Spectrum sharing: A coordination framework enabled by fuzzy logic

2015 ◽  
Author(s):  
Konstantinos Chatzikokolakis ◽  
Panagiotis Spapis ◽  
Alexandros Kaloxylos ◽  
George Beinas ◽  
Nancy Alonistioti
Keyword(s):  
Fuzzy Logic ◽  
Spectrum Sharing ◽  
Coordination Framework

scholarly journals Preventing Cognitive User Emulation Attack in Cognitive Radio Network by Calculating Trust Values Using Fuzzy Logic

2021 ◽  
pp. 239-250
Author(s):  
Spriha Pandey* ◽  
Ashawani Kumar
Keyword(s):  
Fuzzy Logic ◽  
Cognitive Radio ◽  
Spectrum Sharing ◽  
Primary User ◽  
Trust Mechanism ◽  
Counter Measures ◽  
Security Issues ◽  
Security Attack ◽  
Management Functions ◽  
Cognitive User

Cognitive radio has proved to be an efficient and promising technology for the future of wireless networks. Its major and fundamental aim is to utilize the spectrum bands which are not efficiently exercised. These bands can be accessed using Opportunistic Spectrum Access (OSA), by a secondary user only when primary user is not transmitting over the channel. Cognitive radio manages spectrum through its cognitive radio cycle, which performs a set of management functions such as, spectrum sensing, spectrum assignment, spectrum sharing and spectrum mobility/handoff. During this cycle, at several stages, cognitive radio is very much vulnerable to security attacks. This is also due to the exposed nature of cognitive radio architecture. One such security attack which has not been much explored and can cause serious security issues is Cognitive User Emulation Attack (CUEA). This attack is expected to occur at the time of spectrum handoff. In this article the reason of occurrence of CUEA is explained along with counter measures to prevent this threat in the network by implementing trust mechanism using fuzzy logic. The proposed system is simulated and analyzed using MATLAB tool.

Fuzzy Systems for Spectrum Access, Mobility and Management for Cognitive Radios

2012 ◽  
pp. 205-218
Author(s):  
Prabhjot Kaur ◽  
Moin Uddin ◽  
Arun Khosla
Keyword(s):  
Fuzzy Logic ◽  
Soft Computing ◽  
Fuzzy Systems ◽  
Spectrum Sharing ◽  
Cognitive Radios ◽  
Spectrum Access ◽  
Air Interface ◽  
Soft Computing Techniques ◽  
The One ◽  
Hierarchical Fuzzy Systems

This chapter addresses the issues in air interface designs for Cognitive Radios. Fuzzy logic system is used as one of the soft computing techniques to learn to sub optimality and vagueness. Many good, simple, and quick fuzzy based solutions have been developed since few decades in many diverse domains. Through this chapter, the authors first discuss the significance and need of soft computing techniques in designing such solutions and then present fuzzy based solutions for spectrum access, mobility, and management. Hierarchical fuzzy systems have been used to get over to the problem of curse of dimensionality. The proposed solutions consider an architecture, similar to the one proposed by IEEE 802.22 working group, for spectrum sharing and management. Models have been designed using fuzzy logic toolbox in MATLAB, and the system performance is checked using SIMULINK.

Application of Fuzzy Logic Power Control for Cognitive Radio Networks

2012 ◽  
pp. 102-114
Author(s):  
Abbas Mohammed ◽  
Elisabeth Rakus-Andersson ◽  
Wlodek Kulesza
Keyword(s):  
Fuzzy Logic ◽  
Cognitive Radio ◽  
Power Control ◽  
Control Strategy ◽  
Spectrum Sharing ◽  
Channel Gain ◽  
Primary Users ◽  
Optimal Power ◽  
Optimal Power Control ◽  
Input Variables

In this chapter, the authors present the application of fuzzy logic for power control in spectrum sharing cognitive radio network. The investigated network consists of a pair of primary users (PUs) and a pair of cognitive radio users (CRs). In order to compute an optimal power scale for the CR link, a fuzzy-based optimal power control strategy is investigated based on the Mamdani fuzzy control model using two input variables: the PU’s signal-to-noise ratio (SNR) and PU’s interference channel gain (channel gain from the cognitive radio users to primary users). Applying the fuzzy-based optimal power control strategy, the desired quality of service (QoS) is assured on the PU link, and the efficiency of spectrum usage is also maximized on the CR link in the spectrum sharing network. In addition, the bit error rate (BER) is also improved as compared with the spectrum sharing network without power control.

Fuzzy Systems for Spectrum Access, Mobility and Management for Cognitive Radios

2015 ◽  
pp. 1854-1867
Author(s):  
Prabhjot Kaur ◽  
Moin Uddin ◽  
Arun Khosla
Keyword(s):  
Fuzzy Logic ◽  
Soft Computing ◽  
Fuzzy Systems ◽  
Spectrum Sharing ◽  
Cognitive Radios ◽  
Spectrum Access ◽  
Air Interface ◽  
Soft Computing Techniques ◽  
The One ◽  
Hierarchical Fuzzy Systems

This chapter addresses the issues in air interface designs for Cognitive Radios. Fuzzy logic system is used as one of the soft computing techniques to learn to sub optimality and vagueness. Many good, simple, and quick fuzzy based solutions have been developed since few decades in many diverse domains. Through this chapter, the authors first discuss the significance and need of soft computing techniques in designing such solutions and then present fuzzy based solutions for spectrum access, mobility, and management. Hierarchical fuzzy systems have been used to get over to the problem of curse of dimensionality. The proposed solutions consider an architecture, similar to the one proposed by IEEE 802.22 working group, for spectrum sharing and management. Models have been designed using fuzzy logic toolbox in MATLAB, and the system performance is checked using SIMULINK.

Hysteresis in Categorization: Fuzzy Logic Makes Fuzzy Boundaries

2012 ◽  
Author(s):  
Thomas M. Crawford ◽  
Justin Fine ◽  
Donald Homa
Keyword(s):  
Fuzzy Logic

Continuous Estimation of CO2 Production during Exercise

1997 ◽  
Vol 36 (04/05) ◽  
pp. 368-371
Author(s):  
R. Soma ◽  
Y. Yamamoto
Keyword(s):  
Fuzzy Logic ◽  
Steady State ◽  
Infusion Rate ◽  
Feedback System ◽  
Whole Body ◽  
Co2 Production ◽  
Cycle Exercise ◽  
Continuous Estimation ◽  
Breath Measurement ◽  
13Co2 Enrichment

Abstract.A new method was developed for continuous isotopic estimation of human whole body CO2 rate of appearance (Ra) during non-steady state exercise. The technique consisted of a breath-by-breath measurement of 13CO2 enrichment (E) and a real-time fuzzy logic feedback system which controlled NaH13CO3 infusion rate to achieve an isotopic steady state. Ra was estimated from the isotope infusion rate and body 13CO2 enrichment which was equal to E at the isotopic steady state. During a non-steady state incremental cycle exercise (5 w/min or 10 w/min), NaH13CO3 infusion rate was successfully increased by the action of feedback controller so as to keep E constant.

Modified fuzzy-based greedy routing protocol for VANETs

2020 ◽  
Vol 39 (6) ◽  
pp. 8357-8364
Author(s):  
Thompson Stephan ◽  
Ananthnarayan Rajappa ◽  
K.S. Sendhil Kumar ◽  
Shivang Gupta ◽  
Achyut Shankar ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Routing Protocol ◽  
Intelligent Transportation Systems ◽  
Vehicular Ad Hoc Networks ◽  
Ad Hoc ◽  
Research Area ◽  
Transportation Systems ◽  
Delivery Ratio ◽  
Greedy Routing ◽  
Hoc Networks

Vehicular Ad Hoc Networks (VANETs) is the most growing research area in wireless communication and has been gaining significant attention over recent years due to its role in designing intelligent transportation systems. Wireless multi-hop forwarding in VANETs is challenging since the data has to be relayed as soon as possible through the intermediate vehicles from the source to destination. This paper proposes a modified fuzzy-based greedy routing protocol (MFGR) which is an enhanced version of fuzzy logic-based greedy routing protocol (FLGR). Our proposed protocol applies fuzzy logic for the selection of the next greedy forwarder to forward the data reliably towards the destination. Five parameters, namely distance, direction, speed, position, and trust have been used to evaluate the node’s stability using fuzzy logic. The simulation results demonstrate that the proposed MFGR scheme can achieve the best performance in terms of the highest packet delivery ratio (PDR) and minimizes the average number of hops among all protocols.

Design and Simulation of Smart Control System for Internet Traffic Distribution on Servers by Using Fuzzy Logic System

2018 ◽  
Vol 2 (1) ◽  
Author(s):  
Raid Daoud ◽  
Yaareb Al-Khashab
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Input Parameter ◽  
Traffic Density ◽  
The Internet ◽  
Linguistic Variables ◽  
Internet Service ◽  
Traffic Distribution ◽  
Smart Control ◽  
High Level

The internet service is provided by a given number of servers located in the main node of internet service provider (ISP). In some cases; the overload problem was occurred because a demand on a given website goes to very high level. In this paper, a fuzzy logic control (FLC) has proposed to distribute the load into the internet servers by a smart and flexible manner. Three effected parameters are tacked into account as input for FLC: link capacity which has three linguistic variables with Gaussian membership function (MF): (small, medium and big), traffic density with linguistic variables (low, normal and high) and channel latency with linguistic variables (empty, half and full); with one output which is the share server status (single, simple and share). The proposed work has been simulated by using MATLAB 2016a, by building a structure in the Fuzzy toolbox. The results were fixed by two manners: the graphical curves and the numerical tables, the surface response was smoothly changed and translates the well-fixed control system. The numerical results of the control system satisfy the idea of the smart rout for the incoming traffics from the users to internet servers. So, the response of the proposed system for the share of server ratio is 0.122, when the input parameter in the smallest levels; and the ratio is 0.879 when the input parameters are in highest level. The smart work and flexible use for the FLC is the main success solution for most of today systems control.

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