Proceedings of National Conference on New Horizons in IT - NCNHIT 2013
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A Competitive Spectrum Sharing using A Game
Theoretic Approach in Cognitive Radio Network
Harshali Patil and Dr. Seema Purohit
Abstract--- Cognitive Radio is a radio network has a
capability to obtain knowledge of its environment
autonomously and dynamically adjust to the operational
parameter. It establishes the policies and learns from the
results obtained. Radio spectrum is a limited resource in
wireless network so efficient utilization of it; becomes an
important issue. Resource allocation and sharing is one of the
most challenging and important aspect of radio
communication networks. We have considered the problem of
spectrum sharing among a primary user and multiple
secondary users, in this paper. This problem is formulated as
an oligopoly market competition and use a Cournot game to
obtain the spectrum allocation for secondary users. The static
Cournot game formulation is used when all secondary users
Nash equilibrium is used to can observe the adopted strategies
and payoff of each other. The strategic selection of secondary
user is solely depending on the pricing information obtained
from primary user. Nash equilibrium is considered as a
solution of this game
Index Terms--- Cognitive Radio, Spectrum Sensing,
Resource Sharing, Cournot Game
I.
INTRODUCTION
A
ll Frequency spectrums are the scarcest resource in
wireless communications. A diverse type of users,
applications and air interfaces uses the frequency spectrum
which may lead to problem of network congestion [1].
Today’s wireless networks are considered as a static spectrum
assignment policy. The increase in spectrum demand is facing
spectrum scarcity at particular spectrum bands. On the
contrary, a large portion of the assigned spectrum is still used
infrequently leading to underutilization of the significant
amount of spectrum [2].
The concepts of Software Defined Radio (SDR) and
Cognitive Radio (CR) were introduced to enhance the
efficiency of frequency spectrum usage. Software radio
improves the capability of a wireless transceiver. The term
SDR was introduced in the late 1990s by some manufacturers
who created radio terminals capable of using more than one
communication technique (e.g., GSM and CDMA); that is the
terminals can alter their operation mode or technique by
means of software. Thus this techniques is known as Software
Defined Radio (SDR). Cognitive Radio (CR) is a new
Harshali Patil, Associate Professor, Mumbai Educational Trust-ICS,
Mumbai, India, E-mail : [email protected]
Dr. Seema Purohit, Director, Navinchadra Mehta Institute of Technology
and Development, Mumbai, India, E-mail: [email protected]
technology proposed to improve spectrum utilization of
wireless telecommunications. It is used to address the issue of
inefficient spectrum management and the increasing demand
of spectrum resources [3]. Two rules have been found through
the study of the utilization of the existed radio spectrum: (1)
some spectrum is used most of the time; (2) most of spectrum
is not used in the most time. Primary users are licensed user
and secondary users are unclosed users. Primary users allow
secondary users to operate in their licensed spectrum when
they are not using it, which contributes to improving spectrum
utilization [4]. As a result, there are three possible dynamic
spectrum access (DSA) approaches that have been suggested
as possible solutions to improve spectrum utilization: i) open
sharing, ii) hierarchical-access and iii) dynamic exclusive use
[5].
Game theory is suitable solution for cognitive radio and
Nash equilibrium in non-cooperative game is suitable for few
secondary users to use the licensed spectrum of primary users
through competition and cooperation. In this paper, we
consider the problem of dynamic spectrum sharing in a
cognitive radio network. In such an environment, there is a
primary user allocated with a licensed radio spectrum the
utilization of which could be improved by sharing it with the
secondary users. The spectrum sharing problem can be
formulated in oligopoly market problem, in which few firm
compete with each other to gain profit in market share by
supplying certain amount of products/goods. In spectrum
sharing problem the secondary users are related to the firm
who compete for spectrum offered by primary user. Pricing
functions are used to find the cost of spectrum. The problem
is defined by using Cournot game and Nash equilibrium is
used for solution identification. The maximization of profit to
secondary users is a main objective of Cournot game. At the
beginning we consider that the secondary user observes the
strategies adopted by each user and the corresponding payoffs.
Whereas this situation is not practically possible, because
there may be some secondary users those are not aware (out of
transmission range) of each other. So we need to consider two
scenarios. For the first scenario where secondary users
observes the strategies adopted by each user and
corresponding payoff, can be implemented by static Cournot
game and Nash equilibrium can be obtained. Similarly for the
second scenario we can implement dynamic Cournot game
and selection of strategy from secondary user is based on the
pricing information provided by the primary user [6].
The implementation of the game model is discussed in the
further sections of this paper.
ISBN 978-93-82338-79-6
Proceedings of National Conference on New Horizons in IT - NCNHIT 2013
II.
COGNIVE RADIO
The term Cognitive Radio was firstly described by Joseph
Mitola. “A cognitive radio is a transceiver which
automatically detects available channels in wireless spectrum
and accordingly changes its transmission or reception
parameters so more wireless communications may run
concurrently in a given spectrum band at a place. This process
is known as “dynamic spectrum management”. In response to
the operator's commands, the cognitive engine is capable of
configuring radio-system parameters. These parameters
include "waveform, protocol, operating frequency, and
networking"[7].
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regulation, as this spectrum might be originally assigned to a
licensed communication system. The sharing of licensed
spectrum with primary radio systems is referred to as vertical
sharing, as indicated in Figure 4, and the sharing between
equals as for instance in unlicensed bands is referred to as
horizontal sharing. These terms of horizontal and vertical
spectrum sharing are first mentioned in [10].
Depending on transmission and reception parameters, there
are two main types of cognitive radio:
•
Full Cognitive Radio (Mitola radio), in which every
possible parameter observable by a wireless node (or
network) is considered [8].
• Spectrum-Sensing Cognitive Radio, in which only the
radio-frequency spectrum is considered [9].
The term cognitive radio is derived from “cognition”.
According to Wikipedia cognition is referred to as
•
•
•
•
Mental processes of an individual, with particular
relation
Mental states such as beliefs, desires and intentions
Information processing involving learning and
knowledge
Description of the emergent development of knowledge
and concepts within a group
Fig.2 Cognitive cycle – Function
Through spectrum sensing and analysis, cognitive radio can
detect white spaces, which is a portion of frequency band that
is not being used by primary user. On the other hand, when
primary user starts using licensed spectrum again, the cognitive
radio through sensing, so that no harmful interference would be
generated.
The cognitive cycle is depicted in figure 1
Fig.3 Spectrum White Spaces
The cognitive radio shares spectrum with different radio
systems. Depending on regulatory status, vertical or horizontal
spectrum sharing is done. The spectrum sharing is shown in
following figure.
Fig. 1 Cognitive cycle
The typical duties of cognitive cycle are detecting
spectrum white space, selecting best frequency bands,
coordinating spectrum access with other users, and vacating
frequencies when primary user need it. Such a cognitive cycle
is supported by following functions
• Spectrum sensing and analysis
• Spectrum management and handoff
• Spectrum allocation and sharing
The cognitive cycle is elaborated and details of the
cognitive cycle functions are as shown in figure 2.
The cognitive radio is a self-aware communication system
that assigns spectrum in an intelligent way. The classification
of spectrum as being unused and the way it is used involves
Fig. 4 Spectrum sharing as per regulatory status
III.
USERS: PRIMARY & SECONDARY
Consider a wireless system with a primary user and
multiple secondary users i.e. total number of secondary users
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Proceedings of National Conference on New Horizons in IT - NCNHIT 2013
230
is denoted by N. The secondary user wants to share the
spectrum allocated to the primary user. Thus scenario is the
primary user is willing to share some portion of the spectrum
(bi) with secondary user i.
pi(B) = rikibi − bic(B).
Assuming the guards bands used to separate the spectrum
allocation to different secondary users is fixed and small.
The charges for spectrum to be collected from secondary
user by a primary user are denoted by c(b) per unit bandwidth,
where b is the amount of available bandwidth that can be
shared. After allocation, the secondary users transmit in the
allocated
spectrum.
pi(B) = rikibi – bi( x+y (∑jbj)τ)
Nash equilibrium is a list of strategies, per player one
strategy. Players can not increase payoff matrix by choosing
different actions. Nash equilibrium is obtained by using the
best response function which is the best strategy of one player
given others’ strategies.
Therefore
V.
DYNAMIC COURNOT GAME
As per a second scenario in cognitive radio environment,
secondary users may only be able to observe the pricing
information from the primary user but not the strategies and
profits of other secondary users. Therefore, we have to obtain
Nash equilibrium of each secondary user based on the
interaction with the primary user only.
Fig. 5 Model for Spectrum Sharing
The revenue/profit of secondary user i is denoted by ri per
unit of achievable transmission rate [6].
IV.
STATIC COURNOT GAME
Based on the system model the Cournot game can be
formulated as follows.
The firm in oligopoly market; players in this game are the
secondary users. The strategy of each of the players
corresponds to the allocated spectrum size, i.e. the pricing
function based decision taken; (denoted by bi for secondary
user i) which is non-negative. Payoff of each player is profit
and is denoted by pi.
The supplied product/commodity in oligopoly market is
frequency spectrum. The pricing function used to charge the
secondary users is given by [6]
Where x and y are non negative constants. τ ≥ 1 so that this
pricing function is rounded, and B denotes the set of strategies
of all secondary users (i.e., B = {b1, . . . bN}). Let w denote the
worth of the spectrum for the primary user. Then, the condition
c(B) > w× ∑ j bj is necessary to ensure that the primary user is
willing to share spectrum of size b with the secondary users.
Note that, the primary user charges all of the secondary
users at the same price.
The revenue/profit of the secondary user i can be obtained
from ri × ki × bi, while the cost of spectrum allocation is
bic(b).
Therefore, the profit of the secondary user i can be
obtained as follows:
Since all secondary users can adjust the spectrum size bi
based on the marginal profit function. In this case, each
secondary user communicates with the primary user to obtain
the differentiated pricing function for different strategies. The
adjustment of the allocated spectrum size can be modelled as a
repeated Cournot game as follows:
where bi(t+1) is the allocated spectrum size at time t, αi is
the speed adjustment parameter (i.e., learning rate) of
secondary user i.
VI.
GAME MODEL AND CRN
In the cognitive radio network (CRN), the formal game
model for the power control can be defined as follows:
•
Players: are the cognitive users (secondary users
(SUs)).
• Actions: called also as the decisions, and are defined
by the transmission power allocation strategy.
• Utility function: represents the value of the observed
quality of-service (QoS) for a player, and is defined
later in this section.
The central idea in game theory is how the decision from
one player will affects the decision-making process from all
other players and how to reach a state of equilibrium that
would satisfy most of the players.
A utility function that meets the objective to maximize the
Secondary users’ capacity, and the protection for Primary user
is given as follows. The utility function is defined as:
Utility function = payoff function - price function
A payoff is used to state the capacity need of multiple
secondary users. A price function is used to represent the
protection for primary user, it is used to charge secondary
user.
ISBN 978-93-82338-79-6
Proceedings of National Conference on New Horizons in IT - NCNHIT 2013
VII.
CONCLUSION
In this paper, a competitive spectrum sharing scheme
based on game theory for a cognitive radio network consisting
of one primary user and multiple secondary users sharing the
same frequency spectrum. We have considered the spectrum
sharing by oligopoly market and static Cournot game is used
to model the system. The static Cournot game is useful only
when all the secondary users are able to observe the strategies
and the payoffs of other secondary users and dynamic
otherwise.
Dynamic spectrum access is an essential approach for
increasing efficiency in spectrum use. It is used to counteract
the observed spectrum scarcity. One concept to utilize
occurring spectrum holes in the time/frequency plane are
overlay systems that are deployed in the same frequency band
as a licensed system. To avoid collisions as well as mutual
interference, the overlay system has to periodically perform
measurements to detect the allocation of the licensed system
and dynamically adapt its system parameters [12].
Cournot game model based spectrum sharing scheme will
be useful for design and engineering of next generation
cognitive wireless networks.
REFERENCES
[1]
J. Mitola, “Cognitive radio for flexible multimedia communications,” in
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[2] FCC, ET Docket No 02-135, Spectrum Policy Task Force Report, Nov
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[3] Haykin
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[4] Ning Tang, Jun Sun, Shixiang Shao, Longxiang Yang, Hongbo Zhu, “An
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[5] Q. Zhao, B. M. Sadler. A survey of dynamic spectrum access [M]. IEEE
Sig. Proc. Magazine, 2007, 24(3): 79-89
[6] Dusit Niyato and Ekram Hossain, “A Game-Theoretic Approach to
Competitive Spectrum Sharing in Cognitive Radio Networks”, IEEE
Communications Society, 2007, 1525-3511/07
[7] Wikipedia, Cognitive Radio,11th June 2012
[8] J. Mitola III and G. Q. Maguire, Jr., "Cognitive radio: making software
radios more personal," IEEE Personal Communications Magazine, vol. 6,
nr. 4, pp. 13–18, Aug. 1999
[9] S.
Haykin,
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[10] J. Kruys, "Co-existence of Dissimilar Wireless Systems," http://www.wifi.org/opensection/pdf/coexistence_dissimilar_systems.pdf, July 2003
[11] White paper on “Cognitive Radio and Management of Spectrum and
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[12] Friedrich K. Jondral, Ulrich Berthold, Dennis Burgkhardt, and Timo A.
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