Radio Resource Management in Cognitive Radio Sensor Networks

2014 ◽  
pp. 27-47 ◽  
Author(s):  
Ayaz Ahmad ◽  
Sadiq Ahmad
Keyword(s):  
Cognitive Radio ◽  
Resource Management ◽  
Sensor Networks ◽  
Radio Resource Management ◽  
Sensor Nodes ◽  
Future Research ◽  
Radio Resource ◽  
Comprehensive Overview ◽  
Ism Band ◽  
Cognitive Radio Sensor Network

Wireless Sensor Networks (WSNs) use the unlicensed Industrial, Scientific, and Medical (ISM) band for transmissions. However, with the increasing usage of these networks for diverse applications, the currently available ISM band does not suffice for their transmissions and a new challenge appears before the WSNs' research community. One of the candidate approaches to tackle this spectrum insufficiency problem is to incorporate the opportunistic spectrum access capability of Cognitive Radio (CR) into the existing WSN, thus giving birth to Cognitive Radio Sensor Network (CRSN). Efficient spectrum utilization is another approach to overcome this challenging problem. Another challenge associated to WSN operation is the dependability of sensor nodes on battery supplied power where the batteries in general are not replaceable. Therefore, advanced and intelligent radio resource management schemes are very essential to perform dynamic and efficient spectrum allocation among multiple sensor nodes and to optimize the power consumption of each individual node in the network. Radio resource management enables the sensor nodes to efficiently utilize the available spectrum and power, which in turn ensures QoS transmissions, maximizes the network lifetime, and reduces the inter-node and inter-network interferences. In this chapter, the authors present a comprehensive overview of the recent advances in radio resource management for CRSN. Radio resource management in CRSN has been reviewed in various scenarios (i.e., centralized, cluster-based, and distributed). The related issues and challenges are discussed, and future research directions are highlighted.

Radio Resource Management in Cognitive Radio Sensor Networks

2016 ◽  
pp. 2353-2374
Author(s):  
Ayaz Ahmad ◽  
Sadiq Ahmad
Keyword(s):  
Cognitive Radio ◽  
Resource Management ◽  
Sensor Networks ◽  
Radio Resource Management ◽  
Sensor Nodes ◽  
Future Research ◽  
Radio Resource ◽  
Comprehensive Overview ◽  
Ism Band ◽  
Cognitive Radio Sensor Network

Wireless Sensor Networks (WSNs) use the unlicensed Industrial, Scientific, and Medical (ISM) band for transmissions. However, with the increasing usage of these networks for diverse applications, the currently available ISM band does not suffice for their transmissions and a new challenge appears before the WSNs' research community. One of the candidate approaches to tackle this spectrum insufficiency problem is to incorporate the opportunistic spectrum access capability of Cognitive Radio (CR) into the existing WSN, thus giving birth to Cognitive Radio Sensor Network (CRSN). Efficient spectrum utilization is another approach to overcome this challenging problem. Another challenge associated to WSN operation is the dependability of sensor nodes on battery supplied power where the batteries in general are not replaceable. Therefore, advanced and intelligent radio resource management schemes are very essential to perform dynamic and efficient spectrum allocation among multiple sensor nodes and to optimize the power consumption of each individual node in the network. Radio resource management enables the sensor nodes to efficiently utilize the available spectrum and power, which in turn ensures QoS transmissions, maximizes the network lifetime, and reduces the inter-node and inter-network interferences. In this chapter, the authors present a comprehensive overview of the recent advances in radio resource management for CRSN. Radio resource management in CRSN has been reviewed in various scenarios (i.e., centralized, cluster-based, and distributed). The related issues and challenges are discussed, and future research directions are highlighted.

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.

A Survey of Radio Resource Management in Cognitive Radio Networks

2013 ◽  
pp. 264-289
Author(s):  
Chengshi Zhao ◽  
Wenping Li ◽  
Jing Li ◽  
Zheng Zhou ◽  
Kyungsup Kwak
Keyword(s):  
Cognitive Radio ◽  
Resource Management ◽  
Dynamic Spectrum Access ◽  
Radio Resource Management ◽  
Radio Spectrum ◽  
Radio Resource ◽  
Green Communications ◽  
Radio Resources ◽  
Adaptive Power

The framework of “green communications” has been proposed as a promising approach to address the issue of improving resource-efficiency and the energy-efficiency during the utilization of the radio spectrum. Cognitive Radio (CR), which performs radio resource sensing and adaptation, is an emerging technology that is up to the requests of green communications. However, CR networks impose serious challenges due to the fluctuating nature of the available radio resources corresponding to the diverse quality-of-service requirements of various applications. This chapter provides an overview of radio resource management in CR networks from several aspects, namely dynamic spectrum access, adaptive power control, time slot, and code scheduling. More specifically, the discussion focuses on the deployment of CR networks that do not require modification to existing networks. A brief overview of the radio resources in CR networks is provided. Then, three challenges to radio resource management are discussed.

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