A discussion on channel sensing techniques By James Xu Supervised by Dr. Fakhrul Alam.

Slides:

Advertisements

Similar presentations

Cognitive Radio Communications and Networks: Principles and Practice By A. M. Wyglinski, M. Nekovee, Y. T. Hou (Elsevier, December 2009) 1 Chapter 13 Defining.

Advertisements

Multistage Spectrum Sensing for Cognitive Radios UCLA CORES.

Helsinki University of Technology Networking Laboratory Timo Ralli Unlicensed radio spectrum: CASE WLAN Timo Ralli

VSMC MIMO: A Spectral Efficient Scheme for Cooperative Relay in Cognitive Radio Networks 1.

Prashant Bajpayee Advisor: Dr. Daniel Noneaker SURE 2005 Motivation Currently most radio-frequency spectrum is assigned exclusively to “primary” users.

By: Gamal El Din Fathy Amin Ahmed Ossama El Fiky Supervised By: Dr Tarek El Naffouri.

Spectrum Awareness in Cognitive Radio Systems based on Spectrum Sensing Miguel López-Benítez Department of Electrical Engineering and Electronics University.

System Design for Cognitive Radio Communications

Speaker: You-Min Lin Advisor: Dr. Kai-Wei Ke Date: 2011/04/25 Cognitive Radio Networks (CRN) 1.

Spectrum Sensing Based on Cyclostationarity In the name of Allah Spectrum Sensing Based on Cyclostationarity Presented by: Eniseh Berenjkoub Summer 2009.

Optimization of pilot Locations in Adaptive M-PSK Modulation in a Rayleigh Fading Channel Khaled Almustafa Information System Prince Sultan University.

Detecting Primary Receivers for Cognitive Radio Applications Ben Wild, Kannan Ramchandran UC Berkeley Dept. of Electrical Engineering and Computer Science.

1 Spectrum Sensing Marjan Hadian. 2 Outline Cognitive Cycle Enrgy Detection Matched filter cyclostationary feature detector Interference Temperature Spectral.

Performance Analysis of Energy Detector in Relay Based Cognitive Radio Networks Saman Atapattu Chintha Tellambura Hai Jiang.

DOF: A Local Wireless Information Plane Stanford University Steven HongSachin Katti 1 August 17, 2011.

Multiantenna-Assisted Spectrum Sensing for Cognitive Radio

Jamming and Anti-Jamming in IEEE based WLANs Ravi Teja C 4/9/2009 TexPoint fonts used in EMF. Read the TexPoint manual before you delete this box.:

COGNITIVE RADIO FOR NEXT-GENERATION WIRELESS NETWORKS: AN APPROACH TO OPPORTUNISTIC CHANNEL SELECTION IN IEEE BASED WIRELESS MESH Dusit Niyato,

EE360: Lecture 12 Outline Underlay and Interweave CRs Announcements HW 1 posted (typos corrected), due Feb. 24 at 5pm Progress reports due Feb. 29 at midnight.

POWER CONTROL IN COGNITIVE RADIO SYSTEMS BASED ON SPECTRUM SENSING SIDE INFORMATION Karama Hamdi, Wei Zhang, and Khaled Ben Letaief The Hong Kong University.

RELIABLE MULTIMEDIA TRANSMISSION OVER COGNITIVE RADIO NETWORKS USING FOUNTAIN CODES Proceedings of the IEEE | Vol. 96, No. 1, January 2008 Harikeshwar.

Performance of Energy Detection: A Complementary AUC Approach

Bingxuan ZHAO Wireless Communication and Satellite Communication Project II Shimamoto Laboratory, GITS Waseda University Ph.D Academy.

Mingyuan Yan, Shouling Ji, and Zhipeng Cai Presented by: Mingyuan Yan.

Simulation Of A Cooperative Protocol For Common Control Channel Implementation Prepared by: Aishah Thaher Shymaa Khalaf Supervisor: Dr.Ahmed Al-Masri.

Cognitive Radio Networks

A Survey of Spectrum Sensing Algorithm for Cognitive Radio Applications YaGun Wu netlab.

Sangeetha Nandan (1ay05cs057)

White Space Internet Device By: Sean Iveson William Sadler.

Tarun Bansal, Bo Chen and Prasun Sinha

Advanced Spectrum Management in Multicell OFDMA Networks enabling Cognitive Radio Usage F. Bernardo, J. Pérez-Romero, O. Sallent, R. Agustí Radio Communications.

Dynamic Spectrum Access in the Time Domain: Modeling and Exploiting White Space Stefan Geirhofer and Lang Tong, Cornell University Brian M. Sadler, United.

Asaf Barel Eli Ovits Supervisor: Debby Cohen June 2013 High speed digital systems laboratory Technion - Israel institute of technology department of Electrical.

Doppler Spread Estimation in Frequency Selective Rayleigh Channels for OFDM Systems Athanasios Doukas, Grigorios Kalivas University of Patras Department.

Cognitive Radio: Next Generation Communication System

Static Spectrum Allocation

Maximum-Minimum Eigen Value Based Spectrum Scanner Mohamed Hamid and Niclas Björsell Center for RF measurement Technology, University of Gävle, Sweden.

Cognitive Radio

CHANNEL AWARE MEDIUM ACCESS CONTROL IN COGNITIVE RADIO NETWORKS

Cognitive Radios Motivation: scarce wireless spectrum

Farrukh Javed F /07-UET - PHD-CASE-CP-40 Spectrum Sensing and Allocation Techniques for Cognitive Radios.

Cooperative MIMO Paradigms for Cognitive Radio Networks

Spectrum Sensing In Cognitive Radio Networks

Presenter: Renato Iide, Le Wang Presentation Date: 12/16/2015.

Authors: Soamsiri Chantaraskul, Klaus Moessner Source: IET Commun., Vol.4, No.5, 2010, pp Presenter: Ya-Ping Hu Date: 2011/12/23 Implementation.

Chance Constrained Robust Energy Efficiency in Cognitive Radio Networks with Channel Uncertainty Yongjun Xu and Xiaohui Zhao College of Communication Engineering,

1 Architecture and Behavioral Model for Future Cognitive Heterogeneous Networks Advisor: Wei-Yeh Chen Student: Long-Chong Hung G. Chen, Y. Zhang, M. Song,

Cooperative Resource Management in Cognitive WiMAX with Femto Cells Jin Jin, Baochun Li Department of Electrical and Computer Engineering University of.

Overcoming the Sensing-Throughput Tradeoff in Cognitive Radio Networks ICC 2010.

Ashish Rauniyar, Soo Young Shin IT Convergence Engineering

TELFOR 2015, Belgrade, Serbia, November Spectrum Sensing for the Unlicensed Band Cognitive Radio Nenad Milošević, Zorica Nikolić, Filip Jelenković,

Doc.: IEEE a Submission November, 2003 CRL-UWB ConsortiumSlide 1 Project: IEEE P Working Group for Wireless Personal Area Networks.

A discussion on channel sensing techniques By James Xu.

Spectrum Utilization The goals of this project: (1) Development of algorithms for the distributed detection of incumbents/trespassers in any frequency.

Mohsen Riahi Manesh and Dr. Naima Kaabouch

Channel Sensing for Cognitive Radio

Comparison Between and af

SPECTRUM SHARING IN COGNITIVE RADIO NETWORK

Paper ID:88 Analysis of OFDM Parameters using Cyclostationary Spectrum Sensing in Cognitive Radio INMIC2011.

Cognitive Radio Based 5G Wireless Networks

Enhancing the capacity of Spectrum Sharing in Cognitive Radio Network

PERFORMANCE ANALYSIS OF SPECTRUM SENSING USING COGNITIVE RADIO

User Interference Effect on Routing of Cognitive Radio Ad-Hoc Networks

Classification of modulation

Cognitive Radio Networks

Presented by Mohamad Haidar, Ph.D. May 13, 2009 Moncton, NB, Canada

Multicarrier Communication and Cognitive Radio

An overview of the IEEE Standard

Spectrum Sharing in Cognitive Radio Networks

April 24, Study Group 1 A Regulatory Framework for Use of TV Channels by Part 15 Devices John Notor, Cadence Design Systems, Inc.

Presentation transcript:

A discussion on channel sensing techniques By James Xu Supervised by Dr. Fakhrul Alam

Presentation overview  Introduction to wireless communications  What is Cognitive Radio (CR)?  Why do we need CR?  What is channel sensing  Our workbench setup  Our research  Our major contributions  Conclusion

Wireless communications

What is Cognitive Radio (CR)  Able to sense spectral environment  Able to provide opportunistic access Find gaps in the spectrum Adjust system parameters to utilize it

Why do we need CR?  Unlicensed spectrum is rare  Almost none available under 3GHz

Why do we need CR?  Licensed to primary user only (Incumbent)  We are running out of space, and higher frequency has problems  We are under utilizing licensed space  CR is allowed usage (guarantee interference free)

What is channel sensing  The first step of CR is to identify free spectrum  Channel sensing is one of the most fundamental part of CR

What is channel sensing

Our research  Our research focus  Energy detection  Cyclostationary feature extraction

Our CR workbench

Energy detection  Easy to implement  Fast  Not effective under low SNR

What is energy detection?  All radio transmission have energy  Based on hypothesis testing

Energy detector

Problems with the detector  Misdetection on Narrowband signals

Problems with the detector  Misdetection on partial signals

Adaptive energy detection  We proposed an improvement  Introduced adaptive detection

 Improved detection

Adaptive ED characteristics

Cyclostationary Features  Another channel sensing strategy  Digital communication systems have built in periodicity  A signal is a first order cyclostationary if it’s mean is periodic  A signal is second order cyclostationary it it’s auto-correlation is periodic

Cyclostationary Features  Auto-correlation how much a signal has in common with itself, against delay  Alpha = Cyclic frequency  S = Spectrum Correlation Function (SCF)

Cyclostationary Features

Work in Progress  This is preliminary, a proof of concept  Could be done in future research

Our major contributions  Xu J. Y., Alam, F., Adaptive Energy Detection for Cognitive Radio: An Experimental Study, ICCIT, 2009  IET PATW Competition, Regional winner  cr.jamesyxu.com  Svn://cr.jamesyxu.com/svn  CRLibs

CRLibs  A library for cognitive radio research

Conclusion  Workbench setup  Investigated various channel sensing techniques (ED, SCF, Spectral Entropy)  Proposed and implemented improvements (AED)  Consolidated library (CRLibs), examples and codebase (SVN)  Full progress documentation (SVN, CR)

Acknowledgement  Dr Fakhrul Alam  Dr James Chang  Dr Tom Moir  Everyone in our lab

Thank you for listening  You are invited to visit our CR workbench at Building 80  Much more details in the project report  Adaptive energy detection model will be on IEEEXplore end of December  Any questions?