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The Radio Environment Map

The Radio Environment Map. Sami Lunnamo. Presentation outline. Location and mobility. Definitions. WS availability. REM. Requirements. Design. Database. Layered REM. Challenges. REM - Definitions. Geolocation service And more Centralized database Radio environment data

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The Radio Environment Map

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  1. The Radio Environment Map Sami Lunnamo

  2. Presentation outline Location and mobility Definitions WS availability REM Requirements Design Database Layered REM Challenges

  3. REM - Definitions • Geolocation service • And more • Centralized database • Radio environment data • Predictions of spectrum opportunities • Cognition cycle

  4. REM – Definitions - Analogy • - Location (x, y, z) • Geographical location • Radio spectrum profile REM Tourist map of Beijing, source: http://images.chinatravel.com/city/beijing/beijing-city-map-large.jpg

  5. REM – Requirements • Normal CR requirements • Safety • Efficiency • Centralized service • Availability • Reliability • Throughput • Latency • Security

  6. REM – Challenges – Signal overhead • Communication between REM and CR • Amount of relevant data • Quality of connection • Balance between overhead and benefits of REM REM Clipart from bestclipartblog.com

  7. REM – Challenges - Validity • REM is collection of data • How long will any data be valid? • Information exchange between layers of REM

  8. REM – Challenges – Spectrum opportunities • Ability to detect and predict spectrum opportunity • Model-driven scheme to calculate opportunities • Loss-ratio can be close to 0% Nope, no free bands here Hey, I have data I’d like to send Bands REM

  9. REM – Challenges - Locations • Determining a location is error-prone and expensive • Could CRs use base station location as substitute for knowing own location accurately? • Mobile CRs • One-off events and wireless microphones

  10. REM – Challenges - Bootstrapping • New client • Connecting with REM through base station • Chicken-and-egg

  11. REM – Design – Spectrum opportunities • Model-driven schemes vs. Data-driven schemes • Longley-Rice (L-R) with terrain data • Climactic effects, soil conductivity, permettivity, Earth’s curvature and surface refractivity • 8% spectrum opportunity loss and even less false positives • In practice, no one model is sufficient alone

  12. REM – Design - Location • Different channels open in different areas • If using base station location, REM would have to use channels that are open and available in every part of the coverage area • 80% spectrum opportunity loss • Location granularity • 4km = 80% loss • 800m = ~0% additional loss • Bootstrapping beacon • Data of available channels

  13. REM – Design - Mobility • Mobile CRs location is constantly changing • CR might travel to an area where it uses a channel in use by PU • Old data about spectrum availability • Protection range for channels • Polling frequency for spectrum updates • 96 km/h, 60sec, 1.6km = 20% loss • 96 km/h, 30sec, 800m = 0% loss

  14. REM – Design – Database • What kind of data should the database contain? • TV transmitter data • Tower locations, antenna heights, transmit powers… • Client data • Locations, IDs, channels, transmit powers… • Cache

  15. REM – Design – Layered REM • Distributing and decentralizing • Layers • REM SA and REM Managers • Subsidiarity • Data stored and analysed in least centralized node possible • National – regional – local • Proportionality • Data with shorter life span needs to be readily available • REM SA and manager within quick reach

  16. REM - Summary • Geolocation service • Analysis and historical data of spectrum opportunities • Can detect and use ~92% of all spectrum opportunities in area • No false positives • Accommodates mobile CRs • Mobility doesn’t cause breach of safety requirement • Layered architecture gives robustness and eliminates overhead • Uses broadcast beacons to bootstrap new clients

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