Communication Systems Simulation - II

Harri SaarnisaariPart of Simulations 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

x(t) and y(t) are I- and Q-componentsof the baseband signal sl(t) (complex envelope)

Simplified transmitter

Simplified receiver

RF part Digital part

complex envelope sl(t)used fordemodulation,Synchronization,…In real life it isdisturbed bynoise, unknown delayand complex amplitude

Signals are usually complex: complex envelopes are usedto present them! Transceivers are IQ.

I

Q

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

data

BER

interleavingChannelcoding

demodulation

channel

modulation

deinterleavingChanneldecoding

Simple BER simulation block diagram

One sample/symbol (chip)

Add TX effects to thesignal

Add RX effects to thesignal

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

data interleavingChannelcoding

channel

modulation

One sample/symbol (chip)

estimatorEstimator

performance

Simple estimator simulation block diagram

Add known uncertainties,which you estimate, to the

signal

Add TX effects to thesignal

Add RX effects to thesignal

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

data

BER

interleavingChannelcoding

demodulation

channel

Modulation/(interpolation)

deinterleavingChanneldecoding

More complex BER/estimator simulation block diagram

One sample/symbol (chip)

Add TX effects to thesignal

Add RX effects to thesignal

estimatorEstimator

performance

Interpolation/filtering

filtering

q samples/symbol(chip)

Add knownuncertainties,

which youestimate, to the

signal

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

interfering signal / direction which is not wanted to be illuminated

Desired signal direction

Basestation with an adaptive antenna array

Maximum gain towards the desired signal and minimum towards an interfering signal in reception and non-desised angle in transmission

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