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Introduction Motivation Our Work Results Future Work
A New Power Allocation Scheme for SpectrumSharing OFDM Cognitive Radio Networks
Anubhav Singla and Mainak ChowdhuryMentor: Dr. Ajit K. Chaturvedi
BTech projectMid Term Presentation
Department of Electrical Engineering, IIT Kanpur
November 11, 2010
Introduction Motivation Our Work Results Future Work
1 Introduction
2 Existing schemes in literature
3 Our Work
4 Numerical results
5 Future Work
Introduction Motivation Our Work Results Future Work
Outline
1 Introduction
2 Existing schemes in literature
3 Our Work
4 Numerical results
5 Future Work
Introduction Motivation Our Work Results Future Work
Cognitive Radios
Opportunistic spectrum utilization by unlicensed users(Secondary Users)
Licensed users (Primary users) should not suffer much
System needs to be aware of the spectrum environment
Real time optimization of operating parameters - carrierfrequency, transmit power, etc
Introduction Motivation Our Work Results Future Work
Models of spectrum utilization
Spectrum interweave
Spectrum underlay
Spectrum overlay
In our work we consider spectrum underlay networks
Introduction Motivation Our Work Results Future Work
Models of spectrum utilization
Spectrum interweave
Spectrum underlay
Spectrum overlay
In our work we consider spectrum underlay networks
Introduction Motivation Our Work Results Future Work
Issues
Fast and Efficient Spectrum Sensing
Optimal Power Allocation Schemes
Security Issues for Primary Users
Medium Access Control
Introduction Motivation Our Work Results Future Work
Challenges in Spectrum underlay
Guarantee to primary users
Incentive for secondary users
Reasonable implementation complexity
Introduction Motivation Our Work Results Future Work
Outline
1 Introduction
2 Existing schemes in literature
3 Our Work
4 Numerical results
5 Future Work
Introduction Motivation Our Work Results Future Work
Notations used
I = {1, 2, . . . ,N} set of subcarriers
J = {1, 2, . . . ,M} set of primary users
Pi secondary user transmitter power in i th subcarrier
Ti is primary user transmitter power in i th subcarrier
Kj is the set of all subcarriers allocated to user j
Figure: Schematic representation of the OFDM channel
Introduction Motivation Our Work Results Future Work
Notations used(contd. . .)
Primary user rate Rpj =
∑i∈Kj
Rpji where
Rpji = log
(1 +
h11iTi
h12iPi + N0
)∀i ∈ Kj
Secondary user sum rate∑N
i=1 Rsi where
Rsi = log
(1 +
h22iPi
h21iTi + N0
)
21
22
12
11
Figure: Channel parameters
Introduction Motivation Our Work Results Future Work
Existing schemes in literature
No primary user protection
Interference power constraints
Primary user rate loss constraints
Introduction Motivation Our Work Results Future Work
No primary user protection
maximizeP
n∑i=1
Rsi
subject to
∑Ni=1 Pi
N≤ Pa
Pi ≥ 0 ∀ i ∈ I
Solution is a simple waterfilling scheme 1.
1[Tse and Viswanath(2005)]
Introduction Motivation Our Work Results Future Work
No primary user protection
maximizeP
n∑i=1
Rsi
subject to
∑Ni=1 Pi
N≤ Pa
Pi ≥ 0 ∀ i ∈ I
Solution is a simple waterfilling scheme 1.
1[Tse and Viswanath(2005)]
Introduction Motivation Our Work Results Future Work
Interference power constraints
maximizeP
n∑i=1
Rsi
subject to∑i∈Kj
h21iPi ≤ Γj ∀j ∈ J
∑Ni=1 Pi
N≤ Pa
Pi ≥ 0 ∀ i ∈ I
Keeps the interference to primary users down to a manageablelevel. 2
2[Wang et al.(2007)Wang, Zhao, Xiao, Zhou, and Wang]
Introduction Motivation Our Work Results Future Work
Interference power constraints
maximizeP
n∑i=1
Rsi
subject to∑i∈Kj
h21iPi ≤ Γj ∀j ∈ J
∑Ni=1 Pi
N≤ Pa
Pi ≥ 0 ∀ i ∈ I
Keeps the interference to primary users down to a manageablelevel. 2
2[Wang et al.(2007)Wang, Zhao, Xiao, Zhou, and Wang]
Introduction Motivation Our Work Results Future Work
Primary User Rate Loss constraints
maximizeP
n∑i=1
Rsi
subject to Rpj ≥ Rp0
j ∀j ∈ J∑Ni=1 Pi
N≤ Pa
Pi ≥ 0 ∀ i ∈ I
Leads to a higher secodary user rate when channel stateinformation is perfectly known 3.
3[Kang et al.(2010)Kang, Garg, Liang, and Zhang]
Introduction Motivation Our Work Results Future Work
Primary User Rate Loss constraints
maximizeP
n∑i=1
Rsi
subject to Rpj ≥ Rp0
j ∀j ∈ J∑Ni=1 Pi
N≤ Pa
Pi ≥ 0 ∀ i ∈ I
Leads to a higher secodary user rate when channel stateinformation is perfectly known 3.
3[Kang et al.(2010)Kang, Garg, Liang, and Zhang]
Introduction Motivation Our Work Results Future Work
Outline
1 Introduction
2 Existing schemes in literature
3 Our Work
4 Numerical results
5 Future Work
Introduction Motivation Our Work Results Future Work
Overview
Proposed Scheme 1: Based on sum rate constraint
Proposed Scheme 2: Based on sum utility rate constraint
Analysis and numerical results
Introduction Motivation Our Work Results Future Work
Scheme 1: Sum rate constraint
maximizeP
n∑i=1
Rsi
subject to∑j∈J
Rpj ≥
∑j∈J
Rp0j = δ
∑Ni=1 Pi
N≤ Pa
Pi ≥ 0 ∀ i ∈ I
Introduction Motivation Our Work Results Future Work
Comparison of Scheme 1 with rate loss constraint
Feasible region is larger:
So, Scheme 1 leads to a secondary user rate higher than thatwith rate loss constraints
Introduction Motivation Our Work Results Future Work
Comparison of Scheme 1 with rate loss constraint
Feasible region is larger:
So, Scheme 1 leads to a secondary user rate higher than thatwith rate loss constraints
Introduction Motivation Our Work Results Future Work
Primary User centric problem formulation
OPT1 : maximizeP
∑j∈J
Rpj
subject to∑i∈I
Rsi ≥ γ∑N
i=1 Pi
N≤ Pa
Pi ≥ 0 ∀ i ∈ I
OPT2 : maximizeP
∑i∈I
Rsi
subject to∑j∈J
Rpj ≥ δ∑N
i=1 Pi
N≤ Pa
Pi ≥ 0 ∀ i ∈ I
Lemma
OPT1 and OPT2 would have the same optimal point P0 if
(i) δ in OPT2 is the optimal value of OPT1
(ii) γ in OPT1 is the optimal value of OPT2
Introduction Motivation Our Work Results Future Work
Primary User centric problem formulation
OPT1 : maximizeP
∑j∈J
Rpj
subject to∑i∈I
Rsi ≥ γ∑N
i=1 Pi
N≤ Pa
Pi ≥ 0 ∀ i ∈ I
OPT2 : maximizeP
∑i∈I
Rsi
subject to∑j∈J
Rpj ≥ δ∑N
i=1 Pi
N≤ Pa
Pi ≥ 0 ∀ i ∈ I
Lemma
OPT1 and OPT2 would have the same optimal point P0 if
(i) δ in OPT2 is the optimal value of OPT1
(ii) γ in OPT1 is the optimal value of OPT2
Introduction Motivation Our Work Results Future Work
An outline of the proof
Follows by contradiction
Strict concavity of the secondary user sum rate
Rsi = log
(1 +
h22iPi
h21iTi + N0
)Primary user rate is a decreasing function of P
Rpji = log
(1 +
h11iTi
h12iPi + N0
)
Introduction Motivation Our Work Results Future Work
Problems with Scheme 1
Note
No guarantee on the minimum rate to a primary user
In fact, the primary user rate can go to zero.
Introduction Motivation Our Work Results Future Work
Problems with Scheme 1
Note
No guarantee on the minimum rate to a primary user
In fact, the primary user rate can go to zero.
Introduction Motivation Our Work Results Future Work
Scheme 2: A sum utility rate constraint
maximizeP
n∑i=1
Rsi
subject to∑j∈J
logRpj ≥
∑j∈J
logRp0j∑N
i=1 Pi
N≤ Pa
Pi ≥ 0 ∀ i ∈ I
where log(x) has been chosen to be the utility function.
Question
Does this scheme have a guarantee?
Introduction Motivation Our Work Results Future Work
Scheme 2: A sum utility rate constraint
maximizeP
n∑i=1
Rsi
subject to∑j∈J
logRpj ≥
∑j∈J
logRp0j∑N
i=1 Pi
N≤ Pa
Pi ≥ 0 ∀ i ∈ I
where log(x) has been chosen to be the utility function.
Question
Does this scheme have a guarantee?
Introduction Motivation Our Work Results Future Work
A trivial guarantee from this scheme
Lemma
There exists δ0 > 0 such that
Rpj > δ0 ∀j ∈ J
Proof.
We have∑
j∈J logRpj > δ
Power bounded implies each term bounded
logRpj > M (M > −∞)
δ0 = eM > 0
Introduction Motivation Our Work Results Future Work
Outline
1 Introduction
2 Existing schemes in literature
3 Our Work
4 Numerical results
5 Future Work
Introduction Motivation Our Work Results Future Work
Numerical Results
The following parameters reflect those used in a paper 4
N = 128 sub-carriers
4 PUs, 32 sub-carriers per user
Channel gains: h22 = 1, h12 = 0.1, h21 = 0.1, h11 varying
PU Transmit Power T = 10dB
Noise N0 = 1
4[Kang et al.(2010)Kang, Garg, Liang, and Zhang]
Introduction Motivation Our Work Results Future Work
Comparison of different schemes
−10 −5 0 5 10 15 200
0.5
1
1.5
2
2.5
3
Transmit Power Constraint, Pa(dB)
Tra
nsm
issio
n r
ate
of
SU
Inteference
Rate Loss
Scheme 1: Σ Rate
Scheme 2: Σ log(Rate)
Figure: Secondary User sum rate for different schemes.
Proposed schemes allow higher SU sum rate.
Introduction Motivation Our Work Results Future Work
PU Rate Protection
−10 −5 0 5 10 15 200
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Transmit Power Constraint, Pa(dB)
Min
imum
tra
nsm
issio
n r
ate
of P
Us
Scheme 1: Σ rate
Scheme 2: Σ log(rate)
Figure: Minimum primary user rate for two proposed schemes
Scheme 2 doesn’t allow any PU rate to go to zero
Introduction Motivation Our Work Results Future Work
Simulation results for two users
−10 −5 0 5 10 15 20 25 300
0.5
1
1.5
2
2.5
3
3.5
4
Transmit Power Constraint, Pa(dB)
Tra
nsm
issio
n r
ate
of
SU
Inteference
Rate Loss
Scheme 1: Σ Rate
Scheme 2: Σ log(Rate)
Figure: Optimal secondary user sum rate for 2 primary users
Introduction Motivation Our Work Results Future Work
Outline
1 Introduction
2 Existing schemes in literature
3 Our Work
4 Numerical results
5 Future Work
Introduction Motivation Our Work Results Future Work
Future Work
Analytical explanations for the observed simulationperformance
Implementation of a better optimization algorithm
Introduction Motivation Our Work Results Future Work
Acknowledgements
We would like to thank Dr. Ajit K. Chaturvedi for providing helpfulinsights and able guidance to our investigations.
Introduction Motivation Our Work Results Future Work
References I
X. Kang, H. Garg, Y.-C. Liang, and R. Zhang.Optimal power allocation for ofdm-based cognitive radio withnew primary transmission protection criteria.Wireless Communications, IEEE Transactions on, 9(6):2066–2075, 2010.ISSN 1536-1276.doi: 10.1109/TWC.2010.06.090912.
D. Tse and P. Viswanath.Fundamentals of wireless communication.Cambridge Univ Pr, 2005.ISBN 0521845270.
Introduction Motivation Our Work Results Future Work
References II
P. Wang, M. Zhao, L. Xiao, S. Zhou, and J. Wang.Power allocation in ofdm-based cognitive radio systems.In Global Telecommunications Conference, 2007. GLOBECOM’07. IEEE, pages 4061 –4065, 2007.doi: 10.1109/GLOCOM.2007.772.
Introduction Motivation Our Work Results Future Work
Questions?
Thank you for your attention.