Communication Systems Simulation - II Harri Saarnisaari

1. Communication Systems Simulation - II Harri Saarnisaari Part ofSimulations and Tools for Telecommunication Course

2. Link Simulations • First you have to design what details you take into account in your simulation model • A too detailed model requires too much (unnecessary) efforts • This depends what you are simulating • Irrelevant things are either • ignored (assumed to be ideal, i.e., no influence) • or modeled by a higher order model, which causes certain distortions/uncertainties to the investigated signal

3. Link Simulations • You might need to • Create the transmitted signal • Create random data • Do channel coding and interleaving • Create pulse shaped signal • Model the radio channel • Simulations usually done as a function of received SNR, i.e., propagation loss effects are ignored • However, short term variations of the channel are often taken into account • Fading channels vs. non-fading channels • Receiver has to be modeled with required details which depends on your target • Channel estimation/synchronization and BER studies usually done separately

4. Simplified transmitter I x(t) and y(t) are I- and Q-components of the baseband signal sl(t) (complex envelope) Q complex envelope sl(t) used for demodulation, Synchronization, … In real life it is disturbed by noise, unknown delay and complex amplitude Simplified receiver RF part Digital part Signals are usually complex: complex envelopes are used to present them! Transceivers are IQ.

5. BER Simulations • Usually done at rate one sample per symbol (or chip in direct sequence systems) • Create • Random data symbols • Channel coding and interleaver • If effects of coding and interleaving are studied • Block, convolutional, cascaded, turbo, space-time, … • Baseband modulator • BPSK, QPSK, MSK, DS, OFDM, MC-CDMA, UWB,… • Coherent modulation • Differential modulation • Orthogonal modulation • Pulse shaping (if needed) • Transmitter DA/RF effects usually ignored

6. BER Simulations • Effects of propagation (radio) channel • Multiply signal by channel tap coefficients • Single tap or multiple taps • Random vs non-random taps (fading vs non-fading channels) • Add thermal noise (actually generated in receiver electronics) • Such that SNR requirements are satisfied (alternatively SNR is set by tap coefficients) • Simulations usually executed as a function of SNR • Add other possible signals • Multiple access signals • Interference

7. BER Simulations • Receiver functions • RF/AD effects usually ignored • Perfect synchronization usually assumed • However, sometimes effects of amplitude imbalance at IQ-channels, phase and frequency synchronization errors to BER might be considered • Freq. error = constantly increasing (in to a direction or to another) phase error due to Doppler frequency shift (mod 2) • Pulse shape matched filtering (if needed) • Channel equalization (if needed) • Data demodulation by the investigated receiver structure • Coherent, differential, energy based (orthogonal modulation) • Hard/soft decisions for decoding, • multiuser detectors (MUD), … • Deinterleaving and channel decoding • Measurements • Coded BER (with channel coding/decoding) • Uncoded BER (without channel coding) • Frame error rate, packet error rate,…

8. BER Simulations

9. Estimation Simulations • For amplitude, phase and frequency estimation studies usually signal with one sample per symbol (or chip) is sufficient • This is so because these estimators often use data decisions as an input to the estimator • Data aided (DA) or non-DA algorithms • This rate is sufficient also for probability of synchronization studies in DS/MC-CDMA • Create a signal • Add channel effects • Manipulate received signals by your estimation algorithm • Measure performance of algorithm • Bias • Variance • Probability of detection/false alarm • Usually compared to some other algorithm(s) in terms of performance and computational complexity

10. Estimation Simulations

11. Higher Sampling Rates • Higher sampling rates (q samples/symbol (or chip)) are needed • In delay estimation studies • To investigate effects of timing uncertainties • In practice timing uncertainties are a fraction of symbol (chip) duration • to model these effects more precisely oversampling is needed • To study fractionally spaced equalizers • To investigate effects of pulse shaping, RF-filters and receiver digital filters more reliable

12. Higher Sampling Rates • To create a baseband signal that is more close the reality than one sample/symbol signals • The Nyquist theorem says that a baseband signal has to be sampled at least twice the bandwidth in order that its analog form can be formed accurately • Practical transmitters usually interpolate signal before DA • Interpolation: from one sample/symbol to q samples/symbol • In the receiver sampling at least by Nyquist rate is usually needed to adjust timing • Sample time that best corresponds the correct timing is selected (or is used to correct sample timing) • After obtaining timing one sample/symbol is sufficient

13. Higher Sampling Rates • Create baseband signal with one sample/symbol (chip) • Interpolate it • E.g., add q-1 zeros between samples and filter • Square pulse: copy sample q times • Modulation either before or after interpolation depending on modulation methods • E.g., in BPSK, QPSK it is after, in MSK it is before • Add channel effects • Manipulate received signal by your receiver

14. Higher Sampling Rates • You can have • Timing uncertainties (in addition to amplitude, phase and frequency ones) • Effects of it to BER • Test how well delay estimators perform • Non-perfect knowledge of timing instant • Create signal with q samples/symbol and receive it with q’ samples/symbol, q’<q • More close to reality than q’=q case but very seldom used (due to its complexity) • Still, you can see some effects that are invisible with q’=q case • E.g., delay estimator’s variance is larger with q’<q than with q’=q

15. Higher Sampling Rates

16. Link Simulations • In baseband simulations RF & AD/DA effects are usually ignored (assumed to be perfect, ideal) • However, the effects may be taken into account by a higher order model of those • E.g., phase & frequency & amplitude imbalance between I- and Q- branches • Sometimes power amplifiers operate at a nonlinear zone • If the signal is not a constant envelope signal nonlinearities affect it • Linear PA model is not sufficient • Some simulations consider how non-linearities (different models) affect the signal and receiver’s performance

17. Link Simulations • AD/DA add noise (quantization error and saturation effects) • How receiver performs if b bits AD is used? • How many bits are needed in order that quantization errors are insignificant (with a given receiver structure or algorithms)? • How saturation affects, what is harmful level of saturation? • How signal should be scaled (by AGC) so that harmful saturation is avoided?

18. Link Simulations • Antenna models usually ignored in single antenna case (this is OK) • In multiple antennae case they should be modeled • However, antennas are usually assumed to follow their theoretical model • E.g. in adaptive antenna array studies • Effects of calibration errors, mutual coupling, errors in direction-of-arrival knowledge are often ignored in BER analysis although their influence may be significant • Results too optimistic view of capabilities of antenna arrays • Some simulations concern these effects and methods that help to mitigate these effects

19. RF & Antenna Simulations • RF and antenna simulators usually used to design RF-parts and antennas • However, these could give a higher level model of these parts to baseband simulations • The models can be used to make simulations more realistic (i.e., more accurate) • This has not been very common, so far