Software Defined Cognitive Radio Prototype toward IMT-Advanced Wireless Communication Systems

2007 ◽  
Author(s):  
Hiroshi Harada
Keyword(s):  
Cognitive Radio ◽  
Wireless Communication ◽  
Communication Systems ◽  
Wireless Communication 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.

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.

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

scholarly journals 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.

scholarly journals 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.

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