Evaluation of Channel Assembling Strategies with Single-Class Users in Cognitive Radio
Networks
Ebenezer Esenogho
Supervised by Dr. Tom Walingo
Discipline of Electrical, Electronic and Computer Engineering.
University Of KwaZulu-Natal.
Centre for Radio Access and Rural Technologies
OUTLINE
INTRODUCTION Cognitive Radio. Cognitive Radio Network. Channel Assembling. CHANNEL ASSEMBLING STRATEGIES & RELATED WORK MOTIVATION SYSTEM MODEL/ARCHITECTURE ALGORITHMS RESULTS AND DISCUSSIONS CONCLUSION FUTURE WORK
INTRODUCTION
Cognitive Radio. Cognitive Radio Network. Channel Assembling.
RELATED WORK AND PROPOSED CHANNEL ASSEMBLING STRATEGIES
RELATED WORK Lei Jiao, Frank Y. Li, and Vicent Pla “Dynamic Channel Aggregation
Strategies in Cognitive Radio Networks with Spectrum Adaptation” IEEE Globecom 2011 proceedings. 2011 pp.1-6 (Static and Dynamic)
Proposed Channel Assembling Strategies vs No- Assembling (NA)
Immediate Blocking Strategy (IBS) Reassignment Based Strategy (RBS)
MOTIVATION
Channel assembling (CA) strategies to : Consider the varying nature of a wireless link and mitigate schemes like
adaptive modulation and coding (AMC) Consider homogeneous traffic class (real time or non-real time users)
SYSTEM MODEL FOR HOMOGENEOUS USERS
Fig. 1 Network Model/Architecture (FCFS -Regime)
Primary User (TV)
Primary User (TV)
PU TV mast
Secodary User
Secodary User
CRBS
Secodary User
Primary User (TV)
class 0
Primary User (TV)
class 0
PU TV mast
SU class 1
SU class 1
CRBS
SU class 1
SU class 1
WIRELESS CHANNEL MODEL AND AMC
SNR Partitioning
Outage R2R1 R3
Bad Moderate Good
Fig.2 SNR Partitioning
OFF Frame
DurationCh 1/ PU1
Ch 1/ PU2
Ch 1/ PU3
Ch 1/ PU1
:::::::::
Ch M/PU M
PU ON PU OFF
Slo1………………………………………………………...S
ON frame OFF frame (Tf)
Fig. 3 Wireless frame utilization
CONT.
Fig. 4. The ON-OFF channel usage model for primary users
The PU’s slot capacity, is given as
Where, Note that is the channel utilization ratio. The SU system capacity (slot capacity/OFF capacity) is given by
ON(Buzy)
OFF(Idle)
ALGORITHM FOR IBS
• CRBs check wireless link ; % cognitive radio base station checks wireless link state (SNR)
• CRBs check ; % cognitive radio base station checks available recourse for SUs
• ; % test for resources
• Admit = true; % admit , but first by the principle of FCFS and assemble with a probability
• else
• Admit =false; % block due to insufficiently resources.
• % PU arrival, pre-empt (no-spectrum adaptation)
• = true; % f
• end if % terminates if no events
• Go to start % repeat the process
ALGORITHM FOR RBS
• CRBs check wireless link ; % cognitive radio base station checks wireless link state (SNR)
• CRBs check ; % cognitive radio base station checks available recourse for SUs
• ; % test for resources
• Admit = true; % admit
• else• % test for new arrival or PU arrival
• do ++ j: % adjusting and iterate over user resources • Admit = true; % admit and assemble for both users
• Else • Admit = false; % b since no free channel-slot or insufficient • Else• if all condition can not be meet• = true; % d • end if ; %start the process
RESULTS AND DISCUSSIONS
SU service rate0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6
Bloc
king
Pro
babi
lity
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
NAIBS StrategyRBS Strategy
0.04 0.06 0.08 0.1 0.12 0.14 0.16 0.18 0.210
-3
10-2
10-1
100
PU arrival rate
SU
Blo
ckin
g P
roba
bilit
y
NAIBSRBS
PU arrival0 0.2 0.4 0.6 0.8 1 1.2 1.4
SU Th
rough
put
0
0.5
1
1.5
2
2.5
3
RBSIBSNA
0 0.2 0.4 0.6 0.8 10
0.5
1
1.5
2
2.5
SU service rate
SU
Thr
ough
put
NA
IBS
RBS
=1.4, =0.2=0.3=0.9
CONT.
0 0.2 0.4 0.6 0.8 10.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
2
2.2
SU service rate
SU
cap
acity
NAIBSRBS
0 5 10 15 200
0.5
1
1.5
2
2.5
SU SNR [dB]
SU
Cap
acity
NA
IBSRBS
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.810
-2
10-1
100
101
PU arrival
SU
For
ced
term
inat
ion
prob
abilit
y
IBSNARBS
SU service rate0 1 2 3 4 5 6 7
SU F
orce
d te
rmina
tion
Prob
abilit
y
0.15
0.2
0.25
0.3
0.35
0.4
0.45
0.50.55
0.60.65
NARBS StrategyIBS Strategy
CONCLUSION
• In this work, compared the performance of two channel assembling strategies with No-Assembling for cognitive radio network considering the dynamics of a wireless link with AMC in a single-class SU traffic.
• The result obtained from our simulation shows that; the RBS scheme outperformed the IBS and NA scheme amidst homogeneous SU class in the sense that, lower blocking and force termination probabilities are observed.
• It demonstrates that AMC with CA is a robust approach in improving dynamic channel allocation schemes.
FUTURE WORK
Our future work will be focus in two folds: • The selection of a traffic type from a SU with two traffic running
simultaneously. • The affect PER/BER especially in a dynamic wireless link. • Integrating queuing discipline into the proposed policies
MAIN REFERENCES
Lei Jiao, Frank Y. Li, and Vicent Pla “Dynamic Channel Aggregation Strategies in Cognitive Radio Networks with Spectrum Adaptation” IEEE Globecom 2011 proceedings. 2011 pp.1-6
L. Jiao, F. Y. Li, and V. Pla, “Modelling and performance analysis of channel assembling in multi-channel cognitive radio networks with spectrum adaptation,” IEEE Trans. Veh. Technol., vol. 61, no. 6, pp.2686–2697, July 2012
THANK YOU
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