Thesis Submitted in partial fulfilment of the requirements of BITS C421T/422T Thesis BY BIRLA INSTITUTE OF TECHNOLOGY AND SCIENCE, PILANI Under the Supervision of Asst. Professor, School of Computer Science & Statistics AT Trinity College Dublin, College Green, Dublin 2 December 2012
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Thesis
Submitted in partial fulfilment of the requirements of
BITS C421T/422T Thesis
BY
BIRLA INSTITUTE OF TECHNOLOGY AND SCIENCE, PILANI
Under the Supervision of
Asst. Professor, School of Computer Science & Statistics
AT
Trinity College Dublin, College Green, Dublin 2
December 2012
Submitted in partial fulfilment of the requirements of
BITS C421T/422T Thesis
BIRLA INSTITUTE OF TECHNOLOGY AND SCIENCE, PILANI
Under the Supervision of
Asst. Professor, School of Computer Science & Statistics
AT
Trinity College Dublin, College Green, Dublin 2
(August - December 2012)
Trinity College Dublin, College Green, Dublin 2
CERTIFICATE This is to certify that the Thesis entitled “Calculating Electromagnetic Field Coverage over Terrain using an Integral Equation Method in order to enable Coexistence in Cognitive Radio” is a bonafide work of KARTIC BHARGAV K.R, ID No. 2009A3TS170P in partial fulfilment of the requirement of BITS C421T/422T Thesis embodies the work done by him under my guidance & supervision at the School of Computer Science & Statistics, Trinity College Dublin from 02/08/2012 to 08/12/2012.
Date: Signature of the Supervisor Name
Designation
ACKNOWLEDGEMENTS
I am deeply indebted to my Thesis supervisor and mentor Dr. Eamonn O’Nuallain. Without his expert
guidance and support, no part of this beautiful venture would have been possible. The lessons
imparted and knowledge gained were priceless and meant more than just an academic programme.
Needless to say I am confident that these sparks have kindled a powerful flame of commitment and
dedication.
I sincerely thank Prof. Jeremy Jones, Head of SCSS for well coordinating the Thesis Programme and
for aiding the project to develop by equipping it with the necessary fuel and mileage for it to
proceed in the right direction.
I also thank Dr. Hitesh Tiwari of the School of Computer Science & Statistics for having agreed to set
aside his valuable time to tutor me.
I express my gratitude to the Administration, Treasurers’ Office and the Management of SCSS for
promptly helping me through various formalities and paperwork.
I would also like to extend my heartfelt thanks to all the people associated, directly or indirectly with
this project for their valuable suggestions and constant motivation throughout the project.
Never the least, come my alma mater(s) BITS Pilani and Trinity College Dublin which gave me such a
wonderful opportunity and a memorable life experience.
Kartic Bhargav K.R
Thesis Abstract
Thesis Title: Calculating Electromagnetic Field Coverage over Terrain using an Integral
Equation Method in order to enable Coexistence in Cognitive Radio.
Supervisor: Dr. Eamonn O’Nuallain
Semester: First
Name of Student: Kartic Bhargav K.R ID No: 2009A3TS170P
Abstract
Basic Objective: To calculate the Electromagnetic Field coverage over terrain using a
Propagation Modelling based Electric Field Integral Equation (EFIE) Method and its variants
in order to enable coexistence in Cognitive Radio.
Previous methods of computing electromagnetic field coverage use Path-loss methods and
Ray–Tracing. Both of these however are either too simple or are computationally too
intensive. Initially, a glance through the history and background of Cognitive Radio
Technology is done. Following this, an appreciation of radio wave propagation and Radio
Environment Mapping is given as it applies to Cognitive Radio. Also a study into the
different existing methods of localization and position awareness in Cognitive Radio is done.
Next, the Electric Field Integral Equation Method is implemented for rural and urban profiles
taking into account forward scattering. Then, a reference Solution is generated for the EFIE
using Gauss-Jordan Elimination & LU Decomposition. Finally, both forward and backward
scattering were taken into account in order to investigate the Electromagnetic Field
Coverage on the German profile using the standard values of frequency of propagation and
transmitter height.
Table of Contents
Thesis Abstract 4
Introduction 6
1. History & Background of Cognitive Radio Technology 7
2. Cognitive Techniques - Position Awareness 9
2.1 Global Position Awareness (GPS) 9
2.2 Time of Arrival (ToA) 10
2.3 Time Difference of Arrival (TDoA) 10
2.4 Angle Of Arrival (AoA) 10
2.5 Very high frequency Omnidirectional Ranging (VOR) 11
2.6 Received Signal Strength (RSS) 11
3. Network Support - REM 12
4. The EFIE Method (Forward Scattering) 16
4.1 Synopsis of the EFIE 16
4.2 Program Implementation 18
4.3 Testing and Observations 18
4.4 Danish Profile Testing 23
5. The Reference Solution Generation 24
6. The Forward Backward Solution 26
6.1 Background Study of the EFIE Solution with Backward Sweep 26
6.2 Programming Methodology 27
7. Conclusion 28
8. Future Scope for Extension 29
9. Bibliography/ References 30
INTRODUCTION
Cognitive Radio (CR) is a radio technology that refers to the ability of a radio
device to sense/learn the communication parameters of its environment and to adapt its
transmissions accordingly. The ability of a radio device to do this with sufficient
sophistication will enable such devices to transmit in underutilized licensed bands without
affecting the communications of the licensee. The Shared Spectrum Company, who famously
measured over 80% underutilization of the spectrum (30-2900MHz) in New York during the
Republican Convention in 2004 and dispelled the myth that the spectrum is ‘crowded’, has
measured similar underutilization in other locations since then.
The value of CR technology is enormous since it opens up large portions of the
valuable communications spectrum for use by such devices – much of it with good
propagation characteristics. CR technology will enable the continuing worldwide exponential
growth and innovation in wireless communications. It is a technology currently in its nascent
stage with the FCC very recently making available a 16MHz portion of the analogue TV
spectrum at 700Mz for, among other purposes, CR. Though there is currently a fast growing
body of literature on the topic it is currently somewhat speculative and consensus on how
technical challenges relating to the deployment of CR ought to be addressed has not been
reached though the current draft IEEE 802.11 WRAN standard and the recent FCC auction
has served to bring these issues into focus.
There are however specific technical challenges that must be overcome for CR to be
feasible. Chief among these is the ability of the cognitive radio to adapt its transmissions
with sufficient agility so as not to adversely affect the communications if the incumbent
licensees or Primary Users (PUs). There are a number of proposals which aim to detect PU
transmission even at very low power and on that basis avoid CR transmission in that band
(matched filter detection, cyclostationary feature detection etc.). Apart from adding
complexity to the cognitive device however, none have explicitly solved the ‘Hidden Node’
problem. This is the presence of a PU receiver in the region covered by the CR transmission.
The CR not has detected the PU signal because of its low power. The result is unwanted
interference at the PU receiver.
The ‘Hidden Node’ problem must be overcome to guarantee non-interference with
PU signals. Furthermore, the chosen link must be stable for effective CR communications.
This requires a means with which to predict link stability based on spectrum usage patterns
such that the scenario of the CR initiating transmission only to be shortly afterward forced to
terminate due to the sudden presence of a PU signal is avoided. It is proposed to address the
‘Hidden Node’ problem through Radio Environment Mapping (REM).
1. History & Background of Cognitive Radio Technology
A Smart Radio should have the ability to think for itself. More like predicting what
the user needs and providing for it without him explicitly asking for it. With conservation of
spectrum becoming a national priority, there arises a need for devices that can efficiently
optimize Spectrum Management. In addition to this, the device should also be able to
perform beneficial tasks that aid the user and should be able to interface with a wide variety
of networks thereby interacting with them in their preferred protocols. Thus a Cognitive
Radio, an SDR in its advanced stage – is basically a combination of many pagers, PDAs, cell
phones and various other present-day gadgets.
Now, the progression of the Basic SDR onto the Cognitive Radio can be visualized to consist
of the development of various threads such as improvement in radio communication
performance by the semiconductor industry, advancement in DSP techniques that replaced
the conventional analog functions (implemented with large discrete components) with
digital functions (implemented in Silicon) and of course, the machine learning and related
methods for improved machine behaviour.
A basic SDR includes an RF-front end, a modem, a cryptographic security function and the
application end. In order to allow the radio to provide network services and to be connected
with the local Ethernet, usually support for the network devices is provided on the plain text
side or the modem side of the radio. The modem on the other hand, is responsible for
processing the received signal or synthesizing the transmitted signal on a full-duplex radio.
The computational processing resources in an SDR usually consist of the GPPs, DSPs and
FPGAs. While speech & video applications run on a DSP processor, text and web browsing
are supported typically by the GPP processor. FPGAs on the other hand are now capable of
providing tremendous amounts of multiply accumulating operations on a single chip. By
defining the on-chip interconnect of many gates, more than 100 multiply accumulators are
arranged to process frequencies of more than 200MHz. All these computational resources
demand significant amount of off-chip memory.
Common Measurements such as the SNR, frequency offset, timing offset, or equaliser taps
can be read by Java reflection. By examining these radio properties, the receiver can
determine what changes at the transmitter will improve the important objectives of
communication (like battery life, interference etc). From the Java reflection, the receiver
formulates a message onto the reverse link and multiplexes it on the channel and observes if
the transmitter gives an improved performance after making the changes.
Smart Antennas and efficient spectrum management are other essential qualities of a
cognitive radio. A smart antenna basically tells a smart radio what its key capabilities are. A
smart transmit antenna can form a beam to focus the transmitted energy in the direction of
the intended receiver while a smart receive antenna can synthesize a main lobe in the
appropriate direction of the transmitter as well as synthesize a deep null in the direction of