1. Ayon Chakraborty and Samir R. Das WINGS Lab
Designing a Cloud-Based Infrastructure for Spectrum Sensing: A Case Study for Indoor Spaces
Ayon Chakraborty and Samir R. Das
WINGS Lab
IEEE DCOSS 2016

2. Mobile Data Demand Skyrockets
Capacity Bottleneck
Demand > 3X Capacity!
Before we delve deeper into the spectrum sensing infrastructure I will try to point out the importance of wireless spectrum. The plot shows a timeline of average mobile broadband demand and capacity.
If you look carefully, by 2016 the demand has already surpassed thrice the capacity. In this situation capacity becomes a bottleneck. In particular wireless network capacity.
Mobile Broadband: Average Demand Per User Versus Average Capacity Per User
Ref: Rysavy Research
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3. Managing Network Capacity
Capacity Bottleneck
Solutions
More Cell Sites
Improve Backhaul / Core
Now lets look at ways that address such capacity problems.
The first one is by having more cell sites. Describe each. Mention LTE Shannon limit etc.
We will focus on ways that help to find more spectrum or share spectrum resources.
Better Utilize Spectrum
Improve Spectral Efficiency
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4. Better Utilize Spectrum (e.g. White Space Channels)
Available TV White Space
RSS Threshold
6MHz channels
FCC opened up this spectrum band for unlicensed use in 2008.
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5. Finding Available White Spaces
Freq1
Freq.
White Space 1
Available? 2
Approach 1: Estimate pathloss at (X, Y) using Propagation Models.
Freq2
Approach 2: Take spectrum measurements at (X, Y).
Location: (X, Y)
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6. Lost White Space: Causes
Propagation models perform poorly indoors and in urban canyon environments.
Sometimes too complicated to use indoor models extensively and at scale.
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7. More White Space is Lost Indoors
Most people are indoors 80% of the time and 70% of the spectrum demand comes from indoor locations.
Propagation model based techniques seems to lose ≈ 70% of the available white space. [Mobicom’13, CoNEXT’14].
Need for fine-grained spatio-temporal spectrum awareness through intelligent spectrum sensing.
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8. SpecSense System Scan Spectrum Server Sensing Scheduler
Messaging Broker
Data Handler
Measurements
Spectrum Database
Analytics Engine
Mobile Spectrum Sensors
Spectrum Database
Web Dashboard
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9. Mobile Spectrum Sensors
Samsung Galaxy S6 Phone
Raspberry-Pi Platform
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10. SpecSense Messaging System: MQTT
Useful when:
Connectivity is intermittent.
Bandwidth is at a premium. Lighter headers.
Interact with one or more phone apps.
Phone / tablet apps need to send data reliably without requiring code retry logic.
Saves > 4% battery per day over HTTP to maintain an open stable connection.
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11. SpecSense Web Dashboard
Live at
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12. Indoor Usecase: Channel Selection
WS Ch. #1
WS Ch. #2
Which Channel to Use?
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13. AP-only Sensing. Poorer REM.
REM: Radio Environment Map
Ch. #1 available
Ch. #2 available
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14. Client-based Sensing Improves REM
Ch. #1 NOT available
Ch. #2 NOT available
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15. More Sensors Reduce Estimation Error
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16. Impacts Performance
Estimation error in the REM leads to erroneous channel selection impacting performance.
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17. Summary
A good amount of wireless spectrum resources are lost due to inefficiencies in signal detection.
We built an end-to-end distributed spectrum sensing system to make signal detection more reliable.
Using our system we demonstrate how a better channel can be selected by employing spectrum sensing capabilities in client devices.
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18. Thanks! Interested about the SpecSense system? Measurement Data
Deploy your own setup
Develop SpecSense APIs
Contact:
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