Operational Channel Capacity = Information Channel Capacity We prove a bunch of propositions leading up to this We only actually prove the equality for a Binary Symmetric Channel (BSC).

Proposition

For a Discrete Memoryless Channel (DMC)

Proof

Let be the Information Channel Capacity. Suppose we can Transmit Reliably at rate i.e. there is a sequence of codes with of length and size such that as . The error probability defined as:

is clearly (i.e. smaller than the max error probability)

Take Random Variable to be the input uniformly distributed over , and be the output when is transmitted and decoded. So, say Then by Fano’s Inequality write:

Thus the sequence of codes doesn’t exist

Proposition

Consider a Binary Symmetric Channel (BSC) with error probability . Let . Then there is a sequence of codes of length and size s.t. as .

Proof

WLOG so there is some s.t. Using minimum distance Decoding rule Let We pick an Binary Code at random (i.e. each with probability ) Say Choose at random (i.e. each with probability ) We send through the channel and get output

It suffices to show

Let

Now consider those two separately

If

Proposition

Consider a Binary Symmetric Channel (BSC) with error probability . Let . Then there is a sequence of codes with of length , size and as

Proof

Pick s.t. . By previous, we construct a sequence of codes with of length and size and as Throwing out the worst half of the codewords in gives a code with

so as Note has length and size for sufficiently large. So we can replace by a subcode of size of and still get as