Difference between revisions of "Aufgaben:Exercise 3.14: Channel Coding Theorem"
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{Over which channel can error-free transmission be achieved with the R=0.32_ ? | {Over which channel can error-free transmission be achieved with the R=0.32_ ? | ||
|type="()"} | |type="()"} | ||
− | - | + | - Over both channels. |
− | - | + | - For the BSC model. |
− | + | + | + With the EUC model. |
− | - | + | - With no model. |
− | { | + | {Over which channel can error-free transmission be achieved with the rate R=0.48_ ? |
|type="()"} | |type="()"} | ||
- For both channels. | - For both channels. |
Revision as of 14:28, 23 September 2021
Shannon's channel coding theorem states that an error-free transmission can be made over a discrete memoryless channel (DMC) with the code rate R as long as R is not greater than the channel capacity
- C=max
The channel coding theorem is to be evaluated numerically in this task, whereby two typical channel models are to be considered:
- the \rm BSC model (Binary Symmetric Channel) with distortion probability ε = 0.25 and channel capacity C = 1 - H_{\rm bin}(ε),
- the \rm EUC model (from Extremely Unsymmetric Channel, this designation originates from us and is not common) according to) Exercise 3.11Z.
The graphs show the numerical values of the information-theoretical quantities for the two channels \rm BSC and \rm EUC:
- the source entropy H(X),
- the equivocation H(X|Y),
- the mutual information I(X; Y),
- the irrelevance H(Y|X), and
- the sink entropy H(Y).
The parameter in these tables is p_0 = {\rm Pr}(X = 0) in the range between p_0 = 0.3 to p_0 = 0.7.
For the second source symbol probability, p_1 = {\rm Pr}(X = 1) =1 - p_0.
Hints:
- The exercise belongs to the chapter Application to Digital Signal Transmission.
- Reference is made in particular to the page Definition and meaning of channel capacity.
Questions
Solution
- The BSC error probability is ⇒ R = 1 with p_0 = p_1 = 0.5 for uncoded transmission:
- p_{\rm B} = 0.5 \cdot 0.25 + 0.5 \cdot 0.25=0.25 \hspace{0.05cm}.
- Correspondingly, with the same boundary conditions for the EUC model::
- p_{\rm B} = 0.5 \cdot 0 + 0.5 \cdot 0.5=0.25 \hspace{0.05cm}.
(2) Proposed solution 3 is correct:
- In the BSC model with the distortion probability ε = 0.25 , for uncoded transmission ⇒ R = 1 , the bit error probability is equal to p_{\rm B} = 0.25. regardless of p_0 and p_1
- In contrast, with the EUC model, for example, a smaller bit error probability is obtained with p_0 = 0.6 and p_1 = 0.4 :
- p_{\rm B} = 0.6 \cdot 0 + 0.4 \cdot 0.5=0.2 \hspace{0.05cm}.
- Note, however, that now the source entropy is no longer H(X) = 1\ \rm (bit) but only H(X) = H_{bin} (0.6) = 0.971 \ \rm (bit).
- In the limiting case p_0 = 1 , only zeros are transmitted and H(X) = 0. For the bit error probability, however, the following then actually applies:
- p_{\rm B} = 1 \cdot 0 + 0 \cdot 0.5=0 \hspace{0.05cm}.
- So no information is transmitted, but it is transmitted with the bit error probability "zero".
(3) Proposed solution 1 is correct:
- From the graph on the information page, it can be read for the capacities of the two channels:
- C_{\rm BSC} = 0.1887 \ \rm {bit/use}, \hspace{0.5cm}C_{rm EUC} = 0.3219 \ \rm {bit/use}.
- According to the channel coding theorem, a channel coding can be found at R ≤ C with which the error probability can be made zero.
- For both channels this condition is true with rate R = 0.16 .
(4) Proposed solution 3 is correct:
- With the EUC model, the necessary condition R ≤ C for an error-free transmission is fulfilled with R = 0.32 and C = 0.3219
- However, the prerequisite for this is the probability function P_X(X) = (0.6,\ 0.4).
- In contrast, for equally probable symbols ⇒ P_X(X) = (0.5,\ 0.5) the mutual information I(X; Y) = 0.3113 would result,
i.e. a smaller value than for the channel capacity C, and I(X; Y) < R also applies. - It can be seen that the EUC model offers more potential for the application of channel coding than the BSC model. Here, for example, it can be exploited in the code that a transmitted "0" is always transmitted without errors.
(5) The comments on subtasks (3) and (4) show that theproposed solution 4 applies.