Exercise 1.4Z: Entropy of the AMI Code

Binary source signal (top) and
ternary encoder signal (bottom)

We assume similar prerequisites as in task 1.4 :

A binary source provides the source symbol sequence $\langle q_\nu \rangle$ with $q_\nu \in \{ {\rm L}, {\rm H} \}$, where there are no statistical ties between the individual sequence elements.

For the symbol probabilities, let:

$p_{\rm L} =p_{\rm H} = 1/2$ (in subtasks 1 und 2),
$p_{\rm L} = 1/4, \, p_{\rm H} = 3/4$ (subtasks 3, 4 and 5),
$p_{\rm L} = 3/4, \, p_{\rm H} = 1/4$ (subtask 6).

The presented code signal $c(t)$ and the corresponding symbol sequence $\langle c_\nu \rangle$ with $c_\nu \in \{{\rm P}, {\rm N}, {\rm M} \}$ results from the AMI coding (Alternate Mark Inversion) according to the following rule:

The binary symbol $\rm L$ ⇒ Low is always represented by the ternary symbol $\rm N$ ⇒ Null .
The binary symbol $\rm H$ ⇒ High is also coded deterministically but alternately (hence the name „AMI”) by the symbols $\rm P$ ⇒ Plus and $\rm M$ ⇒ Minus .

In this task, the decision content $H_0$ and the resulting entropy $H_{\rm C}$ the code symbol sequence $\langle c_\nu \rangle$ are to be determined for the three parameter sets mentioned above. The relative redundancy of the code sequence results from this according to the equation

$$r_{\rm C} = \frac{H_{\rm 0}-H_{\rm C}}{H_{\rm C}} \hspace{0.05cm}.$$

Hints:

The task belongs to the chapter Sources with Memory.
Reference is made in particular to the page The Entropy of the AMI code.

In general, the following relations exist between the decision content $H_0$, the entropy $H$ $($here equal to $H_{\rm C})$ und den Entropienäherungen:

$$H \le \ \text{...} \ \le H_3 \le H_2 \le H_1 \le H_0 \hspace{0.05cm}.$$

In task 1.4 for equally probable symbols $\rm L$ and $\rm H$ the entropy approximations were calculated as follows (each in „bit/symbol”):

$$H_1 = 1.500\hspace{0.05cm},\hspace{0.2cm} H_2 = 1.375\hspace{0.05cm},\hspace{0.2cm}H_3 = 1.292 \hspace{0.05cm}.$$

Questions

$H_{\rm C} \ = \ $

$\ \rm bit/ternary symbol$

$r_{\rm C} \ = \ $

$\ \rm \%$

$H_{\rm C} \ = \ $

$\ \rm bit/ternary symbol$

$r_{\rm C} \ = \ $

$\ \rm \%$

$H_{\rm 1} \ = \ $

$\ \rm bit/ternary symbol$

$H_{\rm 1} \ = \ $

$\ \rm bit/ternary symbol$

Solution

(1) Since the AMI code neither adds new information nor causes information to disappear, the entropy $H_{\rm C}$ of the code symbol sequence $\langle c_\nu \rangle$ is equal to the source entropy $H_{\rm Q}$.

Therefore, for equally probable and statistically independent source symbols, the following holds:

$$H_{\rm Q} {= 1 \,{\rm bit/binary symbol}} \hspace{0.3cm} \Rightarrow\hspace{0.3cm} H_{\rm C} \hspace{0.15cm} \underline {= 1 \,{\rm bit/ternary symbol}} \hspace{0.05cm}.$$

(2) The decision content of a ternary source is $H_0 = \log_2 \; (3) = 1.585\; \rm bit/symbol$.

This gives the following for the relative redundancy

$$r_{\rm C} =1 -{H_{\rm C}/H_{\rm 0}}=1-1/{\rm log}_2\hspace{0.05cm}(3) \hspace{0.15cm} \underline {= 36.9 \,\%} \hspace{0.05cm}.$$

(3) $H_{\rm C} = H_{\rm Q}$ is still valid. However, because of the unequal symbol probabilities, $H_{\rm Q}$ is now smaller:

$$H_{\rm Q} = \frac{1}{4} \cdot {\rm log}_2\hspace{0.05cm} (4) + \frac{3}{4} \cdot {\rm log}_2\hspace{0.1cm} (4/3) {= 0.811 \,{\rm bit/binary symbol}} \hspace{0.3cm} \Rightarrow\hspace{0.3cm} H_{\rm C} = H_{\rm Q} \hspace{0.15cm} \underline {= 0.811 \,{\rm bit/ternary symbol}} \hspace{0.05cm}.$$

(4) By analogy with sub-task (2) $r_{\rm C} = 1 - 0.811/1.585 \hspace{0.15cm} \underline {= 48.8 \,\%} \hspace{0.05cm}$ now holds.

One can generalise this result. Namely, it holds:

$$(1-0.488) = (1- 0.189) \cdot (1- 0.369)\hspace{0.3cm} \Rightarrow\hspace{0.3cm} (1-r_{\rm Codefolge}) = (1-r_{\rm Quelle}) \cdot (1- r_{\rm AMI-Code}) \hspace{0.05cm}.$$

(5) Since each $\rm L$ is mapped to $\rm N$ and $\rm H$ is mapped alternately to $\rm M$ and $\rm P$, it holds that

$$p_{\rm N} = p_{\rm L} = 1/4\hspace{0.05cm},\hspace{0.2cm}p_{\rm P} = p_{\rm M} = p_{\rm H}/2 = 3/8\hspace{0.3cm} \Rightarrow\hspace{0.3cm} H_1 = {1}/{4} \cdot {\rm log}_2\hspace{0.1cm} (4) + 2 \cdot {3}/{8} \cdot {\rm log}_2\hspace{0.1cm}(8/3) \hspace{0.15cm} \underline {= 1.56 \,{\rm bit/ternary symbol}} \hspace{0.05cm}.$$

(6) Now the probabilities of occurrence of the ternary symbols are $p_{\rm N} = 3/4$ sowie $p_{\rm P} = p_{\rm M} =1/8$. Thus:

$$H_1 = {3}/{4} \cdot {\rm log}_2\hspace{0.1cm} (4/3) + 2 \cdot {1}/{8} \cdot {\rm log}_2\hspace{0.1cm}(8) \hspace{0.15cm} \underline {= 1.06 \,{\rm bit/ternary symbol}} \hspace{0.05cm}.$$

Interpretation:

For $p_{\rm L} = 1/4, \ p_{\rm H} = 3/4$ gives $H_1 = 1.56 \; \rm bit/symbol$.
For $p_{\rm L} = 3/4, \ p_{\rm H} = 1/4$ , on the other hand, $H_1 = 1.06 \; \rm bit/symbol$ results in a significantly smaller value.
For both parameter combinations, however, the same applies:

$$H_0 = 1.585 \,{\rm bit/symbol}\hspace{0.05cm},\hspace{0.2cm}H_{\rm C} = \lim_{k \rightarrow \infty } H_k = 0.811 \,{\rm bit/Symbol} \hspace{0.05cm}.$$

It follows from this:

If one considers two message sources $\rm Q1$ and $\rm Q2$ with the same symbol range $M$ ⇒ decision content $H_0 = \rm const.$, whereby the first-order entropy approximation $\rm Q1$ is clearly greater for source $(H_1)$ than for source $\rm Q2$, one cannot conclude from this by any means that the entropy of $\rm Q1$ is actually greater than the entropy of $\rm Q2$.
Rather, one must

calculate enough entropy approximations $H_1$, $H_2$, $H_3$, ... for both sources and
determine from them (graphically or analytically) the limit value of $H_k$ for $k \to \infty$ .

Only then is a final statement about the entropy ratios possible.