scholarly journals Spectrum Sensing for Cognitive Networks Based on Dimensionality Reduction and Random Forest

Author(s):  
Xin Wang ◽  
Jin-Kuan Wang ◽  
Zhi-Gang Liu ◽  
Bin Wang ◽  
Xi Hu
2017 ◽  
Vol 2017 ◽  
pp. 1-14 ◽  
Author(s):  
Teddy Febrianto ◽  
Jiancao Hou ◽  
Mohammad Shikh-Bahaei

In asynchronous cognitive networks (CNs), where there is no synchronization between primary users (PUs) and secondary users (SUs), spectrum sensing becomes a challenging task. By combining cooperative spectrum sensing and full-duplex (FD) communications in asynchronous CNs, this paper demonstrates improvements in terms of the average throughput of both PUs and SUs for particular transmission schemes. The average throughputs are derived for SUs and PUs under different FD schemes, levels of residual self-interference, and number of cooperative SUs. In particular, we consider two types of FD schemes, namely, FD transmit-sense-reception (FDr) and FD transmit-sense (FDs). FDr allows SUs to transmit and receive data simultaneously, whereas, in FDs, the SUs continuously sense the channel during the transmission time. This paper shows the respective trade-offs and obtains the optimal scheme based on cooperative FD spectrum sensing. In addition, SUs’ average throughput is analyzed under different primary channel utilization and multichannel sensing schemes. Finally, new FD MAC protocol design is proposed and analyzed for FD cooperative spectrum sensing. We found optimum parameters for our proposed MAC protocol to achieve higher average throughput in certain applications.


Author(s):  
Yunxue Liu ◽  
Dongfeng Yuan ◽  
Mingyan Jiang ◽  
Hui Yu ◽  
Chunyuan Xu ◽  
...  

Author(s):  
Vishal C V

Abstract: Statistics has always been an integral part of the sporting world. Selectors pick players based on numerous factors such as averages, strike-rates, runs scored or goals scored. Teams have exclusive ‘talent hunters’, who spend weeks, if not months, trying to uncover talent from different parts of the world. With the rise of this new niche field called Sports Analytics, teams can now perform player evaluations on tons of data that is available. This paper aims to examine the factors that truly indicate the capacity of cricket players to perform at the top-most level – international cricket. Though this research has been carried out on cricket data, it is hoped that similar methods can be used to hunt for true talent in other sports! Keywords: Cricket Analytics, Random Forest, Principal Component Analysis, Dimensionality Reduction.


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