Difference between revisions of "Aufgaben:Exercise 1.16: Block Error Probability Bounds for AWGN"
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− | {{quiz-Header|Buchseite= | + | {{quiz-Header|Buchseite=Channel_Coding/Limits_for_Block_Error_Probability}} |
− | [[File:P_ID2414__KC_A_1_15.png|right|frame| | + | [[File:P_ID2414__KC_A_1_15.png|right|frame|Function Q(x) and approximations;<br>it holds: Qu(x)≤Q(x)≤Qo(x) ]] |
− | + | We assume the following constellation: | |
− | * | + | *A linear block code with code rate R=k/n and distance spectrum {Wi}, i=1, ... ,n, |
− | |||
− | |||
+ | *an AWGN channel characterized by EB/N0 ⇒ convertible to noise power σ2, | ||
− | + | *a receiver based on "soft decision" as well as the "maximum likelihood criterion". | |
+ | |||
+ | |||
+ | Under the assumption valid for the entire exercise that always the zero-word x_1=(0,0,... ,0) is sent, the [[Channel_Coding/Limits_for_Block_Error_Probability#Union_Bound_of_the_block_error_probability|"pairwise error probability"]] with a different code word x_l(l=2, ... ,2k): | ||
:Pr[x_1↦x_l]=Q(√wH(x_l)/σ2). | :Pr[x_1↦x_l]=Q(√wH(x_l)/σ2). | ||
− | + | The derivation of this relation can be found in [Liv10]. Used in this equation are: | |
− | * | + | *the [[Theory_of_Stochastic_Signals/Gaussian_Distributed_Random_Variables#Exceedance_probability|"complementary Gaussian error function"]] Q(x), |
− | * | + | |
− | + | *the [[Channel_Coding/Objective_of_Channel_Coding#Important_definitions_for_block_coding|"Hamming weight"]] w_{\rm H}(\underline{x}_{l}) of the code word \underline{x}_{l}, | |
+ | *the [[Digital_Signal_Transmission/Optimization_of_Baseband_Transmission_Systems#System_optimization_with_power_limitation|"AWGN noise power"]] \sigma^2 = (2 \cdot R \cdot E_{\rm B}/N_{0})^{-1}. | ||
− | |||
− | * | + | This allows various bounds to be specified for the block error probability: |
+ | |||
+ | *the so called [[Channel_Coding/Limits_for_Block_Error_Probability#Union_Bound_of_the_block_error_probability|"Union Bound"]] $\rm (UB)$: | ||
:p_1 = \sum_{l = 2}^{2^k}\hspace{0.05cm}{\rm Pr}[\hspace{0.05cm}\underline{x}_{\hspace{0.02cm}1} \hspace{-0.02cm}\mapsto \hspace{-0.02cm}\underline{x}_{\hspace{0.02cm}l}\hspace{0.05cm}] = \sum_{l \hspace{0.05cm}= \hspace{0.05cm}2}^{2^k}\hspace{0.05cm}{\rm Q}\left ( \sqrt{w_{\rm H}(\underline{x}_{\hspace{0.02cm}l})/\sigma^2} \right ) \hspace{0.05cm}, | :p_1 = \sum_{l = 2}^{2^k}\hspace{0.05cm}{\rm Pr}[\hspace{0.05cm}\underline{x}_{\hspace{0.02cm}1} \hspace{-0.02cm}\mapsto \hspace{-0.02cm}\underline{x}_{\hspace{0.02cm}l}\hspace{0.05cm}] = \sum_{l \hspace{0.05cm}= \hspace{0.05cm}2}^{2^k}\hspace{0.05cm}{\rm Q}\left ( \sqrt{w_{\rm H}(\underline{x}_{\hspace{0.02cm}l})/\sigma^2} \right ) \hspace{0.05cm}, | ||
− | * | + | *the so called [[Channel_Coding/Limits_for_Block_Error_Probability#Bounds_for_the_.287.2C_4.2C_3.29_Hamming_code_at_the_AWGN_channel|"Truncated Union Bound"]] $\rm (TUB)$: |
:p_2 = W_{d_{\rm min}} \cdot {\rm Q}\left ( \sqrt{d_{\rm min}/\sigma^2} \right ) \hspace{0.05cm}, | :p_2 = W_{d_{\rm min}} \cdot {\rm Q}\left ( \sqrt{d_{\rm min}/\sigma^2} \right ) \hspace{0.05cm}, | ||
− | * | + | *the [[Channel_Coding/Limits_for_Block_Error_Probability#The_upper_bound_according_to_Bhattacharyya|"Bhattacharyya Bound"]]: |
− | :$$p_3 = W(\beta) - 1\hspace{0.05cm},\hspace{0.2cm} {\rm | + | :$$p_3 = W(\beta) - 1\hspace{0.05cm},\hspace{0.2cm} {\rm with}\hspace{0.15cm} \beta = {\rm e}^{ - 1/(2\sigma^2) } \hspace{0.05cm}.$$ |
− | :In | + | :In this case, replace the distance spectrum \{W_i\} with the weight enumerator function: |
:\left \{ \hspace{0.05cm} W_i \hspace{0.05cm} \right \} \hspace{0.3cm} \Leftrightarrow \hspace{0.3cm} W(X) = \sum_{i=0 }^{n} W_i \cdot X^{i} = W_0 + W_1 \cdot X + W_2 \cdot X^{2} + ... \hspace{0.05cm} + W_n \cdot X^{n}\hspace{0.05cm}. | :\left \{ \hspace{0.05cm} W_i \hspace{0.05cm} \right \} \hspace{0.3cm} \Leftrightarrow \hspace{0.3cm} W(X) = \sum_{i=0 }^{n} W_i \cdot X^{i} = W_0 + W_1 \cdot X + W_2 \cdot X^{2} + ... \hspace{0.05cm} + W_n \cdot X^{n}\hspace{0.05cm}. | ||
− | + | In the transition from the "Union Bound" p_{1} to the more imprecise bound p_{3} among others | |
+ | *the function {\rm Q}(x) is replaced by the [https://en.wikipedia.org/wiki/Chernoff_bound "Chernoff-Rubin bound"] {\rm Q}_{\rm CR}(x). | ||
+ | |||
+ | *Both functions are shown in the above graph (red and green curve, resp.). | ||
+ | |||
+ | |||
+ | In the [[Aufgaben:Exercise_1.16Z:_Bounds_for_the_Gaussian_Error_Function|"Exercise 1.16Z"]] the relationship between these functions is evaluated numerically and referenced to the bounds {\rm Q}_{\rm o}(x) and ${\rm Q}_{\rm u}(x)$ which are also drawn in the above graph. | ||
+ | |||
− | |||
+ | Hints: | ||
+ | * This exercise belongs to the chapter [[Channel_Coding/Bounds_for_Block_Error_Probability|"Bounds for block error probability"]]. | ||
+ | * The above cited reference "[Liv10]" refers to the lecture manuscript "Liva, G.: Channel Coding. Chair of Communications Engineering, TU Munich and DLR Oberpfaffenhofen, 2010." | ||
− | + | * Further we refer to the interactive HTML5/JavaScript applet [[Applets:Komplementäre_Gaußsche_Fehlerfunktionen| "Complementary Gaussian error functions"]]. | |
− | * | ||
− | |||
− | |||
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− | === | + | ===Questions=== |
<quiz display=simple> | <quiz display=simple> | ||
− | { | + | {Which equation applies to the "Union Bound"? |
|type="[]"} | |type="[]"} | ||
- p_{1} = \sum_{l\hspace{0.05cm}=\hspace{0.05cm}2}^{2^k} W_{l} · {\rm Q}\big[(l/\sigma^2)^{0.5}\big], | - p_{1} = \sum_{l\hspace{0.05cm}=\hspace{0.05cm}2}^{2^k} W_{l} · {\rm Q}\big[(l/\sigma^2)^{0.5}\big], | ||
+ p_{1} = \sum_{i\hspace{0.05cm}=\hspace{0.05cm}1}^{n} W_{i} · {\rm Q}\big[(i/\sigma^2)^{0.5}\big]. | + p_{1} = \sum_{i\hspace{0.05cm}=\hspace{0.05cm}1}^{n} W_{i} · {\rm Q}\big[(i/\sigma^2)^{0.5}\big]. | ||
− | { | + | {Specify the Union Bound for the (8, 4, 4) code and various \sigma. |
|type="{}"} | |type="{}"} | ||
\sigma = 1.0 \text{:} \hspace{0.4cm} p_{1} \ = \ { 32.15 3% } \ \% | \sigma = 1.0 \text{:} \hspace{0.4cm} p_{1} \ = \ { 32.15 3% } \ \% | ||
\sigma = 0.5 \text{:} \hspace{0.4cm} p_{1} \ = \ { 0.0444 3% } \ \% | \sigma = 0.5 \text{:} \hspace{0.4cm} p_{1} \ = \ { 0.0444 3% } \ \% | ||
− | { | + | {Given the same boundary conditions, what does the "Truncated Union Bound" provide? |
|type="{}"} | |type="{}"} | ||
\sigma = 1.0 \text{:} \hspace{0.4cm} p_{2} \ = \ { 31.92 3% } \ \% | \sigma = 1.0 \text{:} \hspace{0.4cm} p_{2} \ = \ { 31.92 3% } \ \% | ||
\sigma = 0.5 \text{:} \hspace{0.4cm} p_{2} \ = \ { 0.044 3% } \ \% | \sigma = 0.5 \text{:} \hspace{0.4cm} p_{2} \ = \ { 0.044 3% } \ \% | ||
− | { | + | {Which statement is always true (for all constellations)? |
|type="[]"} | |type="[]"} | ||
− | + | + | + The block error probability is never greater than p_{1}. |
− | - | + | - The block error probability is never greater than p_{2}. |
− | { | + | {How do you get from p_{1} to the "Bhattacharyya Bound" p_{3}? |
|type="[]"} | |type="[]"} | ||
− | + | + | + Replace the error function {\rm Q}(x) with the function {\rm Q}_{\rm CR}(x). |
− | - | + | - Set the Bhattacharyya parameter \beta = 1/\sigma. |
− | + | + | + Instead of \{W_i\} uses the weight enumerator function W(X). |
− | { | + | {Specify the Bhattacharyya Bound for \sigma = 1 and \sigma = 0.5 . |
|type="{}"} | |type="{}"} | ||
\sigma = 1.0 \text{:} \hspace{0.4cm} p_{3} \ = \ { 191.3 3% } \ \% | \sigma = 1.0 \text{:} \hspace{0.4cm} p_{3} \ = \ { 191.3 3% } \ \% | ||
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</quiz> | </quiz> | ||
− | === | + | ===Solution=== |
{{ML-Kopf}} | {{ML-Kopf}} | ||
− | '''(1)''' | + | '''(1)''' The correct solution is <u>suggestion 2</u>: |
+ | |||
+ | *The distance spectrum \{W_i\} is defined for i = 0, \ \text{...} \ , \ n: | ||
− | + | #W_{1} indicates how often the Hamming weight w_{\rm H}(\underline{x}_{i}) = 1 occurs. | |
− | + | #W_{n} indicates how often the Hamming weight w_{\rm H}(\underline{x}_{i}) = n occurs. | |
− | + | *With that, the "Union Bound" is: | |
:p_1 = {\rm Pr(Union \hspace{0.15cm}Bound)}= \sum_{i = 1}^{n}\hspace{0.05cm}W_i \cdot {\rm Q}\left ( \sqrt{i/\sigma^2} \right ) \hspace{0.05cm}. | :p_1 = {\rm Pr(Union \hspace{0.15cm}Bound)}= \sum_{i = 1}^{n}\hspace{0.05cm}W_i \cdot {\rm Q}\left ( \sqrt{i/\sigma^2} \right ) \hspace{0.05cm}. | ||
− | '''(2)''' | + | '''(2)''' The distance spectrum of the (8, 4, 4) code was given as W_{0} = 1 , \ W_{4} = 14, \ W_{8} = 1. |
+ | *Thus, one obtains for \sigma = 1: | ||
:$$p_1 = W_4 \cdot {\rm Q}\left ( 2 \right ) + W_8 \cdot {\rm Q}\left ( 2 \cdot \sqrt{2} \right ) | :$$p_1 = W_4 \cdot {\rm Q}\left ( 2 \right ) + W_8 \cdot {\rm Q}\left ( 2 \cdot \sqrt{2} \right ) | ||
= 14 \cdot 2.28 \cdot 10^{-2}+ 1 \cdot 0.23 \cdot 10^{-2} \hspace{0.15cm}\underline{\approx 32.15\%}\hspace{0.05cm},$$ | = 14 \cdot 2.28 \cdot 10^{-2}+ 1 \cdot 0.23 \cdot 10^{-2} \hspace{0.15cm}\underline{\approx 32.15\%}\hspace{0.05cm},$$ | ||
− | + | *For \sigma = 0.5: | |
:$$p_1 = 14 \cdot {\rm Q}\left ( 4 \right ) + {\rm Q}\left ( 4 \cdot \sqrt{2} \right ) | :$$p_1 = 14 \cdot {\rm Q}\left ( 4 \right ) + {\rm Q}\left ( 4 \cdot \sqrt{2} \right ) | ||
= 14 \cdot 3.17 \cdot 10^{-5}+ 1.1 \cdot 10^{-8} \hspace{0.15cm}\underline{\approx 0.0444 \%}\hspace{0.05cm}.$$ | = 14 \cdot 3.17 \cdot 10^{-5}+ 1.1 \cdot 10^{-8} \hspace{0.15cm}\underline{\approx 0.0444 \%}\hspace{0.05cm}.$$ | ||
− | '''(3)''' | + | '''(3)''' With the minimum distance d_{\rm min} = 4 we get: |
:\sigma = 1.0\text{:} \hspace{0.4cm} p_2 \hspace{-0.15cm}\ = \ \hspace{-0.15cm} W_4 \cdot {\rm Q}\left ( 2 \right ) \hspace{0.15cm}\underline{= 31.92\%}\hspace{0.05cm}, | :\sigma = 1.0\text{:} \hspace{0.4cm} p_2 \hspace{-0.15cm}\ = \ \hspace{-0.15cm} W_4 \cdot {\rm Q}\left ( 2 \right ) \hspace{0.15cm}\underline{= 31.92\%}\hspace{0.05cm}, | ||
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− | '''(4)''' | + | '''(4)''' The correct solution is <u>suggestion 1</u>: |
− | * | + | *The "Union Bound" - denoted here by p_{1} - is an upper bound on the block error probability in all cases. |
− | * | + | |
− | * | + | *For the bound p_{2} ("Truncated Union Bound") this is not always true. |
+ | |||
+ | *For example, in the (7, 4, 3) Hamming code ⇒ W_{3} = W_{4} = 7, \ W_{7} = 1 is obtained with standard deviation \sigma = 1: | ||
:p_2 \hspace{-0.15cm}\ = \ \hspace{-0.15cm} 7 \cdot {\rm Q}\left ( \sqrt{3} \right ) = 7 \cdot 4.18 \cdot 10^{-2} \approx 0.293\hspace{0.05cm}, | :p_2 \hspace{-0.15cm}\ = \ \hspace{-0.15cm} 7 \cdot {\rm Q}\left ( \sqrt{3} \right ) = 7 \cdot 4.18 \cdot 10^{-2} \approx 0.293\hspace{0.05cm}, | ||
:p_1 \hspace{-0.15cm}\ = \ \hspace{-0.15cm} p_2 + 7 \cdot {\rm Q}\left ( \sqrt{4} \right )+ 1 \cdot {\rm Q}\left ( \sqrt{7} \right ) \approx 0.455 \hspace{0.05cm}. | :p_1 \hspace{-0.15cm}\ = \ \hspace{-0.15cm} p_2 + 7 \cdot {\rm Q}\left ( \sqrt{4} \right )+ 1 \cdot {\rm Q}\left ( \sqrt{7} \right ) \approx 0.455 \hspace{0.05cm}. | ||
− | + | *The actual block error probability is likely to be between p_{2} = 29.3\% and p_{1} = 45.5\% (but this has not been verified). <br>That is, p_{2} is not an upper bound. | |
− | '''(5)''' | + | '''(5)''' Correct are <u>suggested solutions 1 and 3</u>, as the following calculation for the (8, 4, 4) code shows: |
− | * | + | *It holds {\rm Q}(x) ≤ {\rm Q_{CR}}(x) = {\rm e}^{-x^2/2}. Thus, for the Union Bound |
:p_1 = W_4 \cdot {\rm Q}\left ( \sqrt{4/\sigma^2} \right ) +W_8 \cdot {\rm Q}\left ( \sqrt{8/\sigma^2} \right ) | :p_1 = W_4 \cdot {\rm Q}\left ( \sqrt{4/\sigma^2} \right ) +W_8 \cdot {\rm Q}\left ( \sqrt{8/\sigma^2} \right ) | ||
− | : | + | :another upper bound can be specified: |
:p_1 \le W_4 \cdot {\rm e}^{ - {4}/(2 \sigma^2) } +W_8 \cdot {\rm e}^{ - {8}/(2 \sigma^2) } \hspace{0.05cm}. | :p_1 \le W_4 \cdot {\rm e}^{ - {4}/(2 \sigma^2) } +W_8 \cdot {\rm e}^{ - {8}/(2 \sigma^2) } \hspace{0.05cm}. | ||
− | * | + | *With $\beta = {\rm e}^{-1/(2\sigma^2)}$ can be written for this also (so the given \beta = 1/\sigma is wrong): |
:p_1 \le W_4 \cdot \beta^4 + W_8 \cdot \beta^8 \hspace{0.05cm}. | :p_1 \le W_4 \cdot \beta^4 + W_8 \cdot \beta^8 \hspace{0.05cm}. | ||
− | * | + | *The weight function of the (8, 4, 4) code is: |
:$$W(X) = 1 + W_4 \cdot X^4 + W_8 \cdot X^8 \hspace{0.3cm} \Rightarrow \hspace{0.3cm} W(\beta) - 1 = W_4 \cdot \beta^4 + W_8 \cdot \beta^8\hspace{0.3cm} | :$$W(X) = 1 + W_4 \cdot X^4 + W_8 \cdot X^8 \hspace{0.3cm} \Rightarrow \hspace{0.3cm} W(\beta) - 1 = W_4 \cdot \beta^4 + W_8 \cdot \beta^8\hspace{0.3cm} | ||
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− | '''(6)''' | + | '''(6)''' With \sigma = 1, the Bhattacharyya parameter is $\beta = {\rm e}^{-0.5} = 0.6065$, and thus one obtains for the Bhattacharyya Bound: |
:p_3 = 14 \cdot \beta^4 + \beta^8 = 14 \cdot 0.135 + 0.018= 1.913 \hspace{0.15cm}\underline{= 191.3%}\hspace{0.05cm}. | :p_3 = 14 \cdot \beta^4 + \beta^8 = 14 \cdot 0.135 + 0.018= 1.913 \hspace{0.15cm}\underline{= 191.3%}\hspace{0.05cm}. | ||
− | * | + | *Considering that p_{3} is a bound for a probability, p_{3} = 1.913 is only a trivial bound. |
− | * | + | |
+ | *For \sigma = 0.5, on the other hand, $\beta = {\rm e}^{-2} \approx 0.135.$ Then holds: | ||
:p_3 = 14 \cdot \beta^4 + \beta^8 = 14 \cdot 3.35 \cdot 10^{-4} + 1.1 \cdot 10^{-7} \hspace{0.15cm}\underline{= 0.47 \%}\hspace{0.05cm}. | :p_3 = 14 \cdot \beta^4 + \beta^8 = 14 \cdot 3.35 \cdot 10^{-4} + 1.1 \cdot 10^{-7} \hspace{0.15cm}\underline{= 0.47 \%}\hspace{0.05cm}. | ||
− | + | A comparison with subtask '''(2)''' shows that in the present example the Bhattacharyya Bound p_{3} is above the "Union Bound" p_{1} by a factor | |
− | * | + | :$$(0.47 - 10^{-2})/(0.044 - 10^{-2}) > 10.$$ |
− | *In | + | |
+ | *The reason for this large deviation is the Chernoff-Rubin bound, which is well above the {\rm Q} function. | ||
+ | |||
+ | *In [[Aufgaben:Exercise_1.16Z:_Bounds_for_the_Gaussian_Error_Function|"Exercise 1.16Z"]], the deviation between {\rm Q}_{\rm CR} and {\rm Q}(x) is also calculated quantitatively: | ||
:{{\rm Q_{CR}}( x )}/{{\rm Q}( x )} \approx 2.5 \cdot x \hspace{0.3cm} \Rightarrow \hspace{0.3cm} {{\rm Q_{CR}}( x = 4 )}/{{\rm Q}( x = 4)} \approx 10 \hspace{0.05cm}. | :{{\rm Q_{CR}}( x )}/{{\rm Q}( x )} \approx 2.5 \cdot x \hspace{0.3cm} \Rightarrow \hspace{0.3cm} {{\rm Q_{CR}}( x = 4 )}/{{\rm Q}( x = 4)} \approx 10 \hspace{0.05cm}. |
Latest revision as of 17:17, 5 August 2022
We assume the following constellation:
- A linear block code with code rate R = k/n and distance spectrum \{W_i\}, \ i = 1, \ \text{...} \ , n,
- an AWGN channel characterized by E_{\rm B}/N_{0} ⇒ convertible to noise power \sigma^2,
- a receiver based on "soft decision" as well as the "maximum likelihood criterion".
Under the assumption valid for the entire exercise that always the zero-word \underline{x}_{1} = (0, 0, \text{... } \ , 0) is sent, the "pairwise error probability" with a different code word \underline{x}_{l} (l = 2,\ \text{...} \ , 2^k):
- {\rm Pr}[\hspace{0.05cm}\underline{x}_{\hspace{0.02cm}1} \hspace{-0.02cm}\mapsto \hspace{-0.02cm}\underline{x}_{\hspace{0.02cm}l}\hspace{0.05cm}] = {\rm Q}\left ( \sqrt{w_{\rm H}(\underline{x}_{\hspace{0.02cm}l})/\sigma^2} \right ) \hspace{0.05cm}.
The derivation of this relation can be found in [Liv10]. Used in this equation are:
- the "complementary Gaussian error function" {\rm Q}(x),
- the "Hamming weight" w_{\rm H}(\underline{x}_{l}) of the code word \underline{x}_{l},
- the "AWGN noise power" \sigma^2 = (2 \cdot R \cdot E_{\rm B}/N_{0})^{-1}.
This allows various bounds to be specified for the block error probability:
- the so called "Union Bound" \rm (UB):
- p_1 = \sum_{l = 2}^{2^k}\hspace{0.05cm}{\rm Pr}[\hspace{0.05cm}\underline{x}_{\hspace{0.02cm}1} \hspace{-0.02cm}\mapsto \hspace{-0.02cm}\underline{x}_{\hspace{0.02cm}l}\hspace{0.05cm}] = \sum_{l \hspace{0.05cm}= \hspace{0.05cm}2}^{2^k}\hspace{0.05cm}{\rm Q}\left ( \sqrt{w_{\rm H}(\underline{x}_{\hspace{0.02cm}l})/\sigma^2} \right ) \hspace{0.05cm},
- the so called "Truncated Union Bound" \rm (TUB):
- p_2 = W_{d_{\rm min}} \cdot {\rm Q}\left ( \sqrt{d_{\rm min}/\sigma^2} \right ) \hspace{0.05cm},
- p_3 = W(\beta) - 1\hspace{0.05cm},\hspace{0.2cm} {\rm with}\hspace{0.15cm} \beta = {\rm e}^{ - 1/(2\sigma^2) } \hspace{0.05cm}.
- In this case, replace the distance spectrum \{W_i\} with the weight enumerator function:
- \left \{ \hspace{0.05cm} W_i \hspace{0.05cm} \right \} \hspace{0.3cm} \Leftrightarrow \hspace{0.3cm} W(X) = \sum_{i=0 }^{n} W_i \cdot X^{i} = W_0 + W_1 \cdot X + W_2 \cdot X^{2} + ... \hspace{0.05cm} + W_n \cdot X^{n}\hspace{0.05cm}.
In the transition from the "Union Bound" p_{1} to the more imprecise bound p_{3} among others
- the function {\rm Q}(x) is replaced by the "Chernoff-Rubin bound" {\rm Q}_{\rm CR}(x).
- Both functions are shown in the above graph (red and green curve, resp.).
In the "Exercise 1.16Z" the relationship between these functions is evaluated numerically and referenced to the bounds {\rm Q}_{\rm o}(x) and {\rm Q}_{\rm u}(x) which are also drawn in the above graph.
Hints:
- This exercise belongs to the chapter "Bounds for block error probability".
- The above cited reference "[Liv10]" refers to the lecture manuscript "Liva, G.: Channel Coding. Chair of Communications Engineering, TU Munich and DLR Oberpfaffenhofen, 2010."
- Further we refer to the interactive HTML5/JavaScript applet "Complementary Gaussian error functions".
Questions
Solution
- The distance spectrum \{W_i\} is defined for i = 0, \ \text{...} \ , \ n:
- W_{1} indicates how often the Hamming weight w_{\rm H}(\underline{x}_{i}) = 1 occurs.
- W_{n} indicates how often the Hamming weight w_{\rm H}(\underline{x}_{i}) = n occurs.
- With that, the "Union Bound" is:
- p_1 = {\rm Pr(Union \hspace{0.15cm}Bound)}= \sum_{i = 1}^{n}\hspace{0.05cm}W_i \cdot {\rm Q}\left ( \sqrt{i/\sigma^2} \right ) \hspace{0.05cm}.
(2) The distance spectrum of the (8, 4, 4) code was given as W_{0} = 1 , \ W_{4} = 14, \ W_{8} = 1.
- Thus, one obtains for \sigma = 1:
- p_1 = W_4 \cdot {\rm Q}\left ( 2 \right ) + W_8 \cdot {\rm Q}\left ( 2 \cdot \sqrt{2} \right ) = 14 \cdot 2.28 \cdot 10^{-2}+ 1 \cdot 0.23 \cdot 10^{-2} \hspace{0.15cm}\underline{\approx 32.15\%}\hspace{0.05cm},
- For \sigma = 0.5:
- p_1 = 14 \cdot {\rm Q}\left ( 4 \right ) + {\rm Q}\left ( 4 \cdot \sqrt{2} \right ) = 14 \cdot 3.17 \cdot 10^{-5}+ 1.1 \cdot 10^{-8} \hspace{0.15cm}\underline{\approx 0.0444 \%}\hspace{0.05cm}.
(3) With the minimum distance d_{\rm min} = 4 we get:
- \sigma = 1.0\text{:} \hspace{0.4cm} p_2 \hspace{-0.15cm}\ = \ \hspace{-0.15cm} W_4 \cdot {\rm Q}\left ( 2 \right ) \hspace{0.15cm}\underline{= 31.92\%}\hspace{0.05cm},
- \sigma = 0.5\text{:} \hspace{0.4cm} p_2 \hspace{-0.15cm}\ = \ \hspace{-0.15cm}W_4 \cdot {\rm Q}\left ( 4 \right ) \approx p_1 \hspace{0.15cm}\underline{ = 0.0444 \%}\hspace{0.05cm}.
(4) The correct solution is suggestion 1:
- The "Union Bound" - denoted here by p_{1} - is an upper bound on the block error probability in all cases.
- For the bound p_{2} ("Truncated Union Bound") this is not always true.
- For example, in the (7, 4, 3) Hamming code ⇒ W_{3} = W_{4} = 7, \ W_{7} = 1 is obtained with standard deviation \sigma = 1:
- p_2 \hspace{-0.15cm}\ = \ \hspace{-0.15cm} 7 \cdot {\rm Q}\left ( \sqrt{3} \right ) = 7 \cdot 4.18 \cdot 10^{-2} \approx 0.293\hspace{0.05cm},
- p_1 \hspace{-0.15cm}\ = \ \hspace{-0.15cm} p_2 + 7 \cdot {\rm Q}\left ( \sqrt{4} \right )+ 1 \cdot {\rm Q}\left ( \sqrt{7} \right ) \approx 0.455 \hspace{0.05cm}.
- The actual block error probability is likely to be between p_{2} = 29.3\% and p_{1} = 45.5\% (but this has not been verified).
That is, p_{2} is not an upper bound.
(5) Correct are suggested solutions 1 and 3, as the following calculation for the (8, 4, 4) code shows:
- It holds {\rm Q}(x) ≤ {\rm Q_{CR}}(x) = {\rm e}^{-x^2/2}. Thus, for the Union Bound
- p_1 = W_4 \cdot {\rm Q}\left ( \sqrt{4/\sigma^2} \right ) +W_8 \cdot {\rm Q}\left ( \sqrt{8/\sigma^2} \right )
- another upper bound can be specified:
- p_1 \le W_4 \cdot {\rm e}^{ - {4}/(2 \sigma^2) } +W_8 \cdot {\rm e}^{ - {8}/(2 \sigma^2) } \hspace{0.05cm}.
- With \beta = {\rm e}^{-1/(2\sigma^2)} can be written for this also (so the given \beta = 1/\sigma is wrong):
- p_1 \le W_4 \cdot \beta^4 + W_8 \cdot \beta^8 \hspace{0.05cm}.
- The weight function of the (8, 4, 4) code is:
- W(X) = 1 + W_4 \cdot X^4 + W_8 \cdot X^8 \hspace{0.3cm} \Rightarrow \hspace{0.3cm} W(\beta) - 1 = W_4 \cdot \beta^4 + W_8 \cdot \beta^8\hspace{0.3cm} \Rightarrow \hspace{0.3cm} p_3 = W(\beta) - 1 \ge p_1\hspace{0.05cm}.
(6) With \sigma = 1, the Bhattacharyya parameter is \beta = {\rm e}^{-0.5} = 0.6065, and thus one obtains for the Bhattacharyya Bound:
- p_3 = 14 \cdot \beta^4 + \beta^8 = 14 \cdot 0.135 + 0.018= 1.913 \hspace{0.15cm}\underline{= 191.3%}\hspace{0.05cm}.
- Considering that p_{3} is a bound for a probability, p_{3} = 1.913 is only a trivial bound.
- For \sigma = 0.5, on the other hand, \beta = {\rm e}^{-2} \approx 0.135. Then holds:
- p_3 = 14 \cdot \beta^4 + \beta^8 = 14 \cdot 3.35 \cdot 10^{-4} + 1.1 \cdot 10^{-7} \hspace{0.15cm}\underline{= 0.47 \%}\hspace{0.05cm}.
A comparison with subtask (2) shows that in the present example the Bhattacharyya Bound p_{3} is above the "Union Bound" p_{1} by a factor
- (0.47 - 10^{-2})/(0.044 - 10^{-2}) > 10.
- The reason for this large deviation is the Chernoff-Rubin bound, which is well above the {\rm Q} function.
- In "Exercise 1.16Z", the deviation between {\rm Q}_{\rm CR} and {\rm Q}(x) is also calculated quantitatively:
- {{\rm Q_{CR}}( x )}/{{\rm Q}( x )} \approx 2.5 \cdot x \hspace{0.3cm} \Rightarrow \hspace{0.3cm} {{\rm Q_{CR}}( x = 4 )}/{{\rm Q}( x = 4)} \approx 10 \hspace{0.05cm}.