scholarly journals Spectrum Sensing Based on Nonparametric Autocorrelation in Wireless Communication Systems under Alpha Stable Noise

2016 ◽  
Vol 2016 ◽  
pp. 1-6 ◽  
Author(s):  
Riqing Chen ◽  
Jun Wang ◽  
Ruiquan Lin ◽  
Xiangning Zhao
Keyword(s):  
Information Systems ◽  
Cognitive Radio ◽  
Wireless Communication ◽  
Spectrum Sensing ◽  
Communication Systems ◽  
Impulsive Noise ◽  
Wireless Communication Systems ◽  
Core Technology ◽  
Key Steps ◽  
Stable Noise

Cognitive radio is regarded as a core technology to support wireless information systems. Spectrum sensing is one of the key steps to achieve cognitive radio technology. To address this problem in the presence of Alpha stable noise in wireless communication systems, we propose a nonparametric autocorrelation method, which takes advantages of the characteristics of signal autocorrelation and noise nonstationarity. The autocorrelated signal is distinguished from Alpha stable noise. As a result, the proposed method is immune from noise uncertainty. Simulation results show the validity of the proposed method under Alpha stable noise, for example, impulsive noise in wireless information systems.

Geometric water-filling and radio resource management

2021 ◽  
Author(s):  
Zhiming He
Keyword(s):  
Cognitive Radio ◽  
Resource Management ◽  
Wireless Communication ◽  
Communication Systems ◽  
Optimization Problems ◽  
Radio Resource Management ◽  
Throughput Maximization ◽  
Wireless Communication Systems ◽  
Radio Resource ◽  
Water Filling

This thesis considers the radio resource management (RRM) of advanced wireless communication systems. With the emerging of more advanced and more complicated systems, such as cognitive radio, nodes with energy harvesting capacities (green communications), and the application of Multiple-Input Multiple-Output (MIMO) technology, RRM problems introduce more difficulties and challenges to optimize system performances. Due to specific structure of communication systems, water-filling (WF) plays an important role in RRM. This thesis introduces the fundamental theory and development of WF algorithm. The proposed Geometric Water-Filling (GWF) is presented and compared with the conventional WF algorithms. It can break through the limitations of the conventional WF to solve the more complicated optimization problems in the advanced wireless communication systems. For the application of the proposed GWF to solve the RRM problems in the advanced MIMO communication systems, cognitive radio communication systems, green communication systems and the “dual problems”, which are the sum power minimization problems, of the throughput maximization problems is investigated in this thesis. Efficient algorithms are presented to achieve the optimal resource allocation.

Geometric water-filling and radio resource management

2021 ◽  
Author(s):  
Zhiming He
Keyword(s):  
Cognitive Radio ◽  
Resource Management ◽  
Wireless Communication ◽  
Communication Systems ◽  
Optimization Problems ◽  
Radio Resource Management ◽  
Throughput Maximization ◽  
Wireless Communication Systems ◽  
Radio Resource ◽  
Water Filling

This thesis considers the radio resource management (RRM) of advanced wireless communication systems. With the emerging of more advanced and more complicated systems, such as cognitive radio, nodes with energy harvesting capacities (green communications), and the application of Multiple-Input Multiple-Output (MIMO) technology, RRM problems introduce more difficulties and challenges to optimize system performances. Due to specific structure of communication systems, water-filling (WF) plays an important role in RRM. This thesis introduces the fundamental theory and development of WF algorithm. The proposed Geometric Water-Filling (GWF) is presented and compared with the conventional WF algorithms. It can break through the limitations of the conventional WF to solve the more complicated optimization problems in the advanced wireless communication systems. For the application of the proposed GWF to solve the RRM problems in the advanced MIMO communication systems, cognitive radio communication systems, green communication systems and the “dual problems”, which are the sum power minimization problems, of the throughput maximization problems is investigated in this thesis. Efficient algorithms are presented to achieve the optimal resource allocation.

Compressed Edge Spectrum Sensing: Extensions and practical considerations

2019 ◽  
Vol 67 (1) ◽  
pp. 51-59
Author(s):  
Edgar Beck ◽  
Carsten Bockelmann ◽  
Armin Dekorsy
Keyword(s):  
Wireless Communication ◽  
Spectrum Sensing ◽  
Industry 4.0 ◽  
Communication Systems ◽  
Sampling Rate ◽  
Wireless Communication Systems ◽  
Active Systems ◽  
Radio Systems ◽  
Edge Spectrum

Abstract Nowadays, spectrum in industrial radio systems is already overoccupied. Therefore, future Industry 4.0 applications require coexistence management of different wireless communication systems. For identification of active systems, we propose Compressed Edge Spectrum Sensing (CESS). Here, we focus on practical aspects and show that the sampling rate can still be highly reduced.

scholarly journals Evolution of Wireless Communication Systems Towards Autonomously Managed, Cognitive Radio Functionalities

2006 ◽  
Author(s):  
Markus Muck ◽  
Sophie Gault ◽  
Didier Bourse ◽  
Konstantinos Tsagkaris ◽  
Panagiotis Demestichas ◽  
...  
Keyword(s):  
Cognitive Radio ◽  
Wireless Communication ◽  
Communication Systems ◽  
Wireless Communication Systems

Big Spectrum Data and Deep Learning Techniques for Cognitive Wireless Networks

2018 ◽  
pp. 33-60
Author(s):  
Punam Dutta Choudhury ◽  
Ankumoni Bora ◽  
Kandarpa Kumar Sarma
Keyword(s):  
Big Data ◽  
Deep Learning ◽  
Wireless Communication ◽  
Spectrum Sensing ◽  
Communication Systems ◽  
Common Factor ◽  
Wireless Communication Systems ◽  
Data Generation ◽  
Daily Lives ◽  
Communication Frameworks

The present world is data driven. From social sciences to frontiers of research in science and engineering, one common factor is the continuous data generation. It has started to affect our daily lives. Big data concepts are found to have significant impact in modern wireless communication systems. The analytical tools of big data have been identified as full scale autonomous mode of operation which necessitates a strong role to be played by learning based systems. The chapter has focused on the synergy of big data and deep learning for generating better efficiency in evolving communication frameworks. The chapter has also included discussion on machine learning and cognitive technologies w.r.t. big data and mobile communication. Cyber Physical Systems being indispensable elements of M2M communication, Wireless Sensor Networks and its role in CPS, cognitive radio networking and spectrum sensing have also been discussed. It is expected that spectrum sensing, big data and deep learning will play vital roles in enhancing the capabilities of wireless communication systems.

Big Spectrum Data and Deep Learning Techniques for Cognitive Wireless Networks

2020 ◽  
pp. 994-1015
Author(s):  
Punam Dutta Choudhury ◽  
Ankumoni Bora ◽  
Kandarpa Kumar Sarma
Keyword(s):  
Big Data ◽  
Deep Learning ◽  
Wireless Communication ◽  
Spectrum Sensing ◽  
Communication Systems ◽  
Common Factor ◽  
Wireless Communication Systems ◽  
Data Generation ◽  
Daily Lives ◽  
Communication Frameworks

The present world is data driven. From social sciences to frontiers of research in science and engineering, one common factor is the continuous data generation. It has started to affect our daily lives. Big data concepts are found to have significant impact in modern wireless communication systems. The analytical tools of big data have been identified as full scale autonomous mode of operation which necessitates a strong role to be played by learning based systems. The chapter has focused on the synergy of big data and deep learning for generating better efficiency in evolving communication frameworks. The chapter has also included discussion on machine learning and cognitive technologies w.r.t. big data and mobile communication. Cyber Physical Systems being indispensable elements of M2M communication, Wireless Sensor Networks and its role in CPS, cognitive radio networking and spectrum sensing have also been discussed. It is expected that spectrum sensing, big data and deep learning will play vital roles in enhancing the capabilities of wireless communication systems.

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