CS代写 COMP2610/COMP6261 – Information Theory Tutorial 9: Stream and Noisy Channel

COMP2610/COMP6261 – Information Theory Tutorial 9: Stream and Noisy Channel Coding
Young Lee and
Tutors: and
Week 11 (16th – 20th Oct), Semester 2, 2017

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1. Complete arithmetic coding (Question 4, Tutorial 8) from previous tutorial if you have not completed. 2. Consider a channel with inputs X = {a, b, c}, outputs Y = {a, b, c, d}, and transition matrix
0.5 0 0 Q=0.5 0.5 0.
 0 0 . 5 0 . 5  0 0 0.5
(a) Assuming pX = (0.25, 0.25, 0.5), what is the mutual information I(X; Y ) between the input and output of the channel?
(b) Assuming pX = (0.25, 0.25, 0.5), what is the average probability of error of the channel?
(c) Calvin claims that he has constructed a block code for Q with rate 0.01 bits per transmission and maximal
block error probability 1%. Is his claim possible? Justify your answer.
(d) Hobbes claims that he has constructed a block code for Q with rate 100 bits per transmission and maximal block error probability 1%. Is his claim possible? Justify your answer.
3. Noisy Coding (Exercise 10.12 in MacKay)
(a) A binary erasure channel with input x ∈ {0, 1} and output y ∈ {0, ?, 1} has transition matrix
1−q 0 QE= q q .
0 1−q FindthemutualinformationI(X;Y)betweentheinputandoutputforageneraldistributionpX =(p0,p1)
over inputs. Show that the capacity of this channel is CE = 1 − q bits.
(b) A Z-channel has transition probability matrix
􏰋1 q􏰌 QZ = 0 1−q .
Show that, using a (2, 1) code, that two uses of a Z -channel can be made to emulate one use of an erasure channel, and state the erasure probability of that erasure channel. Hence show the capacity of the Z-channel CZ ≥ 21 (1 − q) = 12 CE bits.
Explain why this result is an inequality rather than an equality.

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