Radio Resource Management of Coexisting Multi-Radio Systems Month Year doc.: IEEE 802.11-yy/xxxxr0 July 2008 Radio Resource Management of Coexisting Multi-Radio Systems Date: 2008-7-14 Authors: Notice: This document has been prepared to assist IEEE 802.19. 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

Month Year doc.: IEEE 802.11-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

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

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

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

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

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

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

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

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

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

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

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

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