Update CSE5313_L26.md
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@@ -114,7 +114,7 @@ A codeword is a set of $M$ binary strings, each of length $L$.
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"Sliced channel":
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- The message 𝑚 is encoded to $c\in \{0,1\}^{ML}, and then sliced to 𝑀 equal parts.
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- The message $m$ is encoded to $c\in \{0,1\}^{ML}, and then sliced to $M$ equal parts.
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- Parts may be noisy (substitutions, deletions, etc.).
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- Also useful in network packet transmission ($M$ packets of length $L$).
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@@ -127,7 +127,7 @@ How to quantify the **merit** of a given code $\mathcal{C}$?
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Redundance:
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- Recall in linear codes,
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- $redundancy=lengt-dimension=\log (size\ of\ space)-\log (size\ of\ code)$.
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- $redundancy=length-dimension=\log (size\ of\ space)-\log (size\ of\ code)$.
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- In sliced channel:
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- $redundancy=\log (size\ of\ space)-\log (size\ of\ code)=\log \binom{2^L}{M}-\log |\mathcal{C}|$.
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@@ -393,20 +393,53 @@ Tools:
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- Want: Markers not to overlap.
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- Solution: Take markers from a Mutually Uncorrelated Codes (existing notion).
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- A code $\mathcal{M}$ is called mutually uncorrelated if no suffix of any 𝑚𝑖 ∈ ℳ if a prefix of another
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𝑚𝑗 ∈ ℳ (including 𝑖 = 𝑗).
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– Many constructions exist.
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• Theorem: For any integer ℓ there exists a mutually uncorrelated code 𝐶𝑀𝑈 of length
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ℓ and size 𝐶𝑀𝑈 ≥
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2
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ℓ
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32ℓ
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- A code $\mathcal{M}$ is called mutually uncorrelated if no suffix of any $m_i \in \mathcal{M}$ is if a prefix of another $m_j \in \mathcal{M}$ (including $i=j$).
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- Many constructions exist.
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Tool: Random encoding.
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• Want: Codewords with many markers from 𝐶𝑀𝑈, that are not too far apart.
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• Problem: Hard to achieve explicitly.
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• Workaround: Show that a uniformly random string has this property.
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• Random encoding:
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– Choose the message at random.
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– Suitable for embedding, say, printer ID.
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– Not suitable for dynamic information.
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Theorem: For any integer $\ell$ there exists a mutually uncorrelated code $\mathcal{C}_{MU}$ of length $\ell$ and size $|\mathcal{C}_{MU}|\geq \frac{2^\ell}{32\ell}$.
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#### Tool: Random encoding.
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- Want: Codewords with many markers from $\mathcal{C}_{MU}$, that are not too far apart.
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- Problem: Hard to achieve explicitly.
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- Workaround: Show that a uniformly random string has this property.
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Random encoding:
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- Choose the message at random.
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- Suitable for embedding, say, printer ID.
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- Not suitable for dynamic information.
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Let $m>0$ be a parameter.
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Fix a mutually uncorrelated code $\mathcal{C}_{MU}$ of length $\Theta(\log m)$.
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Fix $m_1,\ldots, m_t$ from $\mathcal{C}_{MU}$ as "special" markers.
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Claim: With probability $1-\frac{1}{\poly(m)}$, in uniformly random string $z\in \{0,1\}^m$.
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- Every $O(\log^2(m))$ bits contain a marker from $\mathcal{C}_{MU}$.
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- Every two non-overlapping substrings of length $c\log m$ are distinct.
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- $z$ does not contain any of the special markers $m_1,\ldots, m_t$.
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Proof idea:
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- Short substring are abundant.
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- Long substring are rare.
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#### Sketch of encoding for t-break codes.
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Repeatedly sample $z\in \{0,1\}^m$ until it is "good".
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Find all markers $m_{i_1},\ldots, m_{i_r}$ in it.
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Build a $|\mathcal{C}_{MU}|\times |\mathcal{C}_{MU}|$ matrix $A$ which records order and distances:
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- $A_{i,j}=0$ if $m_i,m_j$ are not adjacent.
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- Otherwise, it is the distance between them (in bits).
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Append $RS_{2t}(A)$ at the end, and use the special markers $m_1,\ldots, m_t$.
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#### Sketch of decoding for t-break codes.
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Construct a partial adjacency matrix $A'$ from fragments.
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