Spectrum Access and Sharing for Cognitive Radio

2012 ◽  
pp. 241-271 ◽  
Author(s):  
Raza Umar ◽  
Asrar U. H. Sheikh
Keyword(s):  
Wireless Networks ◽  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Next Generation ◽  
Spectrum Access ◽  
Enabling Technology ◽  
Secondary Users ◽  
Next Generation Wireless Networks ◽  
Transmission Parameters ◽  
Characteristic Features

Cognitive radio (CR) has emerged as a smart solution to spectrum bottleneck faced by current wireless services, under which licensed spectrum is made available to intelligent and reconfigurable secondary users. CR technology enables these unlicensed secondary users to exploit any spectrum usage opportunity by adapting their transmission parameters on the run. In this chapter, the authors discuss the characteristic features and main functionality of CR oriented technology. Central to this chapter is Spectrum sensing (SS), which has been identified as a fundamental enabling technology for next generation wireless networks based on CR. The authors compare different SS techniques in terms of their sensing accuracy and implementation and computational complexities along with merits and demerits of these approaches. Various challenges facing SS have been investigated, and possible solutions are proposed.

scholarly journals 5G cognitive radio system design with new algorithm asynchronous spectrum sensing

2021 ◽  
Vol 10 (4) ◽  
pp. 2046-2054
Author(s):  
Mohammed Mehdi Saleh ◽  
Ahmed A. Abbas ◽  
Ahmed Hammoodi
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Energy Detection ◽  
Primary User ◽  
Spectrum Access ◽  
Secondary Users ◽  
Radio System ◽  
Wireless Applications ◽  
Fifth Generation ◽  
Time Required

Due to the rapid increase in wireless applications and the number of users, spectrum scarcity, energy consumption and latency issues will emerge, notably in the fifth generation (5G) system. Cognitive radio (CR) has emerged as the primary technology to address these challenges, allowing opportunist spectrum access as well as the ability to analyze, observe, and learn how to respond to environmental 5G conditions. The CR has the ability to sense the spectrum and detect empty bands in order to use underutilized frequency bands without causing unwanted interference with legacy networks. In this paper, we presented a spectrum sensing algorithm based on energy detection that allows secondary user SU to transmit asynchronously with primary user PU without causing harmful interference. This algorithm reduced the sensing time required to scan the whole frequency band by dividing it into n sub-bands that are all scanned at the same time. Also, this algorithm allows cognitive radio networks (CRN) nodes to select their operating band without requiring cooperation with licensed users. According to the BER, secondary users have better performance compared with primary users.

NeXt generation/dynamic spectrum access/cognitive radio wireless networks: A survey

2006 ◽  
Vol 50 (13) ◽  
pp. 2127-2159 ◽  
Author(s):  
Ian F. Akyildiz ◽  
Won-Yeol Lee ◽  
Mehmet C. Vuran ◽  
Shantidev Mohanty
Keyword(s):  
Wireless Networks ◽  
Cognitive Radio ◽  
Dynamic Spectrum Access ◽  
Dynamic Spectrum ◽  
Next Generation ◽  
Spectrum Access

Introduction to Cognitive Radio Networks

2013 ◽  
pp. 1-30 ◽  
Author(s):  
Natarajan Meghanathan
Keyword(s):  
Cognitive Radio ◽  
Dynamic Spectrum Access ◽  
Dynamic Spectrum ◽  
Spectrum Access ◽  
Medium Access ◽  
Secondary Users ◽  
Comprehensive Review ◽  
Primary Users ◽  
Transmission Parameters ◽  
Perceived Availability

A cognitive radio (CR) is a radio that can change its transmission parameters based on the perceived availability of the spectrum bands in its operating environment. CRs support dynamic spectrum access and can facilitate a secondary unlicensed user to efficiently utilize the available underutilized spectrum allocated to the primary licensed users. A cognitive radio network (CRN) is composed of both the secondary users with CR-enabled radios and the primary users whose radios need not be CR-enabled. In this chapter, the authors provide an exhaustive analysis of the issues and the state-of-the-art literature solutions available with regards to the following four layers of the TCP/IP protocol layer stack, in the context of CRNs: physical layer (spectrum sensing), medium access control, routing, and transport layers. We discuss the various techniques/mechanisms/protocols that have been proposed for each of these four layers, in the context of CRNs. In addition to the above, we discuss in detail several security attacks that could be launched on CRNs and the countermeasure solutions that have been proposed to avoid or mitigate them. This chapter serves as a good comprehensive review and analysis of all the critical aspects for CRNs, and would lay a strong foundation for someone to further delve onto any particular aspect in greater depth.

A Complete Spectrum Sensing and Sharing Model for Cognitive Radio Ad Hoc Wireless Networks Using Markov Chain State Machine

2013 ◽  
pp. 166-178
Author(s):  
Amir Rajaee ◽  
Mahdy Saedy ◽  
Brian Kelley
Keyword(s):  
Wireless Networks ◽  
Markov Chain ◽  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Ad Hoc ◽  
Secondary Users ◽  
Scale Free ◽  
Markov Chain Method ◽  
Scale Free Networks ◽  
Hoc Networks

This paper presents the Cognitive Radio framework for wireless Ad Hoc networks. The proposed Cognitive Radio framework is a complete model for Cognitive Radio that describes the sensing and sharing procedures in wireless networks by introducing Queued Markov Chain method in spectrum sensing and Competitive Indexing Algorithm in spectrum sharing part. Queued Markov Chain method is capable of considering waiting time and is well generalized for an unlimited number of secondary users. It includes the sharing aspect of Cognitive Radio. Power-law distribution of node degree in scale-free networks is important for considering the traffic distribution and resource management thus we consider the effect of the topology on sensing and sharing performances. The authors demonstrate that CIF outperforms Uniform Indexing (UI) algorithm in Scale-Free networks while in Random networks UI performs as well as CIF.

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