J. Scott Marcus, WIK-Consult GmbH

1. Inventory and review of spectrum use:Assessment of the EU potential for improving spectrum efficiency J. Scott Marcus, WIK-Consult GmbH Presentation to RSPG #27 29 February 2012

2. Overview of Presentation • Objectives and scope of the project • An exploratory effort • Issues for consideration • A Decision Support System (DSS) • Data gathering and measures of efficiency • Data and the relationship to EFIS • Study schedule

3. Objectives of the project Gather detailed information on current spectrum use in EU Member States Define and analyse efficiency using technical, economic, social and any other relevant criteria Identify candidates for improved efficiency Conduct two stakeholder workshops

4. Scope of the study • All Member States • Frequencies • 400 MHz to 6 GHz in detail. • Selected bands elsewhere (e.g. PPDR/TETRA) • Other frequencies only at a high level.

5. An exploratory effort • We view our task as a prototype effort for the eventual spectrum inventory. • Determine what data is useful. • Determine what data is reasonably available. • Experiment with different efficiency measures. • Experiment with different ways to analyse data. • Experiment with different ways to organise data. • What works? • What does not work?

6. Issues for consideration • It is important to distinguish among: • The process used to identify candidates for enhanced efficiency or effectiveness; • The specific metrics that could be gathered and used to measure spectrum efficiency; • The measures that could be taken to enhance efficiency or effectiveness.

7. Issues for consideration • Is optimization of spectrum allocation, assignment and use at European level: • A fully structured problem (where all relationships can be identified and understood in advance, and where a computer could in principle derive an ideal answer)? • A totally unstructured problem (where relationships are totally unknown and unknowable)? • A semi-structured problem?

8. Issues for consideration • In a semi-structured problem, many relationships can be identified in advance, and many can be fully understood, but not all. • This implies that there is no realistic prospect of a fully automated solution for determination of the optimal result. • There is, however, a potential role for Decision Support Systems (DSS) to provide automated assistance to human planners.

9. Decision Support System • A Decision Support Systems (DSS) is an aid to the decision-maker. • It provides automated assistance. • It does not substitute for human judgment.

10. Decision Support System • The inventory can thus be thought of as a DSS that attempts: • to help the analyst to identify candidate bands and geographies for improvement, and • to further assist the analyst in evaluating likely costs and benefits. • This implies the need for: • Data storage and management; • Graphical tools to identify clusters and trends; • Aids to analysis.

11. Gather detailed information • GOAL: Collect and analyse data on the current use of spectrum in the EU and relevant non-EU countries • Information comes from: • desk research: EFIS, NFATs, frequency registers • interviews with stakeholders including SMAs • input from the first public workshop • the RSPG • The data and information collected serves as: • an output in itself (prototype inventory) • the basis for the efficiency analysis and development of recommendations for potential efficiency improvement

12. Spectrum Efficiency • There are different forms of efficiency: • Technical efficiency • Economic efficiency • Social efficiency • No single metric can fully capture efficiency in any of these dimensions. • Measures of efficiency help identify candidates for improvement.

13. Data and the relationship to EFIS • The long term relationship to EFIS is not explicit in our terms of reference, but it emerged as a crucial issue in our study. • Our data gathering task requires not only information about allocations, assignments, and rights, but also usage. • EFIS is a good source for some data, but not all. • EFIS level 1/2/3 terminology is not well suited to our analytical needs.

14. Data and the relationship to EFIS • For data that is available in EFIS, or that could be made available, it is vitally important to avoid wasteful, duplicate update processes.

15. A possible realisation Updates National SMAs EFIS Spectrum Inventory DSS Other Data Sources

16. A possible realisation • This approach seeks to ensure that anything that can be maintained in EFIS is updated through the normal mechanisms. • It segregates EFIS data management from the analytic tools that would use EFIS data (and also data from other sources). • The approach is based entirely on existing, proven methods and procedures.

17. Study Schedule Oct Nov Dec Jan Feb Mar Apr May Jun Jul Information gathering Develop prototype data gathering and analysis Define efficiency Analyse efficiency Identify potential improvements Final Workshop First Workshop Liaison with RSPG Final Report Interim Report

18. Stakeholder Workshops • Stakeholder workshop to present the Interim Report (Brussels, 10 May 2012) • Present preliminary findings • Solicit feedback for subsequent work • Stakeholder workshop to present the Final Report (Brussels, 6 July 2012)

19. Contact Points for the Study • J. Scott Marcus, WIK-Consult (Project Manager) • S.Marcus@WIK.ORG] • John Burns, Aegis Systems (Technical) • John.burns@aegis-systems.co.uk • Phillipa Marks, Plum Consulting (Economics) • Phillipa.marks@plumconsulting.co.uk • Frederic Pujol, IDATE (Data Gathering) • F.pujol@idate.org