View
221
Download
0
Tags:
Embed Size (px)
Citation preview
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