Exercise 4.7: Several Parallel Gaussian Channels
The channel capacity of the AWGN channel with the indicator $Y = X + N$ was given in the theory section as follows
(with the additional unit "bit"):
- $$C_{\rm AWGN}(P_X,\ P_N) = {1}/{2} \cdot {\rm log}_2\hspace{0.05cm}\left ( 1 + {P_X}/{P_N} \right )\hspace{0.05cm}.$$
The quantities used have the following meaning:
- $P_X$ is the transmission power ⇒ variance of the random variable $X$,
- $P_N$ is the noise power ⇒ variance of the random variable $N$.
If $K$ identical Gaussian channels are used in parallel, the total capacity is:
- $$C_K(P_X,\ P_N) = K \cdot C_{\rm AWGN}(P_X/K, \ P_N) \hspace{0.05cm}.$$
Here it is considered that
- in each channel the same interference power $P_N$ is present,
- thus each channel receives the same transmit power $(P_X/K)$ ,
- the total power is equal to $P_X$ exactly as in the case $K = 1$ .
In the adjacent graph, the signal space points for some digital modulation schemes are given:
- Amplitude Shift Keying (ASK),
- Binary Phase Shift Keying (BPSK),
- Quadrature Amplitude Modulation (here: 4-QAM),
- Phase Shift Keying (here: 8–PSK for GSM Evolution),
- Combined ASK/PSK Modulation (here: 16-ASK/PSK).
At the beginning of this exercise, check which $K$–parameter is valid for each method.
Hints:
- The exercise belongs to the chapter AWGN channel capacity with continuous value input.
- Reference is made in particular to the page Parallel Gaussian Channels.
- Since the results are to be given in "bit", wird "log2" is used.
Questions
Solution
- For ASK and BPSK, $\underline{K=1}$.
- For constellations 3 to 5,however, $\underline{K=2}$ (orthogonal modulation with cosine and sine).
(2) Correct is the proposed solution 2:
- For each of the channels $(1 ≤ k ≤ K)$ , the channel capacitance is $C = 1/2 \cdot \log_2 \ \big[1 + (P_X/K) /P_N) \big]$. The total capacitance is then larger by a factor of $K$ :
- $$C_K(P_X) = \sum_{k= 1}^K \hspace{0.1cm}C_k = \frac{K}{2} \cdot {\rm log}_2\hspace{0.05cm}\left ( 1 + \frac{P_X}{K \cdot P_N} \right )\hspace{0.05cm}.$$
- The proposed solution 1 is too positive. This would apply when limiting the total power to $K · P_X$ .
- Proposition 3 would imply that no capacity increase is achieved by using multiple independent channels, which is obviously not true.
(3) The table shows the results for $K = 1$, $K = 2$ and $K = 4$ , and various signa–to–noise power ratios $\xi = P_X/P_N$. For $\xi = P_X/P_N = 15$ (highlighted column), the result is:
- $K=1$: $C_K = 1/2 · \log_2 \ (16)\hspace{0.05cm}\underline{ = 2.000}$ bit,
- $K=2$: $C_K = 1/2 · \log_2 \ (8.5)\hspace{0.05cm}\underline{ = 3.087}$ bit,
- $K=4$: $C_K = 1/2 · \log_2 \ (4.75)\hspace{0.05cm}\underline{ = 4.496}$ bit.
(4) Propositions 3 and 4 are correct, as the following calculations show:
- It is already obvious from the above table that the first proposed solution must be wrong.
- We now write the channel capacity using the natural logarithm and the abbreviation $\xi = P_X/P_N$:
- $$C_{\rm nat}(\xi, K) ={K}/{2} \cdot {\rm ln}\hspace{0.05cm}\left ( 1 + {\xi}/{K} \right )\hspace{0.05cm}.$$
- Then, for large values of $K$i.e., for small values of the quotient $\varepsilon =\xi/K$ jholds:
- $${\rm ln}\hspace{0.05cm}\left ( 1 + \varepsilon \right )= \varepsilon - \frac{\varepsilon^2}{2} + \frac{\varepsilon^3}{3} - ... \hspace{0.3cm}\Rightarrow \hspace{0.3cm} C_{\rm nat}(\xi, K) = \frac{K}{2} \cdot \left [ \frac{\xi}{K} - \frac{\xi^2}{2K^2} + \frac{\xi^3}{3K^3} - \text{...} \right ]$$
- $$\hspace{0.3cm}\Rightarrow \hspace{0.3cm} C_{\rm bit}(\xi, K) = \frac{\xi}{2 \cdot {\rm ln}\hspace{0.1cm}(2)} \cdot \left [ 1 - \frac{\xi}{2K} + \frac{\xi^2}{3K^2} -\frac{\xi^3}{4K^3} + \frac{\xi^4}{5K^4} - \text{...} \right ] \hspace{0.05cm}.$$
- For $K → ∞$ , the proposed value is:
- $$C_{\rm bit}(\xi, K \rightarrow\infty) = \frac{\xi}{2 \cdot {\rm ln}\hspace{0.1cm}(2)} = \frac{P_X/P_N}{2 \cdot {\rm ln}\hspace{0.1cm}(2)} \hspace{0.05cm}.$$
- For smaller values of $K$ , the result is always a smalle $C$–value, since
- $$\frac{\xi}{2K} > \frac{\xi^2}{3K^2}\hspace{0.05cm}, \hspace{0.5cm} \frac{\xi^3}{4K^3} > \frac{\xi^4}{5K^4} \hspace{0.05cm}, \hspace{0.5cm} {\rm usw.}$$
The last row of the table shows: With $K = 4$ one is still far from the theoretical maximum $($for $K → ∞)$ for large $\xi$–values.