Measurements of digital signals with spectrum analyzers Thomas

Types of available Spectrum Analyzers n Sweeping Analyzer n n Scans the desired frequency

Sweeping Analyzer: Principle in Theory n Filter is swept through the desired frequency range

Sweeping Analyzer: Realization of Principle n IF signal is swept through fixed frequency filter

Sweeping Analyzer: Simplified Block Diagram Detector Reference level Input Mixer IF Amp. IF Filter

Sweeping Analyzer: RBW 3 d. B „dip“ RBW = frequency spacing is not always

Sweeping Analyzer: Envelope Detector n „Filters“ out the RF, leaves only modulation component A

Sweeping Analyzer: Detectors n Analyzer measures much faster than it can display Multiple measurement

FFT: Theory n Fourier says: Each random time signal is the sum of discrete,

FFT Analyzer: Principle n Fourier formulas allow calculation of the spectrum of each time

FFT: Problems and issues n Usually no seamless acquisition (blind times during calculation) Spectrum

FFT with pulsed signals n FFT analyzers are usually fast enough to show the

Important levels of digital signals n Peak: maximum possible level over a long meas.

Bandwidth Measurement (Direct Method) Most important for monitoring stations: 99% bandwidth (equal to occupied

Level Measurement: Procedure With Sweeping Analyzer (1) n n Peak level: n Span ≥

Level Measurement: Procedure With Sweeping Analyzer (2) n AV-burst level: n n n Span

Level Measurement: Procedure with FFT Analyzer (1) n n Peak level: n Capture bandwidth

Level Measurement: Procedure with FFT Analyzer (2) n AV-burst level: n Capture bandwidth ≥

Level Measurement Under Low S/N Ratios n For accurate Pk measurement, S/N ≥ 20

Literature n ITU Spectrum Monitoring Handbook (2011): Chapter 4. 3: RF level measurements Thomas

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Measurements of digital signals with spectrum analyzers Thomas Hasenpusch Federal Network Agency Germany www. bundesnetzagentur. de

Types of available Spectrum Analyzers n Sweeping Analyzer n n Scans the desired frequency range with a narrow filter FFT Analyzer n Captures the time signal and calculates spectrum mathematically Thomas Hasenpusch, Bundesnetzagentur 11/5/2020 2

Sweeping Analyzer: Principle in Theory n Filter is swept through the desired frequency range (Span) A f Thomas Hasenpusch, Bundesnetzagentur 11/5/2020 3

Sweeping Analyzer: Realization of Principle n IF signal is swept through fixed frequency filter (RBW) A IF Thomas Hasenpusch, Bundesnetzagentur f 11/5/2020 4

Sweeping Analyzer: Simplified Block Diagram Detector Reference level Input Mixer IF Amp. IF Filter Log. Amp. Resolution Bandwidth (RBW) Centre frequency Envelope Detector Video Bandwidth (VBW) Video Filter Detector Local Oscillator Trace Mode Display Sawtooth Generator Span, Sweep time Thomas Hasenpusch, Bundesnetzagentur 11/5/2020 5

Sweeping Analyzer: RBW 3 d. B „dip“ RBW = frequency spacing is not always sufficient to separate two signals Optimum (best frequency resolution): RBW = span / display pixels Thomas Hasenpusch, Bundesnetzagentur 11/5/2020 6

Sweeping Analyzer: Envelope Detector n „Filters“ out the RF, leaves only modulation component A Thomas Hasenpusch, Bundesnetzagentur Video signal 11/5/2020 7

Sweeping Analyzer: Detectors n Analyzer measures much faster than it can display Multiple measurement results lie behind each display pixel n Detector determines which of the measured values is displayed n A s 1 s 2 s 3 s 4 s 5 s 6 Average level RMS level Pixel 1 A Pixel 2 t peak AV RMS sample t Thomas Hasenpusch, Bundesnetzagentur 11/5/2020 8

FFT: Theory n Fourier says: Each random time signal is the sum of discrete, unmodulated sinewaves sum Thomas Hasenpusch, Bundesnetzagentur FFT 11/5/2020 9

FFT Analyzer: Principle n Fourier formulas allow calculation of the spectrum of each time signal n Fast Fourier Transform (FFT) greatly reduces calculations, but work only under certain assumptions n Time signal is captured (acquired) for a certain time, digitized and stored in memory n FFT spectrum is then calculated from the stored time samples by a Digital Signal Processor (DSP) RF in Low Pass FIF DSP A/D X 0 Memory FFT f. RF Display Thomas Hasenpusch, Bundesnetzagentur 11/5/2020 10

FFT: Problems and issues n Usually no seamless acquisition (blind times during calculation) Spectrum 1: Display Block 1 acquisition Block 1 processing Block 2 acquisition Spectrum 2: Display Block 2 processing time blind time n blind time Solution: Deploying two separate processing lanes with alternate timing (one lane acquires while the other one processes previous block) Thomas Hasenpusch, Bundesnetzagentur 11/5/2020 11

FFT with pulsed signals n FFT analyzers are usually fast enough to show the spectrum of even very short pulses (e. g. Radar) A 0 FFT window t A A f Thomas Hasenpusch, Bundesnetzagentur A f f 11/5/2020 12

Important levels of digital signals n Peak: maximum possible level over a long meas. time n n RMS (continuous signals): average power a over long meas. time n n Applies when assessing interference potential Applies when checking reception capability, coverage and licence conditions AV burst (pulsed signals): average power during burst only n Applies as RMS, but in case of bursted signals A AV burst level burst duration Thomas Hasenpusch, Bundesnetzagentur t 11/5/2020 13

Bandwidth Measurement (Direct Method) Most important for monitoring stations: 99% bandwidth (equal to occupied bandwidth) n Definition: bandwidth in which 99% of all transmitted energy lies n A 99% 100% 0. 5% OBW f Span (100%) n With analyzer: narrow RBW, Max. Hold, OBW function Thomas Hasenpusch, Bundesnetzagentur 11/5/2020 14

Level Measurement: Procedure With Sweeping Analyzer (1) n n Peak level: n Span ≥ signal bandwidth or zero span n RBW ≥ signal bandwidth n Detector: peak n Max. Hold n Read highest level with Marker RMS-level: n Span ≥ signal bandwidth n Narrow RBW (span/display points) n Detector = RMS or sample n Clear. Write n Channel Power measurement function n If reading is instable: increase sweep time (never use Max. Hold!) Thomas Hasenpusch, Bundesnetzagentur 11/5/2020 15

Level Measurement: Procedure With Sweeping Analyzer (2) n AV-burst level: n n n Span = zero span RBW ≥ signal bandwidth Detector = RMS or sample Clear. Write, trigger on burst Sweep time ≥ burst time Time domain power measurement Ref -20 d. Bm Att 10 d. B RBW 30 k. Hz VBW 300 k. Hz SWT 20 ms -20 Marker 1 [T 1 ] -37. 47 d. Bm 8. 714500 ms POWER [T 1] RMS -39. 27 d. Bm -30 1 RM * CLRWR 1 A SGL TRG -40 -50 -60 -70 TRG -70 d. Bm 3 DB n Average level: n Span = zero span n RBW ≥ signal bandwidth n Detector = Average or sample n Trace = linear average Thomas Hasenpusch, Bundesnetzagentur -80 -90 -100 -110 T 2 T 1 -120 Center 410. 5 MHz 2 ms/ 11/5/2020 16

Level Measurement: Procedure with FFT Analyzer (1) n n Peak level: n Capture bandwidth = signal bandwidth n Time domain analysis n Select shortest possible acquisition time n Max. Hold over multiple acquisitions or amplitude vs. time together with long analysis time n Read highest value RMS level: n Capture bandwidth ≥ signal bandwidth n Channel power function n Long acquisition time or average over multiple short acquisition times n If reading is instable: increase acquisition time or number of averages Thomas Hasenpusch, Bundesnetzagentur 11/5/2020 17

Level Measurement: Procedure with FFT Analyzer (2) n AV-burst level: n Capture bandwidth ≥ signal bandwidth n Trigger analysis on burst start n Channel power function n Acquisition time (or analysis time) = burst time analysis time acquisition time Thomas Hasenpusch, Bundesnetzagentur 11/5/2020 18

Level Measurement Under Low S/N Ratios n For accurate Pk measurement, S/N ≥ 20 d. B is necessary n For accurate RMS, AV-burst measurement, 10 d. B S/N is sufficient n Corrections to indicated level for measurements under lower S/N values: Thomas Hasenpusch, Bundesnetzagentur 11/5/2020 19

Literature n ITU Spectrum Monitoring Handbook (2011): Chapter 4. 3: RF level measurements Thomas Hasenpusch, Bundesnetzagentur 11/5/2020 20