Exercise 4.4: About the Quantization Noise
To calculate the quantization noise power PQ we assume a periodic sawtooth-shaped source signal q(t) with value range ±qmax and period duration T0 .
- In the mean time domain −T0/2≤t≤T0/2 holds: q(t)=qmax⋅(2⋅t/T0).
- We refer to the power of the signal q(t) here as the transmit power PS.
The signal q(t) is quantized according to the graph with M=6 steps. The quantized signal is qQ(t), where:
- The linear quantizer is designed for the amplitude range ±Qmax such that each quantization interval has width {\it Δ} = 2/M \cdot Q_{\rm max}.
- The diagram shows this fact for Q_{\rm max} = q_{\rm max} = 6 \ \rm V. These numerical values shall be assumed up to and including the subtask (5).
The "quantization noise power" is defined as the second moment of the difference signal ε(t) = q_{\rm Q}(t) - q(t). It holds:
- P_{\rm Q} = \frac{1}{T_0' } \cdot \int_{0}^{T_0'}\varepsilon(t)^2 \hspace{0.05cm}{\rm d}t \hspace{0.05cm},
where the time T_0' is to be chosen appropriately. The "quantization SNR" is the ratio \rho_{\rm Q} = {P_{\rm S}}/{P_{\rm Q}}\hspace{0.05cm}, which is usually given logarithmically (in dB).
Hints:
- The exercise belongs to the chapter "Pulse Code Modulation".
- Reference is made in particular to the page "Quantization and quantization Noise".
Questions
Solution
- Due to periodicity and symmetry, averaging over the time domain T_0/2 is sufficient:
- P_{\rm S} = \frac{1}{T_0/2} \cdot \int_{0}^{T_0/2}q^2(t) \hspace{0.05cm}{\rm d}t = \frac{2 \cdot q_{\rm max}^2}{T_0} \cdot \int_{0}^{T_0/2}\left ( { 2 \cdot t}/{T_0} \right )^2 \hspace{0.05cm}{\rm d}t= \frac{2 \cdot q_{\rm max}^2}{T_0} \cdot \frac{T_0}{2} \cdot \int_{0}^{1}x^2 \hspace{0.05cm}{\rm d}x = \frac{q_{\rm max}^2}{3} \hspace{0.05cm}.
- Here the substitution x = 2 - t/T_0 was used. With q_{\rm max} = 6 \ \rm V one gets P_\rm S\hspace{0.15cm}\underline { = 12 \ V^2}.
(2) Correct are suggested solutions 1, 3, and 4:
- We assume here Q_{\rm max} = q_{\rm max} = 6 \ \rm V.
- This gives the sawtooth-shaped error signal ε(t) between ±1\ \rm V.
- The period duration is T_0' = T_0/6.
(3) The error signal ε(t) proceeds in the same way as q(t) sawtooth.
- Thus, the same equation as in subtask (1) is suitable for calculating the power.
- Note, however, that the amplitude is smaller by a factor M while the different period duration does not matter for the averaging:
- P_{\rm Q} = \frac{P_{\rm S}}{M^2} = \frac{12\,{\rm V}^2}{36}\hspace{0.15cm}\underline {= 0.333\,{\rm V}^2 }\hspace{0.05cm}.
(4) The results of the subtasks (1) and (3) lead to the quantization SNR:
- \rho_{\rm Q} = \frac{P_{\rm S}}{P_{\rm Q}} = M^2 = 36 \hspace{0.3cm}\Rightarrow \hspace{0.3cm} 10 \cdot {\rm lg}\hspace{0.1cm}\rho_{\rm Q}\hspace{0.15cm}\underline { =15.56\,{\rm dB}} \hspace{0.05cm}.
(5) With M = 2^N we obtain in general:
- \rho_{\rm Q} = M^2 = 2^{2N} \hspace{0.3cm}\rightarrow \hspace{0.3cm} 10 \cdot {\rm lg}\hspace{0.1cm}\rho_{\rm Q} =20 \cdot {\rm lg}\hspace{0.1cm}(2)\cdot N \approx 6.02\,{\rm dB} \cdot N .
- This results in the special cases we are looking for:
- N = 8:\hspace{0.2cm} 10 \cdot {\rm lg}\hspace{0.1cm}\rho_{\rm Q} \hspace{0.15cm}\underline {= 48.16\,{\rm dB}}\hspace{0.05cm},
- N = 16:\hspace{0.2cm} 10 \cdot {\rm lg}\hspace{0.1cm}\rho_{\rm Q} \hspace{0.15cm}\underline { = 96.32\,{\rm dB}}\hspace{0.05cm}.
(6) All of the above preconditions must be satisfied:
- For non-linear quantization, the simple relation ρ_{\rm Q} = M^2 does not hold.
- For an PDF other than the uniform distribution ρ_{\rm Q} = M^2 is also only an approximation, but this is usually accepted.
- If Q_{\rm max} < q_{\rm max}, truncation of the peaks occurs, while with Q_{\rm max} > q_{\rm max} the quantization intervals are larger than required.
The graph shows the error signals ε(t)
- for Q_{\rm max} > q_{\rm max} (left)
- and Q_{\rm max} < q_{\rm max} (right):
- In both cases, the quantization noise power is significantly larger than calculated in sub-task (3).