1. Radio Resource Management of Coexisting Multi-Radio Systems
Month Year
doc.: IEEE yy/xxxxr0
July 2008
Radio Resource Management of Coexisting Multi-Radio Systems
Date:
Authors:
Notice: This document has been prepared to assist IEEE It is offered as a basis for discussion and is not binding on the contributing individual(s) or organization(s). The material in this document is subject to change in form and content after further study. The contributor(s) reserve(s) the right to add, amend or withdraw material contained herein.
KC Chen, National Taiwan University
John Doe, Some Company

2. Month Year
doc.: IEEE yy/xxxxr0
July 2008
Abstract
We introduce the fundamental benefits of cooperative relay by organizing cognitive radio nodes, and primary methodologies to facilitate radio resource management so that cooperation among co-existing wireless networks can support future wireless communications, in terms of tremendous number of nodes, high-bandwidth requirement, and smooth migration from legacy systems and devices.
KC Chen, National Taiwan University
John Doe, Some Company

3. Three Technology Directions for Co-Existing Multi-Radio Systems
July 2008
Three Technology Directions for Co-Existing Multi-Radio Systems
Cognitive and cooperative relay
Relying on terminal capability with software radio at physical layer to support multiple-radio systems and re-configurable networking capability
Inter-system handover
Realizing terminal access selection and mobility management among candidate systems and personal networks
Joint radio resource allocation
Joint optimization among systems
All OFDMA
OFDMA, CDMA, and others
KC Chen, National Taiwan University

4. July 2008
Illustration of a generalized cooperative relay from source to destination
KC Chen, National Taiwan University

5. Self-organized Cognitive Radio Terminal Device Architecture
July 2008
Self-organized Cognitive Radio Terminal Device Architecture
KC Chen, National Taiwan University

6. Cognitive and Cooperative Relay
July 2008
Cognitive and Cooperative Relay
Following network coding study to develop the algorithms, cognitive and
cooperative relay can increase 130% more throughput per bandwidth
with 92% useful, in randomly generated network topology.
KC Chen, National Taiwan University

7. Inter-System Handover
July 2008
Inter-System Handover
A gateway (GW) entity can be introduced as an anchor point for inter-system communication and that provides the interface (IG) to the Internet and communicates with external routing functional entities.
GWs connect different RANs and the RANs will be considered as the elements of the whole communication networks.
A base station (BS) would perform almost all radio related functions for the active terminals (i.e., terminals sending data) and would be responsible for governing radio transmission to and reception from the terminal and relay nodes (RNs) in one or more cells. The BS is in control of relays (if used) and determines routes, forwards packets to the respective relay and takes care of flow control for the relays to ensure that they can forward the data to their associated terminals.
KC Chen, National Taiwan University

8. Scenario for inter-system mobility management including a 4G system
July 2008
Scenario for inter-system mobility management including a 4G system
BS is in control of relays (if used)
and determines routes,
forwards packets to
the respective relay
KC Chen, National Taiwan University

9. Realization of inter-system inter-working in a 4G scenario
July 2008
Realization of inter-system inter-working in a 4G scenario
Specific RRM (SRRM)
is the entity in charge of
adapting the RANs
to the cooperation.
KC Chen, National Taiwan University

10. GW pools for support of mobility management in a 4G scenario
July 2008
GW pools for support of mobility management in a 4G scenario
The pool of GWs
decouples the physical
relation between a unique
GW and a number
of BS associated.
KC Chen, National Taiwan University

11. Cooperative Joint radio resource allocation
July 2008
Cooperative Joint radio resource allocation
An even more aggressive scenario is to have a fully “integrated” system network architecture
to allow joint radio resource allocation among different systems
to approach ultimate radio resource utilization
in terms of frequency/sub-carrier, time, code, spatial/antenna in MIMO
Execution in 3 steps via mathematical optimization
Spectrum re-farming
allocating a pre-determined frequency band B among those N cells to maximize total network capacity according to demands
Spectrum (and power) allocation in each cell
Cross-layer resource allocation among co-existing systems
KC Chen, National Taiwan University

12. July 2008
Numerical Result of Capacity Improvement by Cross-Layer Resource Allocation
KC Chen, National Taiwan University

13. July 2008
Concluding Remarks
We suggest 3 technical directions toward co-existence of multi-radio systems
Cognitive radio terminal
Inter-system handover
Joint radio resource allocation
Easy to upgrade from legacy devices and systems
International standardization efforts would be helpful to facilitate ideas of enhancing spectrum efficiency
KC Chen, National Taiwan University

14. July 2008
References
K.C. Chen, L.H. Kung, David Shiung, R. Prasad, S. Chen, “Self-Organizing Terminal Architecture for Cognitive Radio Networks”, Wireless Personal Multimedia Communications Conference, Jaipur, India, Dec. 3-6, 2007.
K.C. Chen, Y.J. Peng, N. Prasad, Sumei Sun, Y.C. Liang, “Cognitive Radio Network Architecture: Part I – General Structure”, Proceeding of ACM International Conference on Ubiquitous Information Management and Communication, Seoul, 2008.
Chu-Hsiang Huang, Yen-Chieh Lai, Kwang-Cheng Chen, “Network Capacity of Cognitive Radio Relay Network”, to appear in PhyCom, 2008.
E. Tragos, A. Mihovska, E. Mino-Diaz, P. Karamolegkos, “Access Selection and Mobility Management in a Beyond 3G RAN: The WINNER Approach”, ACM MobiWac, 2007.
Feng Seng Chu, Kwang-Cheng Chen, “Radio Resource Allocation for Mobile MIMO-OFDMA,” IEEE Vehicular Technology Conference - Spring, Singapore, 2008.
Acknowledgement:
This research is supported in part by the European research projects WINNER II and MAGNET Beyond, and by the research projects sponsored by National Science Council and Ministry of Economic Affairs, Taiwan ROC.
KC Chen, National Taiwan University