Because of the higher datarate imposed by the channel coder, the probability of bit error occurring in the digital channel increases relative to the value obtained when no channel coding is used. The bit interval duration must be reduced by KN K N in comparison to the no-channel-coding situation, which means the energy per bit E b E b goes down by the same amount. The bit interval must decrease by a factor of three if the transmitter is to keep up with the data stream, as illustrated here.

Because of this reduction, the error probability p e p e of the digital channel goes up. The question thus becomes does channel coding really help: Is the effective error probability lower with channel coding even though the error probability for each transmitted bit is larger? The answer is no: Using a repetition code for channel coding cannot ultimately reduce the probability that a data bit is received in error. The ultimate reason is the repetition code's inefficiency: transmitting one data bit for every three transmitted is too inefficient for the amount of error correction provided.

The repetition code represents a special case of what is known as block channel coding. For every KK bits that enter the block channel coder, it inserts an additional N−K N K error-correction bits to produce a block of NN bits for transmission. We use the notation (N,K) to represent a given block code's parameters. In the three-fold repetition code, K=1 K 1 and N=3 N 3 . A block code's coding efficiency EE equals the ratio KN K N , and quantifies the overhead introduced by channel coding. The rate at which bits must be transmitted again changes: So-called data bits bn b n emerge from the source coder at an average rate BA¯ B A and exit the channel at a rate 1E 1 E higher. We represent the fact that the bits sent through the digital channel operate at a different rate by using the index ll for the channel-coded bit stream cl c l . Note that the blocking (framing) imposed by the channel coder does not correspond to symbol boundaries in the bit stream bn b n , especially when we employ variable-length source codes.

Does any error-correcting code reduce communication errors when real-world constraints are taken into account? The answer now is yes. To understand channel coding, we need to develop first a general framework for channel coding, and discover what it takes for a code to be maximally efficient: Correct as many errors as possible using the fewest error correction bits as possible (making the efficiency KN K N as large as possible).

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This work is licensed by Don Johnson under a Creative Commons Attribution License (CC-BY 1.0), and is an Open Educational Resource.

Last edited by Connexions on Jun 5, 2009 2:36 pm GMT-5.