distributed spectrum occupancy measurements in the 0.15...

Institute of Industrial Information TechnologyProf. Dr.-Ing. habil. Klaus Dostert

Distributed Spectrum Occupancy Measurements in the0.15 - 10 MHz Band for LV PLC Networks9th Workshop on Power Line Communications | September 22, 2015Nico Otterbach

KIT – University of the State of Baden-Wuerttemberg and

National Laboratory of the Helmholtz Association

www.kit.edu

http://www.kit.edu

Motivation

(Usable) spectrum is a limitedressource

Idea: Dynamic Access⇒ Problem: Avoid interference

Source: brunel.ac.uk

ChallengesCo-existence with wireless systems⇒ Primary User (PU) Detection

Detect low noise frequency sections

Determine spectrum occupancy (noise & PUs)

=⇒ Dynamic Spectrum Access for Cognitive PLC systems

2/21 Distributed Spectrum Occupancy Measurements in the 0.15 - 10 MHz Band for LV PLC NetworksNico Otterbach

Institute of IndustrialInformation Technology

Service Survey

f / MHz1 2 3 4 5 6 7 8 9 100

civil and military broadcasting services

Civil services⇒ Broadcasting services

Military services

Combined services

(Various noise sources)

=⇒ Focus on broadcasting services



Outline

1. Motivation

2. Spectrum Estimation Method

3. Measurement SetupAutomated Measurement SystemCampaign Description

4. AnalysisLocation DiversityTime DiversityTime-Frequency AnalysisWired vs. Wireless

5. Summary



Outline

1. Motivation




5. Summary



Spectrum Estimation Method

Energy Detection (ED) as promising approach for PLC systems⇒ Oberservations of the Power Spectral Density (PSD)

Welch’s methodAveraged periodogramsOverlapped blocks of samples

⇒ Consistent estimation⇒ Analysis of stationary random processes

Short-time analysis based on the Short-Time Fourier Transform (STFT)⇒ Basic cyclostationary analysis

=⇒ PSD as rough estimation of occupied spectrum (PUs & noise)



Spectrum Estimation Parameters

PSD parameters

Parameter ValueSample rate 25 MS/s (real-valued)

Number of samples 2,500,000 (5 mains periods)FFT size 4096 (∆f ≈ 6 kHz)Window HanningOverlap 50 %

STFT parameters

Parameter ValueSample rate 25 MS/s (real-valued)

Number of samples 1,000,000 (2 mains periods)DFT size 5000 (∆f = 5 kHz)Window HanningOverlap 50 %

∆t 200 µs



Outline

1. Motivation




5. Summary



Automated Measurement System (AMS)

Live-USB Image

Based on SSH⇒ (W-)LAN, 3G/4G, VPN

Central repository

Central control unit

2 time modes (GPS,system time)

Modular design (GNURadio flowgraphs)

⇒ Uniform, automated measurement procedure

⇒ Systematic planning, „offline“ design

⇒ Reduced error probability

⇒ Consistent filing of measurement parameters, results and raw data



Campaign Description

RequirementsMultiple locationsSynchronous measurementsCentral control and monitoringUniform data structureWired/Wireless measurements

Source: google.com

Campaign detailsAll measurements taken at June 11th & 12th in Karlsruhe, Germany

4 Locations: Transformer station, garage, cellar & apartment building

24 hours observation: Every 15 minutes 5 seconds of raw data at 25 MS/s

Additionally 5 minutes of raw data every 6 hours at each location



Outline

1. Motivation




5. Summary



Location Diversity

0.0Hz 2.0 MHz 4.0 MHz 6.0 MHz 8.0 MHz 10.0 MHzFrequency

−160

−140

−120

−100

−80

Sca

led

PS

D[V

2/

Hz]

apartment building

garage

cellar

transformer station

−160 −140 −120 −100 −80

Scaled PSD [V2/Hz]

0.00.20.40.60.81.01.21.41.6

Rel

ati

vefr

equ

ency

[%]

garage

apartment building

cellar

transformer station



Location Diversity

0.0Hz 200.0 kHz 400.0 kHz 600.0 kHz 800.0 kHz 1.0 MHzFrequency

−150

−140

−130

−120

−110

−100

−90

−80

−70

Sca

led

PS

D[V

2/

Hz]

apartment building

cellar

transformer station

=⇒ Common features, but highly location-dependent



Time Diversity – Garage, Cellar

PSD

Histogram

Garage Cellar



Time Diversity – Transformer, Apartment

PSD

Histogram

Transformer station Apartment building



STFT Analysis – Garage, Transformer

Garage

5.0 ms 10.0 ms 15.0 ms 20.0 ms 25.0 ms 30.0 ms 35.0 msTime

0.0Hz

2.0 MHz

4.0 MHz

6.0 MHz

8.0 MHz

10.0 MHz

Fre

qu

ency

−195

−180

−165

−150

−135

−120

−105

−90

−75

Sca

led

PS

D[d

BV

2/

Hz]


0.0Hz

2.0 MHz

4.0 MHz

6.0 MHz

8.0 MHz

10.0 MHz

Fre

qu

ency

−195

−180

−165

−150

−135

−120

−105

−90

−75

Sca

led

PS

D[d

BV

2/

Hz]

Transformer station


0.0Hz

2.0 MHz

4.0 MHz

6.0 MHz

8.0 MHz

10.0 MHz

Fre

qu

ency

−200

−180

−160

−140

−120

−100

−80

−60

Sca

led

PS

D[d

BV

2/

Hz]


0.0Hz

2.0 MHz

4.0 MHz

6.0 MHz

8.0 MHz

10.0 MHz

Fre

qu

ency

−200

−180

−160

−140

−120

−100

−80

−60

Sca

led

PS

D[d

BV

2/

Hz]

06/12 03:15 06/12 15:15



Wired vs. Wireless – PSD

0.0Hz 2.0 MHz 4.0 MHz 6.0 MHz 8.0 MHz 10.0 MHzFrequency

−150

−140

−130

−120

−110

−100

Sca

led

PS

D[V

2/

Hz]

Power Line

Air

−150 −140 −130 −120 −110 −100

Scaled PSD [V2/Hz]

0.0

0.5

1.0

1.5

2.0

Rel

ati

vefr

equ

ency

[%]

Power Line

Air



Wired vs. Wireless – Time Diversity

STFT


0.0Hz

2.0 MHz

4.0 MHz

6.0 MHz

8.0 MHz

10.0 MHz

Fre

qu

ency

−210

−195

−180

−165

−150

−135

−120

−105

Sca

led

PS

D[d

BV

2/

Hz]


0.0Hz

2.0 MHz

4.0 MHz

6.0 MHz

8.0 MHz

10.0 MHz

Fre

qu

ency

−195

−180

−165

−150

−135

−120

−105

Sca

led

PS

D[d

BV

2/

Hz]

06/12 03:15 06/12 15:15PSD & Histogram



Outline

1. Motivation




5. Summary



Summary & Outlook

Basic Observations towards spectrum sensing & occupancy estimation

Novel, Software-Defined Radio based Automated Measurement System

Spectrum occupancy is highly dependent on the location⇒ Distributed, cooperative spectrum sensing

Spectrum occupancy is highly dependent on the (day) time⇒ Application of machine learning algorithms

(Centralized) Wireless measurements to enhance PU detection accuracy

Analysis still work in progress⇒ More sophisticated detection algorithms⇒ Dedicated detection of Primary User signals⇒ Occupancy evaluation divided into noise/PUs⇒ Define (frequency-dependent) occupancy levels/spectrum masks⇒ Duty cycle models

⇒ Distributed, adaptive sensing for DSA/Cognitve PLC systems



Questions?

Thank you for your attention!



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