Cognitive Radio Networks (CRnet) Research

Project Overview

Traditional static spectrum allocation policies have been to grant each wireless service exclusive usage of certain frequency bands, leaving several spectrum bands unlicensed for industrial, scientific and medical purposes. The tremendous growth in ubiquitous low-cost wireless applications that utilize the unlicensed spectrum bands has laid increasing stress on the limited and scarce radio spectrum resources.

Consequently, dynamic spectrum allocation has been proposed so that unlicensed spectrum users are allowed to use the underutilized licensed spectrum (or white space) conditional on the interference to the licensed user being below an acceptable level. The enabling technology behind the dynamic spectrum allocation is Cognitive Radio (CR). There are two prominent features of cognitive radio that, for simplicity, we call context-awareness and intelligence. Firstly, sensing task is performed across a wide range of spectrum to identify the white space. Secondly, opportunistic utilization of the white space.

Our Strategies

In addressing the various problems and issues as they are brought forward by the two aforementioned prominent features, we have defined a unique approach to tackle them. We recognised that achieving context-awareness and intelligence is of paramount important in ensuring the successful deployment of cognitive radio networks. Our unique and timely approach of integrating advanced machine learning and computational modeling techniques with cognitive radio research has brought about a paradigm shift in the way a cognitive radio device to operate efficiently for performance enhancement, rather than just being functional.

In the DSRG Group, we have built up expertise in the area of machine learning and wireless networking over the years, particularly data-link and network layers, while taking into account the impact of physical and higher layers. Hence, cognitive radio networks research has been rapidly expanding within the group.

People

Dr Peter Komisarczuk, Dr. Paul Teal, Kok-Lim Alvin Yau, and Yu Ren

Document

Overview of Cognitive Radio Research at Victoria University, August 2009 Source: New Zealand Ministry of Economic Development

Project Description

We are investigating the following areas:

1. Quality of Service (QoS) Architecture for Cognitive Radio Networks
2. Medium Access Control (MAC) Protocols for Cognitive Radio Networks
3. Context-Awareness in Cognitive Radio Networks
4. Application of Context-Awareness in Cognitive Radio Networks

Quality of Service (QoS) Architecture for Cognitive Radio Networks

A Cognitive Wireless Ad Hoc Network (CWAN) is a multihop self-organized and dynamic network that applies the cognitive radio technology. The research into Quality of Service (QoS) in CWAN is still in its infancy. To date, no attempt has been made to model a QoS architecture as a unified solution for CWAN. In this research, our objective is to materialise our novel QoS architecture called C2net for CWAN based on Next Steps in Signaling (NSIS). C2net provides service prioritization to different traffic types in the presence of nodal mobility and licensed users. The main objective is to provide stable QoS assurance to high priority flows. This is realized by a number of distributed and cross-layer features of C2net including topology management, congestion control, scheduling, and dynamic channel selection.

Related work:

1. Kok-Lim Alvin Yau, Peter Komisarczuk, and Paul D. Teal, "Quality of Service (QoS) Provisioning in Cognitive Wireless Ad Hoc Networks: Challenges, Design Approaches, and Open Issues", Quality of Service Architectures for Wireless Networks: Performance Metrics and Management, edited by Sasan Adibi, Raj Jain, Mostafa Tofigh, and Shyam Parekh (IGI Global, 2009).
2. Kok-Lim Alvin Yau, Peter Komisarczuk, and Paul D. Teal, "C2net: A Cross-Layer Quality of Service (QoS) Architecture for Cognitive Wireless Ad Hoc Networks," Australasian Telecommunication Networks and Applications Conference (ATNAC'08) IEEE, Adelaide, Australia, December 2008.

Medium Access Control (MAC) Protocols for Cognitive Radio Networks

For channel access between wireless nodes, a cognitive Medium Access Control (MAC) protocol is necessary to coordinate the cognitive radios. Multi-channel MAC protocol extensions have been proposed in IEEE802.11 to enable a node to operate in multiple channels in order to improve network-wide throughput. These multi-channel MAC protocols have several functions that can be leveraged by cognitive MAC protocols due to their similarities in certain aspects, though the cognitive radio has an additional requirement to cope with the existence of licensed users that have higher authority over the channels. In this project, we focus on possible technology leverage from multi-channel to cognitive MAC protocols.

Related work:

1. Kok-Lim Alvin Yau, Peter Komisarczuk, and Paul D. Teal, "A Survey on Multi-channel Medium Access Control (MAC) Protocols: A Cognitive Radio Perspective," New Zealand Computer Science Research Student Conference (NZCSRSC'09), Auckland, New Zealand, April 2009 .
2. Kok-Lim Alvin Yau, Peter Komisarczuk, and Paul D. Teal, "Medium Access Control (MAC) Protocols for Cognitive Radio Networks: Recent Advances and Design Considerations," New Zealand Computer Science Research Student Conference (NZCSRSC'09), Auckland, New Zealand, April 2009.
3. Kok-Lim Alvin Yau, Peter Komisarczuk, and Paul D. Teal, "On Multi-Channel MAC Protocols in Cognitive Radio Networks," Australasian Telecommunication Networks and Applications Conference (ATNAC'08) IEEE, Adelaide, Australia, December 2008.

Context-Awareness and Intelligence in Cognitive Radio Networks

To achieve context-awareness and intelligence in cognitive radio networks, there are two essential features that need to be catered for. Firstly, sensing task is performed across a wide range of spectrum to identify the white space. Secondly, opportunistic utilization of the white space. In this project, the approach to achieve context-awareness and intelligence is investigated. Using advanced techniques in machine learning, specifically Reinforcement Learning (RL), we are able to achieve the objective and improve the network performance.

Related work:

1. Kok-Lim Alvin Yau, Peter Komisarczuk, and Paul D. Teal, "Enhancing Network Performance in Distributed Cognitive Radio Networks Using Single-Agent and Multi-Agent Reinforcement Learning," to appear in 35th Conference on Local Computer Networks (LCN'10) IEEE, Denver, Colorado, USA, October 2010.
2. Kok-Lim Alvin Yau, Peter Komisarczuk, and Paul D. Teal, "Achieving Efficient and Optimal Joint Action in Distributed Cognitive Radio Networks using Payoff Propagation," General Symposium on Selected Areas in Communications, International Conference on Communications (ICC'10) IEEE, Cape Town, South Africa, May 2010.
3. Kok-Lim Alvin Yau, Peter Komisarczuk, and Paul D. Teal, "Context-Awareness and Intelligence in Distributed Cognitive Radio Networks: A Reinforcement Learning Approach," 11th Australian Communications Theory Workshop (AusCTW'10) IEEE, Canberra, Australia, February 2010.
4. Kok-Lim Alvin Yau, Peter Komisarczuk, and Paul D. Teal, "Learning Mechanisms for Achieving Context Awareness and Intelligence in Cognitive Radio Networks," Communications and Networking Research Group, School of Engineering and Computer Science, Victoria University of Wellington, New Zealand, February 2010 .
5. Kok-Lim Alvin Yau, Peter Komisarczuk, and Paul D. Teal, "Enhancing Network Performance in Distributed Cognitive Radio Networks using Single-Agent and Multi-Agent Reinforcement Learning," Communications and Networking Research Group, School of Engineering and Computer Science, Victoria University of Wellington, New Zealand, February 2010 .
6. Kok-Lim Alvin Yau, Peter Komisarczuk, and Paul D. Teal, "Achieving Context Awareness and Intelligence in Cognitive Radio Networks using Reinforcement Learning for Multi-state Applications," Communications and Networking Research Group, School of Engineering and Computer Science, Victoria University of Wellington, New Zealand, January 2010 .
7. Kok-Lim Alvin Yau, Peter Komisarczuk, and Paul D. Teal, "Performance Analysis of Reinforcement Learning for Achieving Context-Awareness and Intelligence in Cognitive Radio Networks," 9th IEEE International Workshop on Wireless Local Networks (WLN'09) at the 34th IEEE Conference on Local Computer Networks (LCN'09) IEEE, Zurich, Switzerland, October 2009. (Acceptance rate for Regular Paper = 11/35 = 31.43%)

Application of Context-Awareness and Intelligence in Cognitive Radio Networks

In this project, our well-researched context-awareness and intelligence technique is applied in various designs and schemes in cognitive radio networks in order to improve network performance. Various problems including dynamic channel selection, scheduling, and topology management are formulated using our context-awareness and intelligence approach that offers a simple and yet practical solution.

Related work:

1. Kok-Lim Alvin Yau, Peter Komisarczuk, and Paul D. Teal, "Applications of Reinforcement Learning to Cognitive Radio Networks," Workshop on Cognitive Radio Interfaces and Signal Processing at the International Conference on Communications (ICC'10) IEEE, Cape Town, South Africa, May 2010.
2. Kok-Lim Alvin Yau, Peter Komisarczuk, and Paul D. Teal, "Cognitive Radio-based Wireless Sensor Networks: Conceptual Design and Open Issues," 2nd IEEE International Workshop on Wireless and Internet Services (WISe'09) at the 34th IEEE Conference on Local Computer Networks (LCN'09) IEEE, Zurich, Switzerland, October 2009.
3. Kok-Lim Alvin Yau, Peter Komisarczuk, and Paul D. Teal, "A Context-aware and Intelligent Dynamic Channel Selection Scheme for Cognitive Radio Networks," Fourth International Conference on Cognitive Radio Oriented Wireless Networks and Communications (CROWNCOM'09) IEEE, Hannover, Germany, June 2009.

Peer-reviewed Publications

1. Kok-Lim Alvin Yau, Peter Komisarczuk, and Paul D. Teal, "Enhancing Network Performance in Distributed Cognitive Radio Networks Using Single-Agent and Multi-Agent Reinforcement Learning," to appear in 35th Conference on Local Computer Networks (LCN'10) IEEE, Denver, Colorado, USA, October 2010.
2. Kok-Lim Alvin Yau, Peter Komisarczuk, and Paul D. Teal, "Achieving Efficient and Optimal Joint Action in Distributed Cognitive Radio Networks using Payoff Propagation," General Symposium on Selected Areas in Communications, International Conference on Communications (ICC'10) IEEE, Cape Town, South Africa, May 2010.
3. Kok-Lim Alvin Yau, Peter Komisarczuk, and Paul D. Teal, "Applications of Reinforcement Learning to Cognitive Radio Networks," Workshop on Cognitive Radio Interfaces and Signal Processing at the International Conference on Communications (ICC'10) IEEE, Cape Town, South Africa, May 2010.
4. Kok-Lim Alvin Yau, Peter Komisarczuk, and Paul D. Teal, "Context-Awareness and Intelligence in Distributed Cognitive Radio Networks: A Reinforcement Learning Approach," 11th Australian Communications Theory Workshop (AusCTW'10) IEEE, Canberra, Australia, February 2010.
5. Kok-Lim Alvin Yau, Peter Komisarczuk, and Paul D. Teal, "Performance Analysis of Reinforcement Learning for Achieving Context-Awareness and Intelligence in Cognitive Radio Networks," 9th IEEE International Workshop on Wireless Local Networks (WLN'09) at the 34th IEEE Conference on Local Computer Networks (LCN'09) IEEE, Zurich, Switzerland, October 2009. (Acceptance rate for Regular Paper = 11/35 = 31.43%)
6. Kok-Lim Alvin Yau, Peter Komisarczuk, and Paul D. Teal, "Cognitive Radio-based Wireless Sensor Networks: Conceptual Design and Open Issues," 2nd IEEE International Workshop on Wireless and Internet Services (WISe'09) at the 34th IEEE Conference on Local Computer Networks (LCN'09) IEEE, Zurich, Switzerland, October 2009.
7. Kok-Lim Alvin Yau, Peter Komisarczuk, and Paul D. Teal, "Quality of Service (QoS) Provisioning in Cognitive Wireless Ad Hoc Networks: Challenges, Design Approaches, and Open Issues", Quality of Service Architectures for Wireless Networks: Performance Metrics and Management, edited by Sasan Adibi, Raj Jain, Mostafa Tofigh, and Shyam Parekh (IGI Global, 2009).
8. Kok-Lim Alvin Yau, Peter Komisarczuk, and Paul D. Teal, "A Context-aware and Intelligent Dynamic Channel Selection Scheme for Cognitive Radio Networks," 4th International Conference on Cognitive Radio Oriented Wireless Networks and Communications (CROWNCOM'09) IEEE, Hannover, Germany, June 2009.
9. Kok-Lim Alvin Yau, Peter Komisarczuk, and Paul D. Teal, "A Survey on Multi-channel Medium Access Control (MAC) Protocols: A Cognitive Radio Perspective," 7th New Zealand Computer Science Research Student Conference (NZCSRSC'09), Auckland, New Zealand, April 2009 .
10. Kok-Lim Alvin Yau, Peter Komisarczuk, and Paul D. Teal, "Medium Access Control (MAC) Protocols for Cognitive Radio Networks: Recent Advances and Design Considerations," 7th New Zealand Computer Science Research Student Conference (NZCSRSC'09), Auckland, New Zealand, April 2009 .
11. Kok-Lim Alvin Yau, Peter Komisarczuk, and Paul D. Teal, "C2net: A Cross-Layer Quality of Service (QoS) Architecture for Cognitive Wireless Ad Hoc Networks," Australasian Telecommunication Networks and Applications Conference (ATNAC'08) IEEE, Adelaide, Australia, December 2008.
12. Kok-Lim Alvin Yau, Peter Komisarczuk, and Paul D. Teal, "On Multi-Channel MAC Protocols in Cognitive Radio Networks," Australasian Telecommunication Networks and Applications Conference (ATNAC'08) IEEE, Adelaide, Australia, December 2008.

Technical Reports

1. Kok-Lim Alvin Yau, Peter Komisarczuk, and Paul D. Teal, "Learning Mechanisms for Achieving Context Awareness and Intelligence in Cognitive Radio Networks," Communications and Networking Research Group, School of Engineering and Computer Science, Victoria University of Wellington, New Zealand, February 2010 .
2. Kok-Lim Alvin Yau, Peter Komisarczuk, and Paul D. Teal, "Enhancing Network Performance in Distributed Cognitive Radio Networks using Single-Agent and Multi-Agent Reinforcement Learning," Communications and Networking Research Group, School of Engineering and Computer Science, Victoria University of Wellington, New Zealand, February 2010 .
3. Kok-Lim Alvin Yau, Peter Komisarczuk, and Paul D. Teal, "Achieving Context Awareness and Intelligence in Cognitive Radio Networks using Reinforcement Learning for Multi-state Applications," Communications and Networking Research Group, School of Engineering and Computer Science, Victoria University of Wellington, New Zealand, January 2010 .

Talks/Presentations

1. Peter Komisarczuk, "Performance Analysis of Reinforcement Learning for Achieving Context-Awareness and Intelligence in Cognitive Radio Networks," 9th IEEE International Workshop on Wireless Local Networks (WLN'09) at the 34th IEEE Conference on Local Computer Networks (LCN'09) IEEE, Zurich, Switzerland, 15:10-15:30, October 23, 2009.
2. Peter Komisarczuk, "Cognitive Radio-based Wireless Sensor Networks: Conceptual Design and Open Issues," 2nd IEEE International Workshop on Wireless and Internet Services (WISe'09) at the 34th IEEE Conference on Local Computer Networks (LCN'09) IEEE, Zurich, Switzerland, October 2009.
3. Kok-Lim Alvin Yau, "Context-Awareness and Intelligence in Cognitive Radio Networks: Design and Applications," IEEE NZ Central Section Postgraduate Presentation Event, Wellington, September 2009.
4. Peter Komisarczuk, "Developments in Cognitive Radio at Victoria University of Wellington," Seminar on Future Wireless Technologies, New Zealand Ministry of Economic Development, Wellington, August 2009.
5. Kok-Lim Alvin Yau, "Context-Awareness and Intelligence in Cognitive Radio Networks," Seminar on Future Wireless Technologies, New Zealand Ministry of Economic Development, Wellington, August 2009.
6. Kok-Lim Alvin Yau, "A Context-aware and Intelligent Dynamic Channel Selection Scheme for Cognitive Radio Networks," Fourth International Conference on Cognitive Radio Oriented Wireless Networks and Communications (CROWNCOM'09) IEEE, Hannover, Germany, June 2009.
7. Kok-Lim Alvin Yau, "Medium Access Control (MAC) Protocols for Cognitive Radio Networks: Recent Advances and Design Considerations," Session 4, New Zealand Computer Science Research Student Conference (NZCSRSC'09), Auckland, New Zealand, 13:50-15:30, April 8, 2009 .
8. Kok-Lim Alvin Yau, "A Survey on Multi-channel Medium Access Control (MAC) Protocols: A Cognitive Radio Perspective," Session 1, New Zealand Computer Science Research Student Conference (NZCSRSC'09), Auckland, New Zealand, 9:00-10:30, April 7, 2009 .
9. Kok-Lim Alvin Yau, "On Multi-Channel MAC Protocols in Cognitive Radio Networks", Technical Session T4c (Wireless Communications 4), Australasian Telecommunication Networks and Applications Conference (ATNAC'08) IEEE, Adelaide, Australia, 16:00-17:00, December 9, 2008.
10. Kok-Lim Alvin Yau, "C2net: A Cross-Layer Quality of Service (QoS) Architecture for Cognitive Wireless Ad Hoc Networks", Technical Session T4c (Wireless Communications 4), Australasian Telecommunication Networks and Applications Conference (ATNAC'08) IEEE, Adelaide, Australia, 16:00-17:00, December 9, 2008.
11. Kok-Lim Alvin Yau, "Quality of Service (QoS) Provisioning in Cognitive Radio Networks: Overview, Challenges, and Design Approaches," PGSA Colloquium, Wellington, October 2008.
12. Kok-Lim Alvin Yau, "Achieving Situation Awareness in Cognitive Radio Networks for Quality of Service Provisioning," IEEE (NZ) Wireless Workshop, Christchurch, September 2008.
13. Kok-Lim Alvin Yau, "Achieving Situation Awareness in Cognitive Radio Networks for Quality of Service Provisioning," IEEE NZ Central Section Postgraduate Presentation Event, Wellington, August 2008.

For more information, please contact Kok-Lim Alvin Yau