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\begin{document}

\title{Welcome to Authorea!}


\author{AVIJIT BOSE}
\affil{Affiliation not available}



\date{\today}

\maketitle




CONTENTS Page\\

1. Dynamic Spectrum Allocation\\

1.1 Introduction\\

1.2 Dynamic Spectrum Allocation\\

1.3 Cognitive Radio\\

1.4 Need for Dynamic Spectrum Access\\

2. Effective Pricing~ Model\\

2.1 What is Effective pricing Model\\

2.2 Why Pricing Model is required?\\

2.3 Approaches for Designing pricing Model\\

3. Ad Hoc Network\\

3.1 What is Ad Hoc Network\\

3.2 Pricing Issues in Ad Hoc Network\\

3.3 Pricing Issues in Hybrid Network\\

3.4 Pricing Issues in WiFi System\\

3.5 Other Pricing Issues\\

4. Game Theory\\

4.1 Cooperative Game Theory\\

4.2 Non Cooperative game theory\\

4.3 Game Theory formulation for defining the Pricing issues\\

5. Cloud Computing\\

5.1 Cloud Computing\\

5.2 Scheduling and Resource Allocation in Cloud Computing\\

5.3 Pricing Model in Cloud Computing environment.\\

6. Literature Survey\\

7. Formulating the Problem\\

7.1 Defining the Model\\

7.2 Solution of the Model with optimization\\

7.3 Difference Between Linear and Non Linear Model\\

7.4 Optimization issues\\

7.5 Results and Discussion\\

8. Conclusion\\

9. Future Scope\\

~ CHAPTER-1 ~~~~~~~~~~~ INTRODUCTION\\

1.1~~ Introduction\\

Mitola came out with the concept of SDR (Software Defined Radio) and
then with CR (Cognitive Radio Network) in 1991 and 1998 respectively.~
Cognitive radio is a synonym for dynamic spectrum access. As shown in
fig (i) there are several models based on which Dynamic spectrum access
actually works {[}1{]}.\\

ONOMY\\

FIG-1 TAXONOMY OF DYNAMIC SPECTRUM ACCESS\\

As can be seen from above that Dynamic Spectrum Allocation comes under
Dynamic Exclusive use model and is a part of Dynamic Spectrum Access. In
Spectrum property rights allows licenses to sell and trade spectrum and
freely choose technology. Here the licenses are shared in spectrum for
profit.~ Dynamic Spectrum Allocation aims to improve spectrum efficiency
through dynamic spectrum assignment by exploiting the spatial and
temporal traffic statistics of different services. In other words, in a
given region and at a given\\

time, spectrum is allocated to services for exclusive use. This
allocation, however, varies at a much faster scale than the current
policy. However both the above methods cannot eliminate white spaces
resulting from the busty nature of the wireless traffic. In the open
sharing model among per users as the basis for managing a temporal
region. Here also the best example is the unlicensed band where many
operators operate e.g wifi, medical instrument etc. In the hierarchical
sharing model it adopts a hierarchical structure with primary and
secondary users. The basic idea is to open licensed spectrum to
secondary users. Here we consider two approaches: - spectrum underlay
and spectrum overlay. In the spectrum underlay approach the secondary
users are put into several constraints so that they operate below the
noise floor of the primary users. So secondary users can achieve short
range high data rate with low transmission power. However detection and
exploitation of spectrum white space does not take place here.~ In the
spectrum overlay which was conceived by Mitola and the concept of
spectrum pooling was first introduced. Here there is no imposition of
constraints to secondary users (transmission power) but rather there
should be a probabilistic distribution on when and where they can
transmit. It targets at temporal and spatial spectrum white space by
allowing secondary users to identify and exploit local and instantaneous
spectrum availability. However there should not be any intrusion.\\

1.2 Dynamic Spectrum Allocation

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