Specific primary user sensing for wireless security in IEEE 802.22 network

2011 ◽  
Author(s):  
Zhenxing Luo ◽  
Caiyi Lou ◽  
Shichuan Chen ◽  
Shilian Zheng ◽  
Shaowei Li
Keyword(s):  
Primary User ◽  
Wireless Security ◽  
Ieee 802.22

Demand of Wireless Network and Security in Current Research

2015 ◽  
Vol 14 (6) ◽  
pp. 5809-5813
Author(s):  
Abhishek Prabhakar ◽  
Amod Tiwari ◽  
Vinay Kumar Pathak
Keyword(s):  
Wireless Networks ◽  
Quality Of Service ◽  
Wireless Network ◽  
Network Performance ◽  
Wireless Security ◽  
Human Intervention ◽  
Unauthorized Access ◽  
Quality Of Service Parameters ◽  
Wireless Infrastructure

Wireless security is the prevention of unauthorized access to computers using wireless networks .The trends in wireless networks over the last few years is same as growth of internet. Wireless networks have reduced the human intervention for accessing data at various sites .It is achieved by replacing wired infrastructure with wireless infrastructure. Some of the key challenges in wireless networks are Signal weakening, movement, increase data rate, minimizing size and cost, security of user and QoS (Quality of service) parameters... The goal of this paper is to minimize challenges that are in way of our understanding of wireless network and wireless network performance.

Cognitive Radio: Primary User Emulation Attacks and Remedies

2012 ◽  
Vol 5 (2) ◽  
pp. 103-108 ◽  
Author(s):  
Sachin Shetty ◽  
Meena Thanu ◽  
Ravi Ramachandran
Keyword(s):  
Cognitive Radio ◽  
Primary User ◽  
Primary User Emulation

Auditors' and Investors' Perceptions of the “Expectation Gap”

2001 ◽  
Vol 15 (4) ◽  
pp. 345-358 ◽  
Author(s):  
John E. McEnroe ◽  
Stanley C. Martens
Keyword(s):  
Empirical Studies ◽  
Primary User ◽  
Financial Statement ◽  
User Group ◽  
Accounting Profession ◽  
The Public ◽  
Government Accounting ◽  
Expectation Gap ◽  
The Difference

The auditing “expectation gap” refers to the difference between (1) what the public and other financial statement users perceive auditors' responsibilities to be and (2) what auditors believe their responsibilities entail. The notion of this divergence receives much attention in the accounting literature (i.e., Commission on Auditors' Responsibilities 1978; Guy and Sullivan 1988; AICPA 1993; U.S. Government Accounting Office 1996). Although prior empirical studies encompass certain expectations associated with a range of audit services, these papers often involve the opinions of bankers as the primary user group employed in the research (Nair and Rittenberg 1987; Lowe and Pany 1995). In contrast, this study extends the prior research by directly comparing audit partners' and investors' perceptions of auditors' responsibilities involving various dimensions of the attest function. We conducted the study to determine if an expectation gap currently exists and we find that it does; investors have higher expectations for various facets and/or assurances of the audit than do auditors. Our findings serve as evidence that the accounting profession should engage in appropriate measures to reduce this expectation gap.

scholarly journals Second order Kalman filtering channel estimation and machine learning methods for spectrum sensing in cognitive radio networks

2021 ◽  
Author(s):  
Olusegun Peter Awe ◽  
Daniel Adebowale Babatunde ◽  
Sangarapillai Lambotharan ◽  
Basil AsSadhan
Keyword(s):  
Machine Learning ◽  
Kalman Filter ◽  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cognitive Radio Networks ◽  
Clustering Algorithm ◽  
Polynomial Regression ◽  
Primary User ◽  
Radio Networks ◽  
Second Order

AbstractWe address the problem of spectrum sensing in decentralized cognitive radio networks using a parametric machine learning method. In particular, to mitigate sensing performance degradation due to the mobility of the secondary users (SUs) in the presence of scatterers, we propose and investigate a classifier that uses a pilot based second order Kalman filter tracker for estimating the slowly varying channel gain between the primary user (PU) transmitter and the mobile SUs. Using the energy measurements at SU terminals as feature vectors, the algorithm is initialized by a K-means clustering algorithm with two centroids corresponding to the active and inactive status of PU transmitter. Under mobility, the centroid corresponding to the active PU status is adapted according to the estimates of the channels given by the Kalman filter and an adaptive K-means clustering technique is used to make classification decisions on the PU activity. Furthermore, to address the possibility that the SU receiver might experience location dependent co-channel interference, we have proposed a quadratic polynomial regression algorithm for estimating the noise plus interference power in the presence of mobility which can be used for adapting the centroid corresponding to inactive PU status. Simulation results demonstrate the efficacy of the proposed algorithm.

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