan Ye ◽  
Zinan Lin ◽  
Alpaslan Demir ◽  
Yan Li
Keyword(s):  
Sensor Networks ◽  
Performance Analysis ◽  
Data Fusion ◽  
Sensor Network ◽  
Spectrum Sensing ◽  
Cognitive Radios ◽  
Fusion Center ◽  
Multiple Sensors ◽  
Different Types ◽  
Information Combining

We consider the problem of using multiple sensors to detect whether a certain spectrum is occupied or not. Each sensor sends its spectrum sensing result to a data fusion center, which combines all the results for an overall decision. With the existence of wireless fading on the channels from sensors to data fusion center, we examine three different mechanisms on the transmissions from sensors to data fusion center: (1) direct transmissions; (2) transmissions with the assistance of relays and (3) transmissions with the assistance of an intermediate fusion helper which fuses the sensing results from the sensors and sends the fused result to the data fusion center. For each mechanism, we analyze the correct probability of the overall decision made by the data fusion center. Our evaluation establishes that a sensor network with an intermediate fusion helper performs almost as good as a sensor network with relays, but providing energy and spectral advantages. Both networks significantly outperform the sensor network without relay or intermediate fusion helper. Such analysis facilitates the design of sensor networks. Furthermore, we generalize this evaluation to sensor networks with an arbitrary number of sensors and to sensor networks applying various information combining rules. Our simulations validate the analytical results.

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