In pursuit of evolvable, sustainable, and submissive networks

Transcription

1 In pursuit of evolvable, sustainable, and submissive networks Luiz DaSilva Stokes Professor in Telecommunications Trinity College, University of Dublin Ireland

2 About CTVR. CTVR is a national centre for telecommunications research. It is head quartered in Trinity College but based in six institutions around Ireland Our mission is to carry out industry informed research in telecommunications to the highest of standards We work both in the optical and wireless domains

3 Other CSETs & SRCs architecture International Collaborations Visiting positions architecture Wireless Technologies Optical Technologies architecture FP7, Future Internet Programmes & Others Wireless & Optical Technologies Wireless & Optical Networks architecture Industry

4 evolvable: Elegant paths to future. Adaptive and flexible where it should be. Understanding of points of inflexibility. submissive: Not biased towards any one model of ownership. No un necessary rulesetting or resource labelling. sustainable: Persistent awareness of resource constraints e.g. man power, energy, bandwidth, processing power, space, storage etc.

5 interests fundamental principles that will allow the wireless network of the future to evolve into new architectures characterized by increasing autonomy and ubiquity of wireless services ability to learn decision making under partial information transient ownership of resources

6 Sustainable, evolvable, submissive: cognitive networks Cognitive networks perceive their environment, then decide, learn and act from the results, with network wide goals end-to-end goal end-to-end goal end-to-end goal CSL Requirements Layer Organization of wireless access networks, including spectrum management, and distributed adaptations by cognitive radios to meet end to end objectives Interaction between wireless access and wired networks, including assignment of users to access points, energy efficiency, flexibility to user mobility element status transfer element element goal goal element goal(s) element goal cognitive cognitive element element goal element goal(s) element element cognitive element SAN API cognitive element cognitive configurable configurable configurable Cognitive cognitive element element element element network network status status sensor sensor Cognitive Process Software Adaptable Network R. W. Thomas, D. H. Friend, L. A. DaSilva, and A. B. MacKenzie, Cognitive Networks: Adaptation and Learning to Achieve End to end Performance Objectives, IEEE Communications Magazine, Dec. 2006

7 Tools From cognitive radios to cognitive networks Spectrum etiquette for distributed channel selection Effects of imperfect network information on radio adaptations Small / large cell coexistence and resource management Analytical (game theory) + experimental Distributed coordination for heterogeneous networks (collaboration with UCC) Sensing and sharing in wireless access and multi hop networks Heterogeneous handover optimisation Transport protocols to handle mismatch at wireless/optical boundary Analytical (optimisation) + experimental

8 From Cognitive Radios to Cognitive Networks Current practice Resource management for cognitive radios acting in a network local adaptations (power, channel, ) local goals (max SINR, min BER, ) perfect information (can observe channel, neighbors actions) Extensions Local adaptations to meet endto end or network wide goals (throughput, network connectivity, ) Information available to adaptive radios is limited, due to cost of propagating network state information or inaccuracy in observing one s local environment

9 Coordination for heterogeneous and multi-hop networks Distributed spectrum sharing for multihop topologies and HetNets (relays, coexistence between small and large cells) Adaptations: channel selection, transmit power Goals: network wide spectrum efficiency, fairness, network connectivity, coverage Cooperative game theory, coalition formation Types of coalition in equilibrium as a function of link range Z. Khan, S. Glisic, L. A. DaSilva, and J. Lehtomaki, Modeling the Dynamics of Coalition Formation Games for Cooperative Spectrum Sharing in an Interference Channel, IEEE Trans. on Computational Intelligence and AI in Games, 2010 J. E. Suris, L. A. DaSilva, Z. Han, A. B. MacKenzie, and R. S. Komali, Asymptotic Optimality for Distributed Spectrum Sharing Using Bargaining Solutions, IEEE Trans. on Wireless Communications, Oct. 2009

10 Imperfect monitoring Impact of incomplete or erroneous information about channel or network conditions or neighbor activity on effectiveness of radio adaptations Framework is games of imperfect public/private monitoring Utility ftn: imperfect public monitoring Price of ignorance in topology control adaptations upon departure of one radio π is the expected utility pis the public signal Need to model the distribution of p, parameterized by the action vector a R. S. Komali, R. W. Thomas, L. A. DaSilva, and A. B. MacKenzie, The Price of Ignorance: Distributed Topology Control in Cognitive Networks, IEEE Trans. on Wireless Communications, April 2010

11 The potential for learning Learning is a part of the cognitive cycle: but when it is beneficial to apply machine learning? Relationship between effectiveness of learning and the amount of pattern that can be observed: Kolmogorov complexity Application to frequency agile radios Evaluation using spectrum measurements at CTVR and RWTH Aachen I. Macaluso, D. Finn, B. Ozgul, and L. DaSilva, Deciding When to Learn: Kolmogorov Complexity and Dynamic Channel Selection, under review, Probability of successfully selecting a channel, as a function of complexity in channel use patterns and primary user activity: ISM (top); GSM900 (bottom)

12 Bringing DSA to LTE/LTE+ HSS Diameter (RFC 3588) SAS GDB enb S1-MME MME S11 UE enb enb enb enb enb S1-U PDG (SGW+PGW) Internet enb S1-MME E-UTRAN S1-U cue cbs cbs cbs cbs cbs cran cbs cbs LTE Network Elements enb: Evolved Node B E-UTRAN: Evolved Universal Terrestrial Radio Access HSS: Home Subscriber Server MME: Mobility Management Entity PDG: Packet Data Gateway PGW: Packet Gateway SGW: Signaling Gateway SA Network Elements cbs: cognitive Base Station cran: cognitive Radio Access Network cue: cognitive User Equipment GDB: Geolocation Data Base SAS: Spectrum Accountability Server J. Deaton, R. Irwin, and L. DaSilva, The Effects of a Dynamic Spectrum Access Overlay in LTE+ Networks, IEEE DySPAN FRIDAY, 1:30 PM

13 Special Issue Cognitive Radio for LTE Advanced and Beyond Taking a broad view of cognitive radio that includes, but is not limited to, DSA Letter from the editors / white paper included with CFP Deadline: 30 June 20011

14 FP7 CREW Cognitive Radio Experimentation World ( )

15 CREW federation modes TUB IBBT/IMEC RELOCATE NODES & CREATE NEW COMBINATIONS STEP 2 REPLAY ONE BEHAVIOUR IN OTHER TESTBED TUD TCD STEP 1 CREW PORTAL MODE 1 CREW PORTAL MODE 2 CREW PORTAL MODE 3

16 CREW open call 20% of the budget for the CREW project is set aside to fund new partners who wish to perform experiments using the federated testbeds

17 FP7 COGEU COGnitive radio systems for efficient sharing of TV white spaces in EUropean context ( )

18 COG-EU objectives To design, implement and demonstrate enabling technologies based on cognitive radio to support mobile\portable applications over TVWS with protection of incumbent systems (DVB, PMSE wireless microphones) To investigate innovative business models and spectrum policies for TVWS exploitation based on secondary market regimes, to increase spectrum utilization enabling innovative wireless services COGEU aims to inform EU policy in relation to the enabling of efficient spectrum sharing and usage over TVWS at the European level. Architecture for using TVWS instantiates different business models

19 On the interwebs About CTVR About Luiz luizdasilva.wordpress.com On