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Principios de Comunicaciones EL4005

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Presentation on theme: "Principios de Comunicaciones EL4005"— Presentation transcript:

1 Principios de Comunicaciones EL4005
César Azurdia Meza, Ph.D

2 Formatting and transmission of baseband signal
Digital info. Bit stream (Data bits)‏ Pulse waveforms (baseband signals)‏ Information (data) rate: Symbol rate : For real time transmission: Textual info. Format source Pulse modulate Sample Quantize Encode Analog info. Sampling at rate (sampling time=Ts)‏ Encoding each q. value to bits (Data bit duration Tb=Ts/l)‏ Quantizing each sampled value to one of the L levels in quantizer. Mapping every data bits to a symbol out of M symbols and transmitting a baseband waveform with duration T

3 Quantization example Quant. levels boundaries x(nTs): sampled values
amplitude x(t)‏ x(nTs): sampled values xq(nTs): quantized values boundaries Quant. levels Ts: sampling time t PCM codeword PCM sequence

4 Example of M-ary PAM Assuming real time transmission and equal energy per transmission data bit for binary-PAM and 4-ary PAM: 4-ary: T=2Tb and Binary: T=Tb Binary PAM (rectangular pulse)‏ 4-ary PAM (rectangular pulse)‏ 3B A. ‘1’ ‘11’ B T T ‘01’ T T ‘10’ ‘00’ T T ‘0’ -B -A. -3B

5 Example of M-ary PAM … 2.2762 V 1.3657 V 1 1 0 1 0 1 Rb=1/Tb=3/Ts
Ts Ts V V 0 Tb 2Tb 3Tb 4Tb 5Tb 6Tb Rb=1/Tb=3/Ts R=1/T=1/Tb=3/Ts 0 T T 3T 4T 5T 6T Rb=1/Tb=3/Ts R=1/T=1/2Tb=3/2Ts=1.5/Ts T T T

6 Today we are going to talk about:
Receiver structure Demodulation (and sampling)‏ Detection First step for designing the receiver Matched filter receiver Correlator receiver

7 Demodulation and detection
Format Pulse modulate Bandpass modulate M-ary modulation channel transmitted symbol Major sources of errors: Thermal noise (AWGN)‏ disturbs the signal in an additive fashion (Additive) has flat spectral density for all frequencies of interest (White)‏ is modeled by Gaussian random process (Gaussian Noise) Inter-Symbol Interference (ISI)‏ Due to the filtering effect of transmitter, channel and receiver, symbols are “smeared”. estimated symbol Format Detect Demod. & sample

8 Example: Impact of the channel

9 Example: Channel impact …

10 Receiver tasks Demodulation and sampling: Detection:
Waveform recovery and preparing the received signal for detection: Improving the signal power to the noise power (SNR) using matched filter Reducing ISI using equalizer Sampling the recovered waveform Detection: Estimate the transmitted symbol based on the received sample

11 Receiver structure Step 1 – waveform to sample transformation
Step 2 – decision making Demodulate & Sample Detect Threshold comparison Frequency down-conversion Receiving filter Equalizing filter Compensation for channel induced ISI For bandpass signals Received waveform Baseband pulse (possibly distored)‏ Baseband pulse Sample (test statistic)‏

12 Baseband and bandpass Bandpass model of detection process is equivalent to baseband model because: The received bandpass waveform is first transformed to a baseband waveform. Equivalence theorem: Performing bandpass linear signal processing followed by heterodyning the signal to the baseband, yields the same results as heterodyning the bandpass signal to the baseband , followed by a baseband linear signal processing.

13 Steps in designing the receiver
Find optimum solution for receiver design with the following goals: Maximize SNR Minimize ISI Steps in design: Model the received signal Find separate solutions for each of the goals. First, we focus on designing a receiver which maximizes the SNR.

14 Design the receiver filter to maximize the SNR
Model the received signal Simplify the model: Received signal in AWGN AWGN Ideal channels AWGN

15 Band-limited Signals Current practical communication systems are band limited. Steadily increasing spectrum congestion. Higher error-free data rate within a fixed limited bandwidth. Nyquist pulses are used to reduce channel bandwidth.

16 Intersymbol Interference (ISI)
It occurs when a pulse spreads out and interferes with adjacent pulses at the sampling instant. ISI produces symbol- timing errors at the receiver. Nyquist pulses are implemented to reduce ISI. Sampling Instants. ISI occurs, but NO ISI is present at the sampling instants.

17 Channel Filter Filtro implementado para limitar el ancho de bando en base a las especificaciones del canal. Pass-band Base-band

18 Channel Filter: Raised Cosine Filter
3GPP standard proposes the use of the RC pulse at the transmitter/receiver side with α = Characterized by the roll-off factor 0 ≤ α ≤1

19 Channel Filter: Raised Cosine Filter
Respuesta al Impulso Respuesta en Frecuencia

20 Channel Filter: Raised Cosine Filter

21 Matched Filter: Root Raised Cosine Filter
According to the 3GPP standard, the impulse response of the RRC pulse is given as: Time Domain Root Raised Cosine Pulse

22 Matched filter receiver
Problem: Design the receiver filter such that the SNR is maximized at the sampling time when is transmitted. Solution: The optimum filter, is the Matched filter, given by which is the time-reversed and delayed version of the conjugate of the transmitted signal T t T t

23 Example of matched filter
T 2T t T/2 T t T/2 T T t T/2 T 3T/2 2T t

24 Properties of the matched filter
The Fourier transform of a matched filter output with the matched signal as input is, except for a time delay factor, proportional to the ESD of the input signal. The output signal of a matched filter is proportional to a shifted version of the autocorrelation function of the input signal to which the filter is matched. The output SNR of a matched filter depends only on the ratio of the signal energy to the PSD of the white noise at the filter input. Two matching conditions in the matched-filtering operation: spectral phase matching that gives the desired output peak at time T. spectral amplitude matching that gives optimum SNR to the peak value.

25 Correlator receiver The matched filter output at the sampling time, can be realized as the correlator output.

26 Implementation of matched filter receiver
Bank of M matched filters Matched filter output: Observation vector

27 Implementation of correlator receiver
Bank of M correlators Correlators output: Observation vector

28 Implementation example of matched filter receivers
Bank of 2 matched filters T t T T T t


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