ChapterPDF Available

Cognitive Radio: A Network Structure Perspective

Authors:

Abstract and Figures

The ideal utilization of radio spectra is a major issue of concern in the field of wireless communication. Increasing demand for wireless radio services has led to the issue of frequency scarcity. Therefore, in order to accommodate more and more users, cognitive radio technology came into existence. The adaptive nature of cognitive radio helps them enhance the spectral efficiency, thereby utilizing the available spectra without causing any interference for the licensed users. The primary task of cognitive radio lies in the spectrum sensing and identification of holes. But the presence of a single CR and multiple secondary users in the network can lead to delay and collision. Therefore, the algorithm named “multiple CRs single-hop (MCSH) secondary user cognitive radio network architecture” has been formulated and proposed in which multiple CRs can coordinate with each other via single hop as well as with unlicensed users in order to diminish the delay, jitter, and packet loss.
Content may be subject to copyright.
Cognitive Radio: A Network Structure Perspective
Tapan Kumar, Vansha Kher, and Pooja Jain
Indian Institute of Information Technology Kota, India
{tapan, vansha, pooja}@iiitkota.ac.in
Abstract: The ideal utilization of radio spectra is a major isue of concern in the field of
wireless communication.Increasing demand for wireless radio services have led to the issue of
frequency scarcity.Therefore,in order to accomodate more and more users, cognitive radio
technology has come into existence. The adaptive nature of Cognitive Radio (CR) help them
enhance the spectral efficiency, thereby utilizing the available spectra without causing any
interference for the licensed users.The primary task of cognitive radio lies in the spectrum
sensing a nd identification of holes. But the presence of a single CR and multiple secondary
users in the network can lead to delay and collision. Therefore, the algorithm named “Multiple
CRs Single Hop (MCSH) Secondary User Cognitive Radio Network Architecture” has been
formulated and proposed in which multiple CRs can coordinate with each other via single hop
as well as with unlicensed users in order to diminish the delay, jitter and packet loss.
Keywords: Cognitive Radio,Dynamic spectrum allocation, sensing,spectrum
holes,multi-hop, mobility.
1 Introduction
The Electromagnetic spectrum is a wholesome natural resource meant for data
transmisssion and reception of data and the exploitation of it by a large number of
transmitters and receivers is strictly licensed by government[1]. The Federal
Communications Commission (FCC) is the central agency that is solely responsible
for maintenance, control and regulation of interstate telecommunication,licensing as
well as management and of electromagnetic radio spectrum within the United States
and it also audits time to ti me inter-station interference in all radio frequency
bands[2]. All conventional wireless connection services, substantially based on fixed
spectrum allocation methodology are muchconstrained by the factors such as wastage
of static spectrum allocation, restricted and limited wireless functionality; leading to
inefficient utilization of radio spectrum. Therefore, spectrum efficiency can be
improved by manifesting the concept of Frequency Reuse where the Secondary Users
(SU) are being permitted to ingress the spectrum when the spectrum is temporarily
being not utilized by the Primary users (PU). The basic idea is to manage RF
resources in such a way that SU can be permitted to access the licensed frequencies
following the condition that they can guarantee minimum interference perceived by
the PU allocated in the RF spectrum.
The basic aim is to consider the architecture of Cognitive Radio (CR) in which all PU
and SU will send their data to the CR either in licensed or unlicensed mode (when
spectrum holes are present). Several Cognitive users are existing in a distributed
fashion and coordinates with SU for data communication in a single –hop in order to
increase the throughput, maximize the spectrum efficiency and to decrease the delay.
With the advances in software and technology, CR can smartly sense and adapt with
the changing environment by modifying its transmitting parameters, such as
modulation, frequency, frame format, etc [3]. In the early days of communication,
there were fixed radios in existence in which the transmitter parameters were static
and were fixed deliberately set up by their operators. The new era of communication
inculcates the concept of Software Defined Radio (SDR) [4-8].
A SDR is a radio in which a transmitter is present whose operating parameters
including the frequency range, type of modulation as well as maximum radiated or
output power can be altered, by initializing a change in software without performing
any hardware changes. It is used to reduce hardware requirements, since it provides
user an inexpensive and reliable solution. But it will not take into consideration the
area of spectrum availability. CR is basically a recent version of SDR in which all the
transmitter parameters modify and update like SDR, but it will also adapt its
parameters as per the the spectrum availability. The primary network is totally
unaware and unknown regarding the capabilities of the cognitive network behavior
and doesn’t necessitate any specific functionalities to co-exist with it. When a PU
arrives in the spectrum, the secondary users ought to vacate the spectrum and should
immediately react by altering their parameters like frequency rate, baud rate,power,
capacity, channel used, codebook, etc so that PU Quality of Service(QoS) might not
degrade.
The proposed technique is to design a CR network architecture named as “Multiple
CRs Single Hop(MSCH) Secondary User CR Network Architecture” in which
multiple CRs will act as heterogenous nodes that can perform the diverse functions of
spectrum sharing, allocation, management, mobility and decision making at the same
time. The unlicensed secondary users will behave as homogenous nodes that can
transmit their data on the licensed bands via multiple CRs in a single hop fashion [9].
2 Related Work
2.1 Cognitive Radio Network
Fixed spectrum allocation policy is employed in wireless networks. Spectrum can
remain under-utilized in some area or for some period of time, where as, some
frequencies will be highly utilized. Therefore some under-utilized wireless spectrum
should be exploited for maximizing the spectrum usage. CR act as secondary-tier
networks in order to access the spectrum. While the licensed users or PU are not using
the spectrum, CR user completely uses the spectrum in order to maximize the
spectrum utilization throughput[5]. Thus CR can be defined as a radio that can change
its transmission parameters based on the active environment in which it operates. The
CR determines that portion of the spectrum which remains available and thus detects
the availability of licensed users and selects the best available channel. CR also
coordinates access to this channel with others. The ultimate objective of CR lies in the
fact that it needs to obtain the best available spectrum due to its property of
reconfigurability and cognitive capability. The most challenging situation for CR is to
share the licensed spectrum keeping the condition that it won’t interfere with the
transmission of other licensed users since most of the spectrum is legally shared
between several PU. The CR enables the process of usage of temporary unused
spectrum gaps called as spectrum hole or white space in Figure 1. İn the case of again
using the spectrum by the licensed user, the CR moves in another spectrum hole or
remains in the same band. By altering its modulation technique, transmitted power
level in order to mitigate the chances of interference.
Figure 1. Spectrum Hole Concept
2.2 Cognitive Network Architecture
The reference CR architecture includes different types of network such as the primary
network, an infrastructure based secondary network as well as an ad-hoc based
secondary network. These CR based networks are operated under the mixed spectrum
environment that consists of both licensed and non-licensed frequencies. As quoted by
multiple authors in the literature for cognitive networks, multiple secondary networks
can communicate with each other in a multi-hop manner or across the base station or
across the base station, leading to collision of data and a large amount of delay
between different SU during the data transmission. Therefore in this proposed
technique, we are relying on the fundamentals of single hop technique between
different XG users and SU in order to maximize the throughout and reducing the delay
and collisions using MS-SH [9] network architecture.
There are three different access types which are as under in Figure 2:
1. Secondary network access: SU have the ability to access their own secondary
base station both on licensed and unlicensed spectrum bands.
2. Secondary Adhoc access: SU are free to communicate with all other
secondary users through adhoc connection on licensed as well as unlicensed
spectrum bands.
3. Primary network access: The SU are capable of accessing the primary base-
station through the licensed band. [10]
Fig
ure
2.
Cog
nitive Radio Architecture
[
]
Figure
3.
Cognitive Radio Cycle
Two basixc groups are inculcated in CRnetworks: Primary User network and
Cognitive radio and Secondary User network architecture .
The Primary Network: It has an exclusive right over a certain spectrum band, like for
cellular networks and T.V. broadcast networks since it is a licensed user. The basic
components of primary networks are: PU which is also called as licensed user, that is
having all rights to operate in a licensed band. The PU remains unaffected by the
activities of CR. Primary base-station which is also called as licensed base-station, a
fixed infrastructure network component having spectrum license.
CR Network: The CR network doesn’t possess license to operate in a licensed
band and its spectrum access is allowed according to the opportunistic
environmental conditions. The components of CR network are as under:
CR user: It is basically an unlicensed user that is possessing no license over the
spectrum. CR can use the spectrum only when PU is not present and CR has t o
vacate the spectrum /channel when ever the PU will be detected.
CR base-station: It is an unlicensed base-station meaning a fixed infrastructure
component with CR capabilities that provides a single-hop connection to CR users.
Spectrum Broker: It’s a central network entity that is capable of managing and
controlling the spectrum resource sharing among the XG users.
Secondary User (SU) : The SU comes in picture along with the Cognitive user
only when the PU is not present in the spectrum.
2.3 Cognitive Radio Cycle
The important areas of CR cycle are mainly categorized into four following steps as
shown in Figure 3:
Step 1: Spectrum Sensing, only for the unused portion of the spectrum, CR allocation
can be done.Therefore, continuous monitoring of the available spectrum bands is
important and hence the spectrum holes can be detected.Spcetrum sensing is basically
performed on the physical layer and is closely related to spectrum allocation
problems.Three main potential approaches are recognized such as beacon signals,
database registry and spectrum sensing [11] in order to identify the spectrum
opportunities. The database registry technique inculcates the method of Global
positioning system (GPS) that are mounted on secondary devices to locate its
respective location and for accessing the database of primary network for locating the
channels that are un-used and vacant at that time. Two spectrum sensing methods are
widely used in the CR architecture:
Non –Cooperative /Transmitter detection.
Cooperative detection.
Step 2: Spectrum Decision,According to the QoS requirements of different bands, the
CR user identifies most suitable band after the process of identication of available
spectrums in the network.The statistical behaviour of the PUs and the radio
environment decides the characteristics of the spectrum band. For dynamic spectrum
characteristics, it is important to have apriori information about the PU activity and this
entire process is done in the link layer and the network layer.
Step 3: Spectrum Sharing,Since multiple CRs are coordinating with each ther
interconnected to different SU in order to avoid collisions in the overlapped portions of
the spectrum.The technique of spectrum sharing provides the capability to have
resource allocation in order to mitigate interferencecaused on the primary
network.Therefore, physical layer and MAC protocols are being applied that can easily
facilitate the sensing control to distribute the sensing task among the coordinating
nodes as well as spectrum access in order to determine the timing mandatory for
transmission.
Step 4: Spectrum Mobility, In case of detection of a PU in the network, the CR should
vacate the licensed spectrum and should continue its transmission in another unutilized
band , thereby connecting to another CR s lying in vicinity of that particular
SU.Therefore the spectrum mobility technique hence utilizes the scheme of spectrum
hand-off in order to detect the failure in any link and in ordfer to decrease the packet
drops. Also the connection management scheme is added in order to sustain the
performance of upper layer protocols.
2.4 CR Network Capability
The capabilities of a CR network includes Re-configurability, operating frequency,
Modulation, Transmission power and communication technology. Configurability can
be defined as ability of adjusting some operating parameters for the purpose of
transmission without any mandatory modification . For the CR user to adapt easily in
the dynamic radio environment, reconfigurability is an important feature in CR
networks.[12-13]
3. Cognitive Radio Architecture Framework
In order to decrease the end to end delay and to fulfill the connection requirements,
single hopping is preferred in CR networks among corresponding SUs.In the case of
arrival of PUs in the RF spectrum,spectrum handoff occurs leading to dynamic
spectrumn allocation in which SU relocates to another CR through Spectrum
broker,therevy maximizing the spectral efficiency.It wouldn’t be possible in “Single
CR Single Hop” and “Single CR Multiple Hop” networks as SU has to vacate the
spectrum as the PU comes into the picture.Hence,“Multiple CRs Single Hop (MCSH)
Secondary User Cognitive Radio Network Architecture” is the most optimal CR
architecture reducing the delay , jitter and packet loss.
The CR ensures three basic fundamental cases to incur Multiple Sink Single Hop
Architecture .
Case1: If one of the SU is connected to multiple secondary BS / Primary Network
Access, then the unlicensed user will relinquish its control over one CR so that it can
allocate the unused spectrum to any other unlicensed user in the network.
Case2: The restructing of network should be done like energy balancing, bandwidth
allocation in order to decrease delay and in order to increase the network coverage.
Case 3:To calculate the optimum number of CRs so that no packet loss, delay can be
incurred in the network.
3.1 Simulation Steps
The following are the simulation steps and results shown in Table 1.
1. All the CR’s (Secondary base station and Primary Network Access) behave
as Hetrogeneous and cover defined geographical area and provide the
connection to all the secondary users. Simulation was performed for 10 to 15
CRs
2. SUi are randomly deployed and stationary. For simulation the total 1000
SU’s are used.
3. The optimal number of CRs is also found out using connection restructuring
of SU. Maximum 250 SU are supported by each CRs.
4. Initially one SU is connected to multiple CRs, but after the connection
restructuring SU is connected to the sihgle CR and enhance the spectral
efficiency. Results are shown in Table 1.
Table 1.Simulation Results
No. of Secondary BS /
Primary N/W Access
Max. SU connected to
Single Sec. BS
After re structuring the Max.
SU connected to Single Sec. BS
378
186
359
152
364
137
353
118
352
106
361
110
4. Conclusion
On the basis of above three cases, we conclude that multiple CR Single hop
secondary user CR network architecture has been found out to be the optimum
structure as per the design parameters of CRs like Bandwidth, collision avoidance,
connectivity, optimum number of CRs required as compared to single CR- Single Hop
and multiple CR-Multiple hop CR network architecture design.
References
1. FCC, ET Docket No 03-222 Notice of proposed rule making and order, December 2003.
2. S. Haykin, Cognitive radio: brain-empowered w ireless communications, IEEE Journal on
Selected Areas in Communications 23 (2) (2005) 201–220.
3. J. Mitola III, Cognitive radio: an integrated agent architecture for software defined radio,
Ph.D Thesis, KTH Royal Institute of Technology, 2000.
4. Joseph Mitola III “Cognitive radio: an integrated agent architecture for software defined
radio,” Ph.D. Thesis, Royal Institute of Technology (KTH) Sweden, May 2000.
5. F. K. Jondral, “Software-defined radio: basics and evolution to cognitive radio,” EURASIP
Journal on Wireless Communications and Networking, vol. 5, no. 3, pp. 275–283, 2005.
6. U. Ramacher, “Software-defined radio prospects for multi-standard mobile phones,” IEEE
J. of Computer, vol. 40, no. 10, pp. 62–69, 2007.
7. R. Bagheri, A. Mirzaei, M.- E. Heidari, S. Chehrazi, M. Lee, M. Mikhemar, W. K. Tang,
and A. A. Abidi, “Software-defined radio receiver: dream to reality,” IEEE
Communications Magazine, vol. 44, no. 8, pp. 111–118, 2006.
8. H. Arslan and S. Yarkan, “Cognitive Radio, Software Defined Radio, and Adaptive
Wireless Systems,” Springer: Netherlands, 2007
9. Jain, Tapan Kumar, Davinder Singh Saini, and Sunil Vidya Bhooshan. "Lifetime
optimization of a multiple sink wireless sensor network through energy balancing." Journal
of Sensors 2015 (2015).
10. Akyildiz, Ian F., Won-Yeol Lee, Mehmet C. Vuran, and Shantidev Mohanty. "NeXt
generation/dynamic spectrum access/cognitive radio wireless networks: a
survey." Computer networks 50, no. 13 (2006): 2127-2159.
11. E. Hoossain, D. Niyato, and Z. Han, “Dynamic Spectrum Access and Management in
Cognitive Radio Networks,” Cambridge University Press: New York, 2009.
12. Pandit, Shweta, and G. Singh. "An overview of spectrum sharing techniques in cognitive
radio communication system." Wireless Networks (2015): 1-22.
13. Akyildiz, Ian F., Won-Yeol Lee, and Kaushik R. Chowdhury. "CRAHNs: Cognitive radio
ad hoc networks." AD hoc networks 7, no. 5 (2009): 810-836.
Chapter
Vehicle-to-vehicle or V2V communication, a progressively developing technology that uses IEEE 802.11 p-based systems to enable vehicular communication over a few hundreds of meters, is being introduced in numerous vehicle designs to equip them with enhanced sensing capabilities. However, it can be subjected to a lot of interference due to sensitivity that can cause potential channel congestion issues. V2V can be complemented using visible light communication (VLC), an alternative technology that uses light emitting diodes (LEDs), headlights or tail lights to function as transmitters, whereas the photodiodes or cameras function as receivers. Although, in real-time applications, a V2V-VLC cannot be demonstrated due to unreliability. In this paper, the overall performance of the vehicle-to-vehicle communication is being implemented using orthogonal frequency division multiplexing (OFDM) in combination with amplitude shift keying (ASK), also termed as on–off keying (OOK) modulation, binary phase shift keying (BPSK) and quadrature phase shift keying (QPSK) digital modulation techniques. All the above-mentioned modulation techniques, i.e., OFDM-OOK, OFDM-BPSK and OFDM-QPSK, are being compared using the following design parameters, i.e., signal to noise ratio (SNR) versus bit error rate (BER) as well as spectral efficiency, in order to choose the best technique for V2V communication. By extensive analysis, in terms of rate and error performances, we have observed that QPSK modulation technique with OFDM performs better when compared to OFDM with OOK and BPSK modulation techniques for V2V communication.
Chapter
Color vision deficit (sometimes known as colour blindness) is a term used to describe a set of diseases that impact colour perception. People take many color blindness tests while consulting an Eye Specialist to check if they are suffering from this deficiency. This test is conducted by showing different types of color blindness charts to the patient and then asking him/her to read those charts. In this paper, we make the machine learn the color blindness charts and identify the pattern present in it, using Image processing and Deep learning. Charts may contain a single digit or double-digit number or any unrecognized pattern. For this, we collected color blindness charts from the internet, preprocessed and augmented them for training purposes using CNN. Deep Learning is a method in which a computer software learns statistical patterns in data so that it can recognise or help us distinguish between the patterns in the charts. The model learns about the various attributes based on the photos and represents the data mathematically, organising it in space.
Article
Full-text available
The wireless sensor network consists of small limited energy sensors which are connected to one or more sinks. The maximum energy consumption takes place in communicating the data from the nodes to the sink. Multiple sink WSN has an edge over the single sink WSN where very less energy is utilized in sending the data to the sink, as the number of hops is reduced. If the energy consumed by a node is balanced between the other nodes, the lifetime of the network is considerably increased. The network lifetime optimization is achieved by restructuring the network by modifying the neighbor nodes of a sink. Only those nodes are connected to a sink which makes the total energy of the sink less than the threshold. This energy balancing through network restructuring optimizes the network lifetime. This paper depicts this fact through simulations done in MATLAB.
Article
Full-text available
Cognitive radio (CR) technology is envisaged to solve the problems in wireless networks resulting from the limited available spectrum and the inefficiency in the spectrum usage by exploiting the existing wireless spectrum opportunistically. CR networks, equipped with the intrinsic capabilities of the cognitive radio, will provide an ultimate spectrum-aware communication paradigm in wireless communications. CR networks, however, impose unique challenges due to the high fluctuation in the available spectrum as well as diverse quality-of-service (QoS) requirements. Specifically, in cognitive radio ad hoc networks (CRAHNs), the distributed multi-hop architecture, the dynamic network topology, and the time and location varying spectrum availability are some of the key distinguishing factors. In this paper, intrinsic properties and current research challenges of the CRAHNs are presented. First, novel spectrum management functionalities such as spectrum sensing, spectrum sharing, and spectrum decision, and spectrum mobility are introduced from the viewpoint of a network requiring distributed coordination. A particular emphasis is given to distributed coordination between CR users through the establishment of a common control channel. Moreover, the influence of these functions on the performance of the upper layer protocols, such as the network layer, and transport layer protocols are investigated and open research issues in these areas are also outlined. Finally, a new direction called the commons model is explained, where CRAHN users may independently regulate their own operation based on pre-decided spectrum etiquette.
Article
Full-text available
We provide a brief overview over the development of software-defined or reconfigurable radio systems. The need for software-defined radios is underlined and the most important notions used for such reconfigurable transceivers are thoroughly defined. The role of standards in radio development is emphasized and the usage of transmission mode parameters in the construction of software-defined radios is described. The software communications architecture is introduced as an example for a framework that allows an object-oriented development of software-defined radios. Cognitive radios are introduced as the next step in radio systems' evolution. The need for cognitive radios is exemplified by a comparison of present and advanced spectrum management strategies.
Book
Today’s wireless services have come a long way since the roll out of the conventional voice-centric cellular systems. The demand for wireless access in voice and high rate data multi-media applications has been increasing. New generation wireless communication systems are aimed at accommodating this demand through better resource management and improved transmission technologies. This book discusses the cognitive radio, software defined radio, and adaptive radio concepts from several perspectives.
Article
Today’s wireless networks are characterized by a fixed spectrum assignment policy. However, a large portion of the assigned spectrum is used sporadically and geographical variations in the utilization of assigned spectrum ranges from 15% to 85% with a high variance in time. The limited available spectrum and the inefficiency in the spectrum usage necessitate a new communication paradigm to exploit the existing wireless spectrum opportunistically. This new networking paradigm is referred to as NeXt Generation (xG) Networks as well as Dynamic Spectrum Access (DSA) and cognitive radio networks. The term xG networks is used throughout the paper. The novel functionalities and current research challenges of the xG networks are explained in detail. More specifically, a brief overview of the cognitive radio technology is provided and the xG network architecture is introduced. Moreover, the xG network functions such as spectrum management, spectrum mobility and spectrum sharing are explained in detail. The influence of these functions on the performance of the upper layer protocols such as routing and transport are investigated and open research issues in these areas are also outlined. Finally, the cross-layer design challenges in xG networks are discussed.
Conference Paper
Cognitive radio wireless networks is an emerging communication paradigm to effectively address spectrum scarcity challenge. Spectrum sharing enables the secondary unlicensed system to dynamically access the licensed frequency bands in the primary system without any modification to the devices, terminals, services and networks in the primary system. In this paper, we propose and analyze new dynamic spectrum access schemes in the absence or presence of buffering mechanism for the cognitive secondary subscriber (SU). A Markov approach is developed to analyze the proposed spectrum sharing policies with generalized bandwidth size in both primary system and secondary system. Performance metrics for SU are developed with respect to blocking probability, interrupted probability, forced termination probability, non-completion probability and waiting time. Numerical examples are presented to explore the impact of key systems parameters like the traffic load on the performance metrics. Comparison results indicate that the buffer is able to significantly reduce the SU blocking probability and non-completion probability with very minor increased forced termination probability. The analytic model has been verified by extensive simulation.