This document presents three channel assembling strategies - Immediate Blocking Strategy (IBS), Reassignment Based Strategy (RBS), and Queuing Based Strategy (QBS) - for cognitive radio networks handling multi-class secondary users. The strategies are evaluated based on their blocking and forced termination probabilities. Simulation results show that QBS outperforms RBS and IBS by demonstrating lower blocking and forced termination probabilities for multi-class secondary users. QBS is found to be a more robust approach by incorporating queuing and adaptive modulation and coding techniques to improve dynamic channel allocation in cognitive radio networks.

1. Africa – The Future Communications Galaxy
Performance Evaluation of Channel Assembling
Strategies with Multi-Class Secondary Users in
Cognitive Radio Networks
Ebenezer Esenogho and Tom Walingo
Centre for Radio Access and Rural Technologies.
Discipline of Electrical, Electronic and Computer
Engineering.
University Of KwaZulu-Natal.

2. OUTLINE
 INTRODUCTION
 Cognitive Radio.
 Cognitive Radio Network.
 Channel Assembling.
 CHANNELASSEMBLING STRATEGIES & RELATED WORK
 MOTIVATION
 SYSTEM MODEL/ARCHITECTURE
 ALGORITHMS
 RESULTS AND DISCUSSIONS
 CONCLUSION
 FUTURE WORK
2

3. INTRODUCTION
 Cognitive Radio.
 Cognitive Radio Network.
 Channel Assembling.
3

4. RELATED WORK AND PROPOSED CHANNELASSEMBLING
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
 Immediate Blocking Strategy (IBS)
 Reassignment Based Strategy (RBS)
 Queuing Based Strategy (QBS)
4

5. MOTIVATION
Realistic channel assembling (CA) strategies need :
 To consider different traffic class (real time and non-real time users)
 Consider the varying nature of a wireless link and mitigate schemes like
adaptive modulation and coding (AMC)
5

6. SYSTEM MODEL/ARCHITECTURE
Primary
User (TV)
class 0
Buffer
Primary
User (TV)
class 0
PU TV
mast
SU class 2
SU class 1
SU class 1
CRBS
SU class 2
Fig. 1 System Model/Architecture
6

7. CONT. WIRELESS CHANNEL MODELAND AMC
Fig. SNR Partitioning
Fig. 2 Wireless frame utilization
SNR Partitioning
Outage R2R1 R3
Bad Moderate Good
OFF
Frame
Duration
Ch 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)
7

8. CONT.
ON
(Buzy)
OFF
(Idle)
Fig. 4. The ON-OFF channel usage model for primary users
The PU’s slot capacity, 𝜃 𝑝𝑢, is given as
𝜃 𝑝𝑢 = 𝑆 𝑛.
𝑖=1
𝑀
𝑃𝑖
𝛽𝑖
𝛽𝑖 + 𝛼𝑖
(3)
Where 𝑃𝑖=
1, 𝑖 ≤ 𝜃𝑠𝑢 ≤ 𝑀 ∗ 𝑆
0, 𝑜𝑡ℎ𝑒𝑟𝑤𝑖𝑠𝑒
, Note that 𝛿𝑖 = 𝛽𝑖 𝛽𝑖 + 𝛼𝑖 is the channel
utilization ratio. The SU system capacity (slot capacity/OFF capacity) 𝜃𝑠𝑢 , is given
by
𝜃𝑠𝑢 = (𝑀 ∗ 𝑆 𝑛) − 𝜃 𝑝𝑢
8

9. ALGORITHM FOR IBS
• 𝐢𝐟 (𝜽 𝒔𝒖 ≥ 𝒊=𝟏
𝑲
𝜽𝒊 ); // test for 𝑆𝑈𝑖 resources
• 𝑺𝑼 𝟏_Admit = true; // admit 𝑆𝑈1
• Else
• 𝑺𝑼 𝟏_Admit =false; // block 𝑆𝑈1
• 𝐢𝐟 [(𝜽 𝒔𝒖 − 𝒊=𝟏
𝑲
𝜽𝒊 ) − (𝜽 𝒑𝒖)];// PU arrival, pre-empt 𝑆𝑈1
• 𝑺𝑼 𝟏_𝐝𝐫𝐨𝐩 = true; // forced terminate on − going 𝑆𝑈1
• 𝐢𝐟 (𝜽 𝒔𝒖 − 𝒊=𝟏
𝑲
𝜽𝒊 ≥ 𝒋=𝟏
𝑳
𝜽𝒋 ) ;// enough resources
• 𝑺𝑼 𝟐_Admit = true: // admit 𝑆𝑈2
• Else
• 𝑺𝑼 𝟐_Admit = false; // block 𝑆𝑈2
• 𝐢𝐟 [[(𝜽 𝒔𝒖 − 𝒊=𝟏
𝑲
𝜽𝒊 ) ≥ 𝒋=𝟏
𝑳
𝜽𝒋
𝒎𝒊𝒏
] − (𝜽 𝒑𝒖)]; // PU arrival, pre-empt 𝑆𝑈2
• 𝑺𝑼 𝟐_𝐝𝐫𝐨𝐩 = true; // dropp 𝑆𝑈2
• end if
• Go to start
9

10. ALGORITHM FOR RBS
• 𝐢𝐟 (𝜽 𝒔𝒖 ≥ 𝒊=𝟏
𝑲
𝜽𝒊
𝒎𝒊𝒏
); // test for 𝑆𝑈𝑖 resources
• 𝑺𝑼𝒊_Admit = true; // admit 𝑆𝑈𝑖
• else
•
𝐢𝐟 𝜽 𝒔𝒖 − 𝒊=𝟏
𝑲
𝜽𝒊
𝒎𝒊𝒏
) < 𝜽𝒊𝒏𝒆𝒘
𝒎𝒊𝒏
)
𝒐𝒓
𝜽 𝒔𝒖 − 𝒊=𝟏
𝑲
𝜽𝒊
𝒎𝒊𝒏
) − (𝜽 𝒑𝒖)
;// test for new arrival or PU arrival
• do 𝜽𝒋
𝒎𝒂𝒙
− 1 , ++ j: // adjusting and iterate over 𝑗 user resources
• 𝑺𝑼𝒊,𝒋_Admit = true: // admit 𝑆𝑈𝑖,𝑗
• Else
• 𝑺𝑼𝒊,𝒋_Admit = false; // block 𝑆𝑈𝑖,𝑗
• 𝐢𝐟 (𝜽 𝒔𝒖 − 𝒊=𝟏
𝑲
𝜽𝒊
𝒎𝒊𝒏
≥ 𝒋=𝟏
𝑳
𝜽𝒋
𝒎𝒊𝒏
); // test for 𝑆𝑈𝑗 resources
• 𝑺𝑼 𝟐_admit = true; // admit 𝑆𝑈2
• Else
• go step 6
• if all condition can not be meet
• 𝑺𝑼𝒊,𝒋_𝐭𝐞𝐫𝐦𝐢𝐧𝐚𝐭𝐞 = false; // dropp 𝑆𝑈𝑖,𝑗
• end if
10

11. ALGORITHM FOR QBS
• 𝐢𝐟 (𝜽 𝒔𝒖 ≥ 𝒊=𝟏
𝑲
𝜽𝒊 ); // test for 𝑆𝑈𝑠1 resources
• 𝑺𝑼 𝟏_admit = true; // admit 𝑆𝑈1
• else
• if ( 𝑲 𝒔𝒖𝟏 < 𝑄𝑠𝑢1)
• 𝑺𝑼 𝟏_admit_queue = true (queue not full)
• else
• 𝑺𝑼 𝒔𝟏_admit = false ;// queue full (block)
• 𝐢𝐟(𝜽 𝒔𝒖 − 𝒊=𝟏
𝑲
𝜽𝒊 ≥ 𝒋=𝟏
𝑳
𝜽𝒋); // enough resources
• 𝑺𝑼 𝒔𝟐_admit = true; // admit 𝑆𝑈𝑠2
• else
• if ( 𝑳 𝒔𝒖𝟐 < 𝑸 𝒔𝒖𝟐)
• 𝑺𝑼 𝟐_admit queue = true ;// (queue not full)
• else
• 𝑺𝑼 𝟐_admit = false ;// queue full (block)
• if ( 𝝏 𝒔𝒖𝟏 > 𝝏 𝒕 𝒔𝒖𝟏
)
• 𝑺𝑼 𝟏_drop queue = true
• if ( 𝝏 𝒔𝒖𝟐 > 𝝏 𝒕 𝒔𝒖𝟐
)
• 𝑺𝑼 𝟐_drop queue = true
• End if
11

12. RESULTS AND DISCUSSIONS
12

13. CONT.
13

14. CONCLUSION
• In this work, compared the performance of three channel assembling
techniques for cognitive radio network considering the dynamics of a
wireless link with AMC in a multiclass SU traffic.
• The result obtained from our simulation shows that; the QBS scheme
outperformed the RBS and IBS scheme amidst multiclass SUs in the sense
that, it shows lower blocking and force termination probabilities.
• It demonstrates that AMC with queueing technique is a robust approach in
improving dynamic channel allocation schemes.
14

15. Assembling many slots/channels irrespective of the channel state can affect
PER/BER especially in a dynamic wireless link. This forms the basis for our
future work.
FUTURE WORK
15

16. 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
 Indika A. M. Balapuwaduge, Lei Jiao, Frank Y. Li, and Vicent Pla
“Channel Assembling with Priority-Based Queue in Cognitive Radio
Network: Strategy and Performance” IEEE Transaction on wireless
Communication, vol.13, NO. 2, FEBUARY 2014, Pp.630-644
 Qingwen Liu, Shengli Zhou, and Georgios B. Giannakis, “Queuing With
Adaptive Modulation and Coding Over Wireless Links: Cross-Layer
Analysis and Design” IEEE Transactions On Wireless Communications,
vol. 4, no. 3, May 2005.pp.
16

17. THANK YOU
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