In partial fulfillment
For the award of the Degree of
Bachelor of Technology
In Department of Electronics and Communication Engineering
2013 - 2014
Student Name – JATIN KUMAR
Student Roll no. – 10/ EL/ 038
SEM: - 6th
Mr. B.M. Baveja.
B.S. Anangpuria Institute of Technology
It is my privilege to express my deep sense of gratitude towards all those who
helped me to undertake training in ELECTRONICS NIKETAN, Ministry of
Communication and Information technology, GOVT. OF INDIA.
I would like to express my sincere thanks to Mr. B.M. Baveja. (Training
coordinator),Ministry of Communication and Information Technology for his
guidance, valuable suggestions & encouragement during the project.
Table of Contents :1. Company profile
2. Introduction to cognitive radio
And dynamic spectrum access
3. History and Background Leading
to Cognitive Radio
4. Basic concept of cognitive radio
5. Configuration of cognitive radio
6. Key technologies
7. Cognitive Networks and the
8. Features Of Cognitive Radio
9. Spectrum Hole Concept
10. Future Applications
The MINISTRY OF COMMUNICATION AND INFORMATION
TECHNOLOGY is an Indian government ministry.
3.1 VISION OF THE DEPARTMENT
e-Development of India as the engine for transition into a developed nation
and an empowered society.
3.2 MISSION OF THE DEPARTMENT
e-Development of India through multi pronged strategy of eInfrastructure creation to facilitate and
promotion of Electronics & Information Technology- Information
Technology Enabled Services (IT-ITeS) Industry, providing support for
creation of Innovation / Research & Development (R&D), building
Knowledge network and securing India's cyber space.
3.3 OBJECTIVE OF THE DEPARTMENT OF ELECTRONICS
AND INFORMATION TECHNOLOGY
e-Government: Providing e-infrastructure for delivery of e-services.
e-Industry: Promotion of electronics hardware manufacturing and ITITeS industry.
e-Innovation / R & D: Providing Support for creation of Innovation
Infrastructure in emerging areas of technology.
e-Education: Providing support for development of e-Skills and
e-Security: Securing India's cyber space.
3.4 CC&BT (COMMUNICATION CONVERGENCE AND
BROADBAND TECHNOLOGY DEPARTMENT)
Information Technology has made possible information access at
gigabit speeds. It has created a level playing field among nations and
has made positive impact on the lives of millions who are poor,
marginalised and living in rural and far flung topographies. Internet
has made revolutionary changes with possibilities of e-filing Income
Tax returns or applying for passports online or railway e-ticketing.
Today a country’s IT potential is paramount for its march towards
global competitiveness, healthy GDP, improving defence capabilities
and meeting up the energy and environmental challenges.
The Indian Information Technology- Information TechnologyEnabled Services (IT-ITES) industry has continued to perform its
role as the most consistent growth driver for the economy. Service,
software exports and BPO remain the mainstay of the sector. Over
the last five years, the IT & ITES industry has grown at a
remarkable pace. Consider some of the significant indicators for
these remarkable achievements. The IT/ITES exports have grown to
a staggering US$ 46.3 billion in 2008-09, the IT sector currently
employing 2.2 million professionals directly and another 8 million
people indirectly accounts for over 5% of GDP, a majority of the
Fortune 500 and Global 2000 corporations are sourcing IT/ITES
from India and it is the premier destination for the global sourcing
of IT/ITES accounting for 55% of the global market in offshore IT
services and garnering 35% of the ITES/BPO market.
3.5 FUNCTIONS OF DEPARTMENT OF ELECTRONICS
AND INFORMATION TECHNOLOGY
The Allocation of Business Rules Pertaining to Department of
Electronics and Information Technology.
Policy matters relating to information technology; Electronics;and Internet(all
matters other than licensing of Internet Service Provider).
Promotion of internet,IT and IT enabled services.
Assistance to other departments in the promotion of E–Governance,E–
Promotion of Information Technology education and Information Technology–
Matters relating to Cyber Laws,administration of the Information Technology
Act.2000 (21 of 2000) and other IT related laws.
Matters relating to promotion and manufacturing of Semiconductor Devices in
the country excluding all matters relating to Semiconductor Complex Limited
(SCL),Mohali ;The Semiconductor Integrated Circuits layout Design Act,2000
(37 of 2000).
Interaction in IT related matters with international agencies and bodies e.g.
Internet for Business Limited(IFB),Institute for Education in Information
Society (IBI) and International Code Council – on line (ICC).
Initiative on bridging the Digital Divide :Matters relating to Media Lab Asia.
Promotion of Standardization,Testing and Quality in IT and standardization of
procedure for IT application and Tasks.
Electronics Export and Computer Software Promotion Council (ESC).
National Informatics Centre (NIC).
Initiatives for development of Hardware/Software industry including
knowledge–based enterprise, measures for promoting IT exports and
competitiveness of the industry.
All matters relating to personnel under the control of the Department.
ORGANISATIONAL CHART OF DEPARTMENT OF
ELECTRONICS AND INFORMATION
A cognitive radio is a transceiver designed to use the best wireless
channels in its vicinity. Such a radio automatically detects available
its transmission or reception parameters
concurrent wireless communications in a given spectrum band at one
location. Depending on transmission and reception parameters.
There are two main types of cognitive radio :
1.Full Cognitive Radio (Mitola radio), in which every possible parameter
observable by a wireless node (or network) is considered
2.Spectrum-Sensing Cognitive Radio, in which only the radio-frequency
spectrum is considered.
Cognitive radio :
A term first coined by Mitola is a low cost, highly flexible alternative to the
classic single frequency band, single protocol wireless device. By sensing
and adapting to its environment, a cognitive radio is able to cleverly avoid
interference and fill voids in the wireless spectrum, dramatically
increasing spectral efficiency.
This dissertation defines and develops cognitive radio, the integration of
model-based reasoning with software radio technologies. It analyzes the
architecture and performance of a rapid-prototype cognitive radio, CR1 in
a simulated environment. This architecture is based on the set-theoretic
ontology of radio knowledge defined in the Radio Knowledge
Representation Language (RKRL). CR1 incorporates machine-learning
techniques to embrace the open domain framework of RKRL. These
machine learning techniques make the software-radio trainable in a broad
sense, instead of just programmable. Although somewhat primitive, CR1’s
level of computational intelligence provides useful insights into the
research issues surrounding cognitive radio. CR1 integrates aspects of
digital signal processing, speech processing, theory of computing, rulebased expert systems, natural language processing, and machine learning
into the software radio domain. The inter-disciplinary nature of cognitive
radio raises interesting questions for future research and development.
THE RADIO spectrum, which is needed for wireless communication
systems, is a naturally limited resource.
To support various wireless applications and services in a noninterfering
basis, the fixed spectrum access (FSA) policy has traditionally been
adopted by spectrum regulators, which assign each piece of spectrum with
certain bandwidth to one or more dedicated users. By doing so, only the
assigned (licensed) users have the right to exploit the allocated spectrum,
and other users are not allowed to use it, regardless of whether the
licensed users are using it. With the proliferation of wireless services in the
last couple of decades, in several countries, most of the available spectrum
has fully been allocated, which results in the spectrum scarcity problem.
On the other hand, recent studies on the actual spectrum utilization
measurements have revealed that a large portion of the licensed spectrum
experiences low utilization. These studies also indicate that it is the
inefficient and inflexible spectrum allocation policy that strongly
contributes to spectrum scarcity and, perhaps, even more than the
physical shortage of the spectrum. To maintain sustainable development
of the wireless communication industry, novel solutions should be
developed to enhance the utilization efficiency of the radio spectrum.
Dynamic spectrum access (DSA) :
has been proposed as an alternative policy to allow the radio spectrum to
more efficiently be used . In DSA, a piece of spectrum can be allocated to
one or more users, which are called primary users (PUs); however, the use
of that spectrum is not exclusively granted to these users, although they
have higher priority in using it. Other users, which are referred to as
secondary users (SUs), can also access the allocated spectrum as long as
the PUs are not temporally using it or can share the spectrum with the
PUs as long as the PUs’ can properly be protected. By doing so, the radio
spectrum can be reused in an opportunistic manner or shared all the time;
thus, the spectrum utilization efficiency can significantly be improved.
To support DSA, SUs are required to capture or sense the
radio environment, and a SU with such a capability is also
called a cognitive radio (CR) or a CR user. There are
different types of cognitive capabilities with which a CR may
be equipped. For example, a CR may sense the ON/OFF status of
the PUs or can predict the interference power level that
is received at the primary receiver (Rx). In an extreme case,
if a CR is a genie user, it may also acquire the messages that are
transmitted by the primary Tx .The process of acquiring the
radio environment knowledge can be complex and expensive,
because it may involve spectrum sensing, autonomous learning, user
cooperation, modeling, and reasoning.
The sophistication possible in a software-defined radio (SDR) has now
reached the level where each radio can conceivably perform beneficial
tasks that help the user, help the network, and help minimize spectral
congestion. Radios are already demonstrating one or more of these
capabilities in limited ways. A simple example is the adaptive digital
European cordless telephone (DECT) wireless phone, which finds and uses
a frequency within its allowed plan with the least noise and interference on
that channel and time slot. Of these capabilities, conservation of spectrum
is already a national priority in international regulatory planning. This
book leads the reader through the technologies and regulatory
considerations to support three major applications that raise an SDR’s
capabilities and make it a cognitive radio:
1. Spectrum management and optimizations.
2. Interface with a wide variety of networks and optimization of
3. Interface with a human and providing electromagnetic resources to
aid the human in his or her activities.
Many technologies have come together to result in the spectrum efficiency
and cognitive radio technologies that are described in this book. This
chapter gives the reader the background context of the remaining chapters
of this book. These technologies represent a wide swath of contributions
upon which cognitive technologies may be considered as an application on
top of a basic SDR platform.
To truly recognize how many technologies have come together to drive
cognitive radio techniques, we begin with a few of the major contributions
that have led up to today’s cognitive radio developments. The development
of digital signal processing (DSP) techniques arose due to the efforts of
such leaders as Alan Oppenheim , Lawrence Rabiner, Ronald Schaefer
Ben Gold, Thomas Parks , James McClellen James Flanagan , Fred
Harris , and James Kaiser. These pioneers2recognized the potential for
digital ﬁltering and DSP, and prepared the seminal textbooks, innovative
papers, and breakthrough signal processing techniques to teach an entire
industry how to convert analog signal processes to digital processes. They
guided the industry in implementing new processes that were entirely
impractical in analog signal processing. Somewhat independently, Cleve
Moler, Jack Little, John Markel, Augustine Gray, and others began to
develop software tools that would eventually converge with the DSP
industry to enable efficient representation of the DSP techniques, and
would provide rapid and efficient modelling of these complex algorithms .
Meanwhile, the semiconductor industry, continuing to follow Moore’s
law ,evolved to the point where the computational performance required
to implement digital signal processes used in radio modulation and
demodulation were not only practical, but resulted in improved radio
communication performance, reliability, ﬂexibility, and increased value to
the customer. This meant that analog functions implemented with large
discrete components were replaced with digital functions implemented in
silicon, and consequently were more producible, less expensive, more
reliable, smaller, and of lower power .
Defining the PDR, SDR, and Software Radio
Military radios for mobile ground, air and naval applications employ the
bands HF through UHF. Thus, 2 MHz to 2 GHz defines the nominal RF
coverage of the tactical military radio. Commercial mobile radios typically
do not require the HF band, but emphasize the mobile satellite, cellular
and PCS bands between 400 and 2400 MHz instead. In the limit, an ideal
mobile military software radio digitizes 2.5 GHz of RF, sampling at 6 gigasamples per second (gsps) with at least 60 dB of dynamic range, including
the contributions of automatic gain control (AGC). The state of the art is 6
gsps and 30 dB .In addition, the 6 gsps DACs and filters cannot yet reach
the spectral purity needed for the ideal software radio. With today’s
technology, then, one must compromise the ideal, implementing
programmable digital radios (PDRs), also called software-defined radios
(SDR). An SDR, for example, might use a fast tuning synthesizer to hop a
3 MHz instantaneous baseband bandwidth over a 200 MHz agility
bandwidth. Although the pattern of hops generated by the synthesizer
could be programmable, the instantaneous waveform bandwidth is limited
to 3 MHz. A software radio, on the other hand, would digitize the 200
MHz bandwidth at 400 msps or more. The instantaneous bandwidth of the
waveform, then, could be programmed to any bandwidth up to 200 MHz,
not limited by the 3 MHz baseband. The PDR would have a
programmable choice of hopping frequencies across 200 MHz, while the
software radio would have an arbitrarily programmable waveform across
the 200 MHz1.
The degree of flexibility of a radio platform is of considerable relevance to
cognitive radio. A commercially viable SDR may be implemented as a mix
of Application-Specific Integrated Circuits (ASICs), Field Programmable
Gate Arrays (FPGAs), Digital Signal Processors (DSPs), and generalpurpose microprocessors. ASIC parameters also may be defined in
software. But, an ideal software radio has no ASICs. Instead, it
implements all the radio’s RF conversion, filtering, modem and related
functions in software.
Implementation points A through D in the figure are contemporary SDRs.
The Virtual Radio, however, is an ideal single-channel narrowband
software radio based on a general-purpose processor, specifically a DEC
Alpha, running UNIX. Point X is the ideal software radio with digital
access at RF and all functions programmed in general purpose processors.
Although providing maximum flexibility and thus of research interest,
such designs are economically impractical in the short term. Cognitive
radio’s focus, however, is on the fourth generation of wireless in which
commercial radios will begin to approximate the software radio.
Fig 1. Dimensions of Software Radio Implementations
In the commercial sector, for example, a dual antenna-RF stage could
cover the radio spectrum from 350 MHz to 2400 MHz. With a 100 MHz x
16 bit ADC and a few GFLOPS of processing capacity, this would be a
powerful software radio precursor.
Modelling the Software Radio
The architecture-level model of identifies the functional components and
interfaces of the software radio In order to reason about its own internal
structure, a radio requires some such model. Cognitive radio’s internal
model of itself is based on this specific model.
There are, however, many other comprehensive, precise models of the
internal architecture of a radio. The architecture model of the SDR
Forum, for example, augments the modem function with a data processing
function on the channel coding and decoding side of the INFOSEC
module. In addition, their model has no IF Processing module. One can
create a mapping among the two models that establishes their equivalence.
The appendix develops a topological model within which such mappings
may be analyzed. That analysis includes the question of constraints on
computational resources in software radio.
Software radio includes the downloading of software objects that modify
or extend the host radio’s capabilities. The SDR Forum, for example, has
defined a secure download protocol that assures the object is suited to the
host radio, appropriately authorized, and free of error . The thinking is
that a new well-behaved object that interacts with existing well-behaved
objects in the
radio will yield a well-behaved system. Appendix B addresses the question
“under what conditions can well-behaved radio software be composed
with other well-behaved radio software to yield a well-behaved system?”
This general question of software composition is known to be undesirable.
That is, there is no algorithm that can examine two arbitrary pieces of
software in finite time and yield “Yes” if they will yield an answer and
“No” if they will consume infinite resources (and thus yield no answer).
Fortunately, software radios are engineering systems with timing
constraints that allow one to prescribe constraints on the topological
structure of the software that establishes conditions under which
composition of software modules is well behaved . Since modems,
equalizers, vocoders, and other radio functions are part of an isochronous
stream, they must run-to-complete in a short time window that a radio
engineer can bound tightly in advance.
There are therefore a-priority bounds on time and space (i.e. memory) for
SDR modules that each new module must meet as well. Theoretically,
these bounds comprise a step-counting function, a function that counts
resources used by another program. There are programming constructs
that will meet these bounds sometimes, but not for all possible
circumstances. In particular, any construct that is equivalent to a while or
until loop can cause two well-behaved software modules (or objects) to
consume infinite resources in unpredictable ways. These functions will
consume up to a specified amount of memory and time independently and
up to another specified amount in concert. The theorems of the appendix
show that the bounded recursive functions are the largest set of functions
for which predictably finite resource consumption may be guaranteed. In
addition, the composition of bounded recursive functions is also bounded
recursive, and this sets measurable conditions under which plug-and-play
modules will not use excessive resources. Furthermore, there is no
practical limit on the useful radio functions that can be computed with the
bounded recursive functions.
Basic concept of cognitive radio
Background of cognitive radio :
We have been living in a society where people can access anything,
anywhere, anytime through networks regardless of time and location for
the past 10 years, and consequently, multimedia communications by
means of compact mobile terminals have gained popularity. Concurrently,
the communication rates and other requirements for wireless
communications have dramatically extended. These requirements will
increasingly expand, and to meet them, a wide variety of high-speed
wireless systems have been developed. With growth of mobile
communications, frequency assignments are getting difficult; particularly
in the frequency bands from VHF to 6 GHz suited for mobile
communications. It has become very difficult to allocate new frequencies
for new wireless services. To solve the problem, research and development
efforts to realize the cognitive radio technologies are being carried on.
Basic concept of cognitive radio :
Cognitive radio is a radio system that senses, and recognizes operational
communication environments and can dynamically and autonomously
adjusts its radio operating such parameters as frequency, transmission
power and data rates without interferences to other systems. Accordingly,
a user can establish communications with required capacity and quality.
Above Figure shows a conceptual image of a cognitive radio terminal.
In the Above Figure, we assume that a mobile user is going to use a
cognitive mobile phone.
There are several communication services such as IEEE802.11g (Wi-Fi,
2.4 GHz), 3G cellular (2 GHz) and IEEE 802.16e (WiMAX, 2.5 GHz) in
the communication environment. There is also a low interference to the
The procedure of a cognitive terminal to establish a communication
channel consists of following three steps.
1. The first step: Recognition of frequency environments.
A cognitive terminal will sense communication environments and detect frequencies
which are in use or not in use. A terminal has to scan wide frequency bands, which
cover possible communications in services.
2.The second step: Think and decision
According to the results of recognition of environments, a terminal has to decide and
select a system based on a policy such as communication costs, data speed,
communication quality and /or mobility. In any cases, a terminal or a base station has
to select a system and a channel, which avoids interferences to and from other systems.
3. The third step: Change function of spectrum managements
A terminal selects the optimal system or a user will select her favourite system from the
menu to change the function to establish communication channels of the selected
system, which procedure is called reconfiguration.
Cognitive radio technology is to make frequency use more efficient and to make
services more high quality by recognizing radio environments near the user terminal.
Two types of cognitive radio and cognitive radio network
1. Heterogeneous type :
Cognitive radio technologies can be divided into two types as shown in
Figure . A heterogeneous type aims at the connection with existing radio
system that is assigned with a dedicated frequency band, so that it can
positively use a radio system having surplus wireless resources or select a
radio system in accordance with the user's purpose to implement desired
2. Spectrum sharing type :
On the other hand, the method to use vacant frequency bands is called
spectrum sharing type (or white space type) cognitive radio. In spectrum
sharing type, vacant frequency bands include vacant bands and vacant
time slots of existing systems (primary operators) as well as vacant bands
not in use. By sensing vacant frequency band and time slot, users can use
adequate bandwidth by bundling vacant frequency bands. In operating
spectrum sharing type cognitive radios, cooperation with networks are
essential in order to coexist with the system which is serviced by a primary
Configuration of cognitive radio network
When a cognitive radio technology is applied to heterogeneous (consists of
different systems) wired networks, an ideal cognitive wireless network can
be established where terminals, base stations, and wireless access network
can be selected or reconfigured with optimum performance. As shown in
Figure- 4-2, in a cognitive wireless network, the measured data of
terminals and base stations are reported to the core network, and by
conducting the statistic processing and machine learning on the part of the
core network, reconfiguring requests for the operating frequencies and
communication systems can be issued to the radio access network (RAN).
Additionally, the network policy for supporting the terminals to select the
RAN and base station is provided from the network.
Hardware platform :
Figure- shows a typical configuration of a cognitive terminal consisting of
hardware devices such as an antenna, filters, amplifiers, mixer, a
synthesizer, analogue-digital (A/D) and D/A converters and signal
In order to scan wide frequency bands which cover many communication
services in operation, a cognitive radio requires a broadband RF (radio
frequency) unit, especially from VHF (30-300 MHz) up to 6GHz. Some
devices such as antennas and mixers are simply but very difficultly
required to cover these wide frequency bands. However, such devices as
filters and amplifiers are required not only broadband but also “tunable”
to a certain bandwidth suitable for sensing a desired system over VHF-up
to 6GHz. From this point, intelligent filter-banks to sense existing radio
communication systems are essential.
Software platform :
In order to sense, detect and reconfigure the radio system, a software
algorithm plays very important role in the cognitive radio.
As a basic software platform (radio reconfiguration manager), the
following factors are required :
• Work on the several CPUs
• Equip an open access point interface (API)
• Easily changeable parameters for spectrum sensing
• Equip arranged profiling procedure
• Block all of attacks for the waveforms (virus)
The core and essential parts of software of cognitive radio function are the following
software algorithms order to realize the optimum communication links for users and
• The fast selection and decision of the system,
• A high-speed system-sensing algorithm
• A high response reconfiguration algorithm for terminals and base stations and
• Network system architectures, which can perform the resource managements
cooperation with terminals, base stations and networks
Research Agenda for Cognitive Radio Networks
By their very nature, DSA and CRNs spans a range of disciplines. The
physical layer involves high performance radio frequency circuits. We
need to control and manage those circuits to gain flexibility and new
capabilities. Once out of the analog domain, we need to analyze and
process received communication signals. We need to limit bandwidth, be
efficient in our utilization of radio frequency spectrum, deal with
differences between the transmitter and receiver, handle radios in motion,
adapt for the physical communications from the transmitter to the
receiver, allocate radio resources for efficient communications, learn how
and when to share information, re-route network traffic as links go up and
down, and know how to adapt to the current situation in this complex
radio communications environment. Wireless networks are challenging
systems because of the complex nature of signal propagation.
DSA further exacerbates those problems since spectrum use is even more
dynamic and unpredictable. Cognitive networking research is inherently a
multidisciplinary endeavour that must address not only traditional
wireless networking challenges, but also the rational control and
management of the spectrum, a distributed and dynamic resource, which
raises complex policy and economic issues.
Cognitive Networks and the Internet
The research questions and answers essential to building cognitive radio
networks are, in some sense, extreme problems of wired networks. For
example, both wired and wireless networks need to deal with links going
up and down. However, in the wireless network, the frequency of link
status changes is much higher than in today’s wired network. So, wireless
network architectures must pay closer attention to link
status changes and react faster to these changes. Research in CR networks
will carry over into wired network.
Some characteristics of cognitive radio networks that are applicable
to larger, end-to-end network are:
• Operating environment sensing –
Cognitive radios measure and react to the environment they are operating in. The
radio environment is multi-dimensional; including cooperative and noncooperative
emitters turning on and off, CRs adapting to their local changes, and traffic loads; and
rapidly varying. CRs must rapidly adapt to this changing environment and
communicate their changing operation settings to other wireless devices in the
network. The mechanisms and Future Directions in Cognitive Radio Network
Research Page: 18 NSF Workshop Report June 2009 techniques to sense, adapt, and
communicate operation state are necessary in CR networks and applicable to networks
• Robust communication services with unreliable links –
The radio links, by their very nature, have intermittent outages. A link outage may
result from the temporary location of the receiver, transmitter and other objects in the
environment. CRs, by their very design, must deal with these very short-term link
outages, and do so through a variety of techniques. It is through this large set of
techniques and mechanisms that wireless networks implement a robust and reliable
communications service with unreliable links. The techniques and design patterns used
in wireless architectures are applicable to the larger network architecture.
• Operational state languages –
CRNs, as they adapt, must communicate their observations and operation state to
other CRNs in the network. A few “languages” will be needed to describe observations
and operation state. This information is likely to be much richer than common link
status information. For example, one radio might send a list of all emitters it has
recently sensed to other CRNs in the network. The entry for each emitter might
include a frequency range, time, and spatial location, and signal format (e.g., spread
spectrum or narrow-band FM). The language used to describe observations and
operation state will be much richer than conventional node or link state information.
The language(s) and protocols necessary for CRN networks should influence general
• Distributed Resource Management –
The radio spectrum is a distributed resource. Use of the spectrum in one location
affects the availability of that spectrum in other network locations. Allocation of the
radio spectrum resource must be carried out in a cooperative manner and balanced
between (quick) local decisions and (optimal) global allocation. The algorithms
developed to allocate the distributed radio spectrum and mobile network resources
based on traffic loads and operating environment are applicable to the GENI
infrastructure – and will require demanding new services within the GENI network.
These examples show how techniques and mechanisms necessary to CR networks will
have an influence on the architecture, design and implementations of networks in
FEATURES OF COGNITIVE RADIO :
Some features of cognitive radio networks include:
• Sensing the current radio frequency spectrum environment:
This includes measuring which frequencies are being currently used, estimating the
location of transmitters and receivers, and determining signal modulation. These
results are then used to determine the radio settings.
• Policy and configuration databases:
This includes having knowledge of the policies that specify how the radio can operate
and physical limitations of radio operation. This information can be stored in the radio
or made available over the network.
The policies might also specify which frequencies are licensed to be used in which
locations. Configuration databases would describe the operating characteristics of the
physical radio. These databases would normally be used to constrain the operation of
the radio to stay within regulatory or physical limits.
Dynamically programmable capability according to radio environment to transmit and
receive on a variety of frequencies i.e. the radio can automatically change its
parameters so as to work on different frequencies.
• Mission-oriented configuration :
Software defined radios can meet a wide set of operational requirements. Configuring
a SDR to meet a given set of mission requirements is called mission oriented
configuration. Typical mission requirements might include operation within buildings,
substantial capacity, operation over long distances, and operation while moving at high
speed. Mission-oriented configuration involves selecting a set of radio software
modules from a library of modules and connecting them into an operational radio.
• Adaptive algorithms :
During radio operation, the cognitive radio is sensing its environment, adhering to
policy and configuration constraints, and negotiating with peers to best utilize the
radio spectrum and meet user demands.
• Distributed collaboration:
Cognitive radios will exchange current information on their local environment, user
demand, and radio performance between themselves on a regular basis. Radios will use
their local information and peer information to determine their operating settings.
Radios will join and leave wireless networks. Radio networks require mechanisms to
authenticate, authorize and protect information flows of participants.
CRNs operate in a rich environment. The agility of underlying SDR platforms provides
a level of flexibility well beyond conventional radio and networking platforms.
SPECTRUM HOLE CONCEPT
A spectrum hole is a band of frequencies assigned to a primary user, but,
at a particular time and specific geographic location, the band is not being
utilized by that user.
A region of location-time frequency available for a secondary user is called
a spectrum hole (SH). Generally, a CR system is able to coexist with a
primary system by accessing SHs. Apparently, SH is a basic
resource for CR users.
FUTURE APPLICATIONS :
Cognitive radio technology can be used in a variety of applications in the
future which include•
4G technology - which aims at achieving very high data transmission rate.
For high rate larger bandwidth should be available so that more channels can
be accommodated within the system. However since the frequency spectrum is
limited this is not possible. CR approach allows accessing the under utilized
spectrum in the licensed bands and hence improving efficiency.
Cellular networks: With increase in the number of mobile phone users which
are expected to rise further in future there will be heavy traffic on the network
and hence jamming can occur. Hence CR technology can provide a solution for
Vehicular Communication: In the vehicular domain, the CR could be used
to enhance and improve intelligent interactions with the transportation system.
Importantly, CR could be the driving force in order to realize real-time
cooperative communications between the vehicles. This would eventually result
in seamless vehicle-to-vehicle and vehicle-to-infrastructure communications, a
gigantic step towards unified and continuous service provision involving
variable speed vehicles.
Emergency network: In case of a disaster, the load on the network increases.
This can be reduced if an alternate band is available to accommodate some of
the users which can be achieved using CR.
The rapid development of wireless technologies is expected to increase the
demand for radio spectrum by orders of magnitude over the next decade.
This problem must be addressed via a technology that can result in
improvement in spectrum efficiency and increase robustness and
performance of wireless devices.
Cognitive radio technology is one such innovation that could provide
solutions to the “radio traffic jam” problem and provide a path to scaling
wireless systems for the next 25 years.
Cognitive radio technology can be used in a variety of applications in the
future which include•
However there are a lot of technical challenges in cognitive radio
networking. These include dynamic spectrum allocation methods,
spectrum sensing, cooperative communications, cognitive network
architecture and protocol design, cognitive network security, cognitive
system adaptation algorithms and emergent system behaviour. A major
hurdle to continued progress in the field is the inability to conclusively
test, evaluate, and demonstrate cognitive networking technology, at scale
and in real-world deployment scenarios. This calls for the development of
a set of cognitive networking testbeds that can be used to evaluate
cognitive networks at various stages of their development.
Cognitive Radio Network applications :
Cognitive Radio Networks can be applied to the following cases:
1. Leased network:
The primary network can provide a leased network by allowing opportunistic
access to its licensed spectrum with the agreement with a third party without
sacrificing the service quality of the primary user. For example, the primary network
can lease its spectrum access right to a mobile virtual network operator (MVNO). Also
the primary network can provide its spectrum access rights to a regional community
for the purpose of broadband access.
Cognitive mesh network:
Wireless mesh networks are emerging as a cost-effective technology
for providing broadband connectivity. However, as the network density increases and
the applications require higher throughput, mesh networks require higher capacity to
meet the requirements of the applications. Since the cognitive radio technology enables
the access to larger amount of spectrum, CR networks can be used for mesh networks
that will be deployed in dense urban areas with the possibility of significant
contention. For example, the coverage area
of CR networks can be increased when a meshed wireless backbone network of
infrastructure links is established based on cognitive access points (CAPs) and fixed
cognitive relay nodes. The capacity of a CAP, connected via a wired broadband access
to the Internet, is distributed into a large area with the help of a fixed CRN. CR
networks have the ability to add temporary or permanent spectrum to the
infrastructure links used for relaying in case of high traffic load.
Public safety and emergency networks are another area in which CR
networks can be implemented. In the case of natural disasters, which may temporarily
disable or destroy existing communication infrastructure, emergency personnel
working in the disaster areas need to establish emergency networks. Since emergency
networks deal with the critical information, reliable communication should be
guaranteed with minimum latency. In addition, emergency communication requires a
significant amount of radio spectrum for handling huge
volume of traffic including voice, video and data. CR networks can enable the usage of
the existing spectrum without the need for an infrastructure and by maintaining
communication priority and response time.
One of the most interesting potential applications of an CR network is in a
military radio environment. CR networks can enable the military radios choose
arbitrary, intermediate frequency (IF) bandwidth, modulation schemes, and coding
schemes, adapting to the variable radio environment of battlefield. Also military
networks have a strong need for security and protection of the communication in
hostile environment. CR networks could allow military personnel to perform spectrum
handoff to find secure spectrum band for themselves and their allies.
Cognitive radio is an immature but rapidly developing technology area. In
terms of spectrum regulation, the key benefit of CR is more efficient use of
spectrum, because CR will enable new systems to share spectrum with
existing legacy devices, with managed degrees of interference. There are
significant regulatory, technological and application challenges that need
to be addressed and CR will not suddenly emerge.
Cognitive radio networks are being studied intensively. The major
motivation for this is the currently heavily under utilized frequency
spectrum. The development is being pushed forward by the rapid
advances in SDR technology enabling a spectrum agile and highly
conigurable radio transmitter/receiver. A fundamental property of the
cognitive radio networks is the highly dynamic relationship between the
primary users having an exclusive priority to their respective licensed
spectrum and the secondary users representing the cognitive network
devices. This creates new challenges for the network design which have
been addressed applying varies approaches as has been discussed in the
The fundamental problems in detecting the spectrum holes are naturally
mostly related to signal processing at the physical layer. From the traffic
point of view careful attention must be
paid in order to guarantee an effcient usage of the wireless medium while
simultaneously providing fairness between competing users and respecting
the priority of the primary users