COMMUNICATION SYSTEM EEEB453 Chapter 5 (Part III) DIGITAL TRANSMISSION

1. COMMUNICATION SYSTEM EEEB453Chapter 5 (Part III)DIGITAL TRANSMISSION Intan Shafinaz Mustafa Dept of Electrical Engineering Universiti Tenaga Nasional http://metalab.uniten.edu.my/~shafinaz

2. Signal to Quantization Noise Ratio (SQR) • Linear codes – the magnitude change between any two successive codes is the same i.e the quantum/quantization interval is equal, thus the magnitude of the quantization errors are also equal. • Recall, maximum quantization noise, Qe = ½ quantum = Vlsb/2, • Then worst-case (minimum) voltage SQR (occurs when input signal is at its minimum amplitude) is • Maximum SQR occurs at the maximum signal amplitude, i.e From previous example,

3. Signal to Quantization Noise Ratio (SQR) • From the example, even though the magnitude of the Qe remains constant, the percentage of error decreases as the magnitude of the sample increase.Thus, SQR is not constant. • For linear PCM code i.e all quantization intervals have equal magnitude, SQR or SNR is defined as • Generally, SQRdB = 10.8 + 20 log v/q where v = rms signal voltage q = quantization interval or SQRdB = 6.02n + 1.76 where n = no. of bits (assume equal R)

4. Example 5 – A digitizing system specifies 55 dB of dynamic range. How many bits are required to satisfy the dynamic range specification? What is the signal-to-noise ratio for the system?

5. Uniform and Non-uniform Quantization Notice that poor resolution is present in the weak signal regions, yet the strong signal exhibit a reasonable exact copy of the original signal. • In uniform (linear) quantization – each quantum interval is the same step size • In nonuniform (non-linear) coding – each quantum interval step size may vary in magnitude • How can the quantization error be modified in a nonuniform PCM system so that an improve SNR result? Figure also shows how the quantum interval can be changed to provide smaller step-sizes within the area of the weak signal. This will result in an improved SNR for the weak signal.

6. SQR at lower amplitude < SQR at higher amplitude Lower amplitude values are relatively more distorted More of voice signal is at lower amplitude Reduce step size at lower amplitude More accuracy at lower amplitude Sacrifices SQR at higher amplitude Provides higher dynamic range

7. Linear versus Nonlinear PCM Codes. • For linear coding, accuracy of the higher amplitude analog signal is the same as for the lower amplitude signal. • SQR for lower amplitude signal is less than the higher amplitude signal. • For voice transmission, low amplitude signals are more likely to occur than large amplitude signals. • Thus a nonlinear encoding is the solution. • With non-linear coding, the step size increases with the amplitude of the input signal. • Nonlinear encoding gives larger dynamic range. • SQR is sacrificed for higher amplitude signals to achieve more accuracy for the lower amplitude signals. • However, it is difficult to fabricate nonlinear ADC.

8. Companding • Companding is the process of compressing and then expanding. • Higher amplitude analog signals are compressed (amplified less) prior to Tx and then expanded (amplified more) at the Rx. • It improves the dynamic range. Notice, how the weak portion of the input is made nearly equal to the strong portion by the compressor but restored to the proper level by the expander. Companding is essential to quality transmission using PCM.

9. Input signal with DR of 50dB is compressed to 25dB at Tx Expanded back to its original DR of 50dB at Rx

10. The input-output characteristics of a compressor are shown in Fig. (b). • The horizontal axis is the normalized input signal i.e • The compressor maps input signal increment, m into larger increments y for small input signals, and vice versa for large input signal.

11. Analog Companding • In the transmitter, the DR of the analog signal is compressed, sampled and then converted to a linear PCM code. • In the receiver, the PCM code is converted to a PAM signal, filtered, and then expanded back to its original DR

12. Analog Companding • 2 methods of analog companding : i. μ-Law - use in Japan and US Vmax= maximum uncompressed analong input amplitude (V) Vin = amplitude of the input signal at a particular instant of time (V) μ = parameter to define the amount of compression (unitless) = 255 Vout = compressed output amplitude (V) ii. A-law – use in Europe For voice Tx which requires minimum DR of 40dB, μ=255 and A=87.6 gives comparable result and has been standardize by CCITT.

13. μ-Law Characteristic A-Law Characteristic • The μ parameter defines the amount of compression (i.e the range of signal power in which the SQR is relatively constant. • Note μ= 0 indicates no compression and the voltage gain curve is linear. • Higher value ofμyield nonlinear curves.

14. Example 6 - For a compressor with a μ = 255, determine a. The voltage gain for the following relative values of Vin : (i) Vmax (ii) 0.75Vmax (iii) 0.5Vmax (iv) 0.25Vmax b. The compressed output voltage for a maximum input voltage of 4V c. Input and output DR and compression.