Measurements of digital signals with spectrum analyzers Thomas Hasenpusch Federal Network Agency Germany

Types of available Spectrum Analyzers Sweeping Analyzer Scans the desired frequency range with a narrow filter FFT Analyzer Captures the time signal and calculates spectrum mathematically Thomas Hasenpusch, Bundesnetzagentur 05.12.2018

Sweeping Analyzer: Principle in Theory Filter is swept through the desired frequency range (Span) f A Thomas Hasenpusch, Bundesnetzagentur 05.12.2018

Sweeping Analyzer: Realization of Principle IF signal is swept through fixed frequency filter (RBW) f A IF Thomas Hasenpusch, Bundesnetzagentur 05.12.2018

Sweeping Analyzer: Simplified Block Diagram Detector Video Bandwidth (VBW) Reference level Input Mixer IF Amp. IF Filter Log. Amp. Envelope Detector Video Filter Detector Display Local Oscillator Sawtooth Generator Resolution Bandwidth (RBW) Centre frequency Detector Trace Mode Span, Sweep time Thomas Hasenpusch, Bundesnetzagentur 05.12.2018

Sweeping Analyzer: RBW 3dB „dip“ RBW = frequency spacing is not always sufficient to separate two signals Optimum (best frequency resolution): RBW = span / display pixels Thomas Hasenpusch, Bundesnetzagentur 05.12.2018

Sweeping Analyzer: Envelope Detector „Filters“ out the RF, leaves only modulation component A Video signal Thomas Hasenpusch, Bundesnetzagentur 05.12.2018

Sweeping Analyzer: Detectors Analyzer measures much faster than it can display Multiple measurement results lie behind each display pixel Detector determines which of the measured values is displayed s1 s2 s3 s4 s5 s6 s1 s2 s3 s4 s5 s6 A t Average level RMS level Pixel 1 Pixel 2 A t peak AV RMS sample Thomas Hasenpusch, Bundesnetzagentur 05.12.2018

FFT: Theory Fourier says: Each random time signal is the sum of discrete, unmodulated sinewaves sum FFT Thomas Hasenpusch, Bundesnetzagentur 05.12.2018

FFT Analyzer: Principle Fourier formulas allow calculation of the spectrum of each time signal Fast Fourier Transform (FFT) greatly reduces calculations, but work only under certain assumptions Time signal is captured (acquired) for a certain time, digitized and stored in memory FFT spectrum is then calculated from the stored time samples by a Digital Signal Processor (DSP) X A/D DSP RF in FIF Low Pass Display FFT Memory fRF Thomas Hasenpusch, Bundesnetzagentur 05.12.2018

FFT: Problems and issues Usually no seamless acquisition (blind times during calculation) Spectrum 1: Display Spectrum 2: Display Block 1 acquisition Block 1 processing Block 2 acquisition Block 2 processing time blind time blind time Solution: Deploying two separate processing lanes with alternate timing (one lane acquires while the other one processes previous block) Thomas Hasenpusch, Bundesnetzagentur 05.12.2018

FFT with pulsed signals FFT analyzers are usually fast enough to show the spectrum of even very short pulses (e.g. Radar) A t FFT window FFT window FFT window A f A f A f Thomas Hasenpusch, Bundesnetzagentur 05.12.2018

Important levels of digital signals Peak: maximum possible level over a long meas. time Applies when assessing interference potential RMS (continuous signals): average power a over long meas. time Applies when checking reception capability, coverage and licence conditions AV burst (pulsed signals): average power during burst only Applies as RMS, but in case of bursted signals AV burst level A t burst duration Thomas Hasenpusch, Bundesnetzagentur 05.12.2018

Bandwidth Measurement (Direct Method) Most important for monitoring stations: 99% bandwidth (equal to occupied bandwidth) Definition: bandwidth in which 99% of all transmitted energy lies f A 100% 99% Span (100%) 0.5% 0.5% OBW With analyzer: narrow RBW, MaxHold, OBW function Thomas Hasenpusch, Bundesnetzagentur 05.12.2018

Level Measurement: Procedure With Sweeping Analyzer (1) Peak level: Span ≥ signal bandwidth or zero span RBW ≥ signal bandwidth Detector: peak MaxHold Read highest level with Marker RMS-level: Span ≥ signal bandwidth Narrow RBW (span/display points) Detector = RMS or sample ClearWrite Channel Power measurement function If reading is instable: increase sweep time (never use MaxHold!) Thomas Hasenpusch, Bundesnetzagentur 05.12.2018

Level Measurement: Procedure With Sweeping Analyzer (2) AV-burst level: Span = zero span RBW ≥ signal bandwidth Detector = RMS or sample ClearWrite, trigger on burst Sweep time ≥ burst time Time domain power measurement A t 1 d B C L R W 3 D k H z V e f - 2 m n r 4 . 5 M s / S T G * 9 8 7 6 a [ ] P O E Average level: Span = zero span RBW ≥ signal bandwidth Detector = Average or sample Trace = linear average Thomas Hasenpusch, Bundesnetzagentur 05.12.2018

Level Measurement: Procedure with FFT Analyzer (1) Peak level: Capture bandwidth = signal bandwidth Time domain analysis Select shortest possible acquisition time MaxHold over multiple acquisitions or amplitude vs. time together with long analysis time Read highest value RMS level: Capture bandwidth ≥ signal bandwidth Channel power function Long acquisition time or average over multiple short acquisition times If reading is instable: increase acquisition time or number of averages Thomas Hasenpusch, Bundesnetzagentur 05.12.2018

Level Measurement: Procedure with FFT Analyzer (2) AV-burst level: Capture bandwidth ≥ signal bandwidth Trigger analysis on burst start Channel power function Acquisition time (or analysis time) = burst time acquisition time analysis time Thomas Hasenpusch, Bundesnetzagentur 05.12.2018

Level Measurement Under Low S/N Ratios For accurate Pk measurement, S/N ≥ 20 dB is necessary For accurate RMS, AV, AV-burst measurement, 10 dB S/N is sufficient Corrections to indicated level for measurements under lower S/N values: Thomas Hasenpusch, Bundesnetzagentur 05.12.2018

Literature ITU Spectrum Monitoring Handbook (2011): Chapter 4.3: RF level measurements Thomas Hasenpusch, Bundesnetzagentur 05.12.2018