Aufgaben:Exercise 3.2Z: Optimum Cutoff Frequency for Gaussian Low-pass

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Noiseless and noisy eye diagrams

As in  Exercise 3.2,  a binary bipolar redundancy-free binary system with Gaussian receiver filter  $H_{\rm G}(f)$  is considered.  Its cutoff frequency  $f_{\rm G}$  is to be determined such that the worst-case S/N ratio

$$\rho_{\rm U} = \frac{\big[\ddot{o}(T_{\rm D})/2 \big]^2}{ \sigma_d^2}\hspace{0.3cm}\Rightarrow \hspace{0.3cm} p_{\rm U} = {\rm Q} \left( \sqrt{\rho_{\rm U}} \right)$$

becomes maximum and thus the worst-case error probability  $p_{\rm U}$  becomes minimum.  The thus optimized cutoff frequency  $f_{\rm G, \ opt}$  usually also leads to the minimum mean symbol error probability  $p_{\rm S, \ min}$.

In the above equation,  the following system quantities are used:

• $\sigma_d^2$  is the detection noise power.  For a Gaussian receiver filter holds:

$$\sigma_d^2 = \frac{N_0}{2} \cdot \int_{-\infty}^{+\infty} |H_{\rm G}(f)|^2 \,{\rm d} f = \frac{N_0 \cdot f_{\rm G}}{\sqrt{2}}\hspace{0.05cm}.$$

• $\ddot{o}(T_{\rm D})$  indicates the  "eye opening".  The detection time is always assumed to be  $T_{\rm D} = 0$. 

• For a Gaussian receiver filter,  the vertical eye opening  $\ddot{o}(T_{\rm D})$  can be expressed solely by the amplitude  $s_0$  of the basic transmission pulse  $($upper boundary line in the noiseless eye diagram$)$ and the maximum value  $g_0$  of the basic detection pulse.  $g_0$ is to be calculated as follows:

$$g_0 = g_d(t = 0) = s_0 \cdot \big [1- 2 \cdot {\rm Q} \left( \sqrt{2\pi} \cdot f_{\rm G} \cdot T \right)\big]\hspace{0.05cm}.$$

The graph shows the eye diagrams of the sought configuration with optimal cutoff frequency.

• In the upper diagram,  noise is not considered.

• The lower diagram,  on the other hand,  is valid with AWGN noise for  $10 \cdot {\rm lg} \ E_{\rm B}/N_0 = 10 \ \rm dB$.

Notes:

• The exercise belongs to the chapter  "Error Probability with Intersymbol Interference".

• Use our HTML5/JavaScript applet  "Complementary Gaussian Error Functions" for the numerical evaluation of the Q–function.

Questions

1

Which statements are true for the eye diagram?

	The eye opening is calculated without noise.
	With Gaussian receiver filter:  $\ddot{o}(T_{\rm D})/2 = s_0 \ – \ g_0$.
	With Gaussian receiver filter:  $\ddot{o}(T_{\rm D})/2 = 2 \cdot g_0 \ – \ s_0$.

2

At what cutoff frequency does a closed eye result?

$f_{\rm G, \ min} \cdot T \ = \ $

3

Calculate the worst-case SNR for  $10 \cdot {\rm lg} \ E_{\rm B}/N_0 = 10 \ \rm dB$.  What are the values for the cutoff frequencies listed below?

$f_{\rm G} \cdot T = 0.6\text{:} \hspace{0.4cm} 10 \cdot \rm lg \ \rho_{\rm U} \ = \ $ $\ \rm dB$

$f_{\rm G} \cdot T = 0.8\text{:} \hspace{0.4cm} 10 \cdot \rm lg \ \rho_{\rm U}\ = \ $ $\ \rm dB$

$f_{\rm G} \cdot T = 1.0\text{:} \hspace{0.4cm} 10 \cdot \rm lg \ \rho_{\rm U} \ = \ $ $\ \rm dB$

4

Which statements are true regarding the optimal cutoff frequency?

	Optimization with respect to  $p_{\rm U}$  $($or  $\rho_{\rm U})$  yields $f_{\rm G, \ opt} \cdot T \approx 0.8$.
	This optimization result is independent of  $E_{\rm B}/N_0$.
	Optimization with respect to  $p_{\rm S}$  leads to exactly the same result.

5

Determine the following quantities for the optimal cutoff frequency  $f_{\rm G, \ opt}$  for  $10 \cdot {\rm lg} \ (E_{\rm B}/N_0) = 10 \ \rm dB$.

$\ddot{o}(T_{\rm D})/s_0 \ = \ $

$\sigma_d/s_0 \ = \ $

$10 \cdot \rm lg \ \rho_{\rm U} \ = \ $ $\ \rm dB$

$p_{\rm U}\ = \ $ $\ \cdot 10^{\rm -5}$

Solution

Solution

(1)  The  first and third solutions  are correct:

• When calculating the vertical eye opening,  the noise component must not be taken into account.  This is captured by the noise rms value  $\sigma_d$.
• If the eye opening were taken from the lower eye diagram,  the noise component would be captured twice.
• The upper boundary of the inner eye line results for the symbol sequence  "$\text{ ...} \, \ -\hspace{-0.1cm}1 \ -\hspace{-0.1cm}1, +1, -\hspace{-0.1cm}1, \ -\hspace{-0.1cm}1, \text{ ...} $" .
• The long  "$-1$"  sequence would lead to the value $-s_0$.
• In contrast,  the  "worst–case"  sequence leads to the eye line  $-s_0 + 2 \cdot g_d(t)$.
• Thus,  at detection time  $T_{\rm D} = 0$,  with decision threshold  $E = 0$:

$${\ddot{o}(T_{\rm D})}/{ 2}= 2 \cdot g_0 - s_0 \hspace{0.05cm}.$$

(2)  For the half vertical eye opening holds:

$${\ddot{o}(T_{\rm D})}/{ 2} \ = \ 2 \cdot g_0 - s_0 = 2 \cdot s_0 \cdot\left [ 1- 2 \cdot {\rm Q} \left( \sqrt{2\pi} \cdot f_{\rm G} \cdot T \right)\right] - s_0 = s_0 \cdot\left [ 1- 4 \cdot {\rm Q} \left( \sqrt{2\pi} \cdot f_{\rm G} \cdot T \right)\right] \hspace{0.05cm}.$$

• A closed eye results according to the given applet for

$${\rm Q} \left( \sqrt{2\pi} \cdot f_{\rm G} \cdot T \right) \ge 0.25 \hspace{0.3cm}\Rightarrow \hspace{0.3cm} \sqrt{2\pi} \cdot f_{\rm G} \cdot T< 0.675\hspace{0.3cm}\Rightarrow \hspace{0.3cm} f_{\rm G, min} \cdot T \approx \frac{0.675}{2.5}\hspace{0.15cm}\underline { \approx 0.27} \hspace{0.05cm}.$$

(3)  Using the equations on the information section and the previous calculations,  we obtain

$\rho_{\rm U}$ as a function of (normalized) cutoff frequency

$$\rho_{\rm U} = \frac{[\ddot{o}(T_{\rm D})/2]^2}{ \sigma_d^2} = \frac{s_0^2 \cdot\left [ 1- 4 \cdot {\rm Q} \left( \sqrt{2\pi} \cdot f_{\rm G} \cdot T \right)\right]^2}{ N_0 \cdot f_{\rm G} / \sqrt{2}}$$

• With the specification  $E_{\rm B}/N_0 = 10 \ \rm dB $,  the following determining equation is obtained:

$$10 \cdot {\rm lg}\hspace{0.1cm} {E_{\rm B}}/{ N_0} = 10 \, {\rm dB}\hspace{0.3cm}\Rightarrow \hspace{0.3cm} {E_{\rm B}}/{ N_0} = {s_0^2 \cdot T}/{ N_0} = 10$$

$$\Rightarrow \hspace{0.3cm} \rho_{\rm U} = 10 \cdot \sqrt{2} \cdot \frac{ \left [ 1- 4 \cdot {\rm Q} \left( \sqrt{2\pi} \cdot f_{\rm G} \cdot T \right)\right]^2}{ f_{\rm G} \cdot T}\hspace{0.05cm}.$$

• The figure shows this function plot as a function of the  (normalized)  cutoff frequency.  For the given cutoff frequencies holds:
• $f_{\rm G} \cdot T = 0.6\text{:} \hspace{0.4cm} \rho_{\rm U} \approx 12.7 \Rightarrow 10 \cdot \rm lg \ \rho_{\rm U} \ \underline {\approx \ 11.04 \ \rm dB},$
• $f_{\rm G} \cdot T = 0.8\text{:} \hspace{0.4cm} \rho_{\rm U} \approx 14.7 \Rightarrow 10 \cdot \rm lg \ \rho_{\rm U} \ \underline {\approx \ 11.66 \ \rm dB},$
• $f_{\rm G} \cdot T = 1.0\text{:} \hspace{0.4cm} \rho_{\rm U} \approx 13.5 \Rightarrow 10 \cdot \rm lg \ \rho_{\rm U} \ \underline {\approx \ 11.30 \ \rm dB}.$

• From the above graph,  one can also see the minimum cutoff frequency   ⇒   subtask (2).

(4)  The  first two solutions  are correct:

• The validity of the first statement is evident from the above graph.
• Since in  $\rho_{\rm U}$  equation the ratio  $E_{\rm B}/N_0$  occurs only a factor,  the optimization  (setting derivative to zero)  always leads to the same result independent of  $E_{\rm B}/N_0$.
• The optimal cutoff frequency with respect to  $p_{\rm U}$  is approximately optimal with respect to  $p_{\rm S}$  as well,  but not exactly.
• For very large values of  $E_{\rm B}/N_0$  (small noise),  this approximation is very correct and  $p_{\rm S} \ \approx \ p_{\rm U}/4$  holds.
• In contrast,  for large noise e.g.  $10 \cdot {\rm lg} \ E_{\rm B}/N_0 = 0 \ \rm dB$,  a smaller optimal cutoff frequency results when the optimization is based on  $p_{\rm S}$:

$f_{\rm G} \cdot T = 0.8\text{:} \hspace{0.4cm} p_{\rm U} = 0.113,\hspace{0.4cm} p_{\rm S} = 0.102,$

$f_{\rm G} \cdot T = 0.6\text{:} \hspace{0.4cm} p_{\rm U} = 0.129,\hspace{0.4cm} p_{\rm S} = 0.094.$

• However,  the error probabilities are then so large that these results are not practically relevant.

(5)  With the result of subtask  (2)   ⇒   $E_{\rm B}/N_0 = 10$ and $f_{\rm G} \cdot T = 0.8$  holds:

$${\ddot{o}(T_{\rm D})}/{ s_0} = 2 \cdot \left [ 1- 4 \cdot {\rm Q} \left( \sqrt{2\pi} \cdot 0.8 \right)\right] = 2 \cdot \left [ 1- 4 \cdot 0.022\right]\hspace{0.15cm}\underline { = 1.824} \hspace{0.05cm},$$

$${\sigma_d^2}/{ s_0^2} = \frac{N_0 \cdot f_{\rm G} }{\sqrt{2}\cdot s_0^2}= \frac{N_0 }{s_0^2 \cdot T} \cdot \frac{f_{\rm G} \cdot T}{\sqrt{2}} = 0.1 \cdot \frac{0.8}{\sqrt{2}} \approx 0.0566 \hspace{0.3cm}\Rightarrow \hspace{0.3cm}{\sigma_d}/{ s_0}\hspace{0.15cm}\underline { \approx 0.238} \hspace{0.05cm},$$

$$\rho_{\rm U} = \frac{[\ddot{o}(T_{\rm D})]^2}{ 4 \cdot \sigma_d^2} = \frac{1.824^2}{ 4 \cdot 0.0566}\approx 14.7 \hspace{0.3cm}\Rightarrow \hspace{0.3cm} 10 \cdot {\rm lg}\hspace{0.1cm} \rho_{\rm U}\hspace{0.15cm}\underline {\approx 11.66\, {\rm dB}} \hspace{0.05cm}.$$

$$p_{\rm U} = {\rm Q} \left( \sqrt{\rho_{\rm U}} \right) = {\rm Q} \left( \sqrt{14.7} \right) \hspace{0.15cm}\underline { \approx 6.4 \cdot 10^{-5}}\hspace{0.05cm}.$$