Which code is best described as a sequential encoder that uses memory to generate redundancy?

Which code is best described as a sequential encoder that uses memory to generate redundancy?

• A. Hamming code
• B. Reed-Solomon code
• C. Convolutional code
• D. Shannon limit

Answer: (C)

A sequential encoder that uses memory to generate redundancy relies on past inputs shaping the current output. A convolutional code fits this exactly: it uses memory elements (shift registers) and generator polynomials so each output parity bit depends on the current input plus several previous inputs. This creates redundancy that spans across the data stream, making the encoding process inherently sequential. In contrast, Hamming and Reed-Solomon are block codes—parity is generated from a fixed block of data with no memory across the stream. The Shannon limit is not a code at all but a theoretical bound on channel capacity. So the code described as using memory to generate redundancy is the convolutional code.

A sequential encoder that uses memory to generate redundancy relies on past inputs shaping the current output. A convolutional code fits this exactly: it uses memory elements (shift registers) and generator polynomials so each output parity bit depends on the current input plus several previous inputs. This creates redundancy that spans across the data stream, making the encoding process inherently sequential. In contrast, Hamming and Reed-Solomon are block codes—parity is generated from a fixed block of data with no memory across the stream. The Shannon limit is not a code at all but a theoretical bound on channel capacity. So the code described as using memory to generate redundancy is the convolutional code.