In telecommunication, information theory, and coding theory, forward error correction ( FEC) or channel coding is a technique used for error control in data transmission over unreliable or noisy communication channels. The central idea is the sender encodes the message in a redundant way by using an errorcorrecting code (ECC).
The redundancy allows the receiver to detect a limited number of errors that may occur anywhere in the message, and often to correct these errors without retransmission. FEC gives the receiver the ability to correct errors without needing a reverse channel to request retransmission of data, but at the cost of a fixed, higher forward channel bandwidth. FEC is therefore applied in situations where retransmissions are costly or impossible, such as oneway communication links and when transmitting to multiple receivers in multicast. For example, in the case of a satellite orbiting around Uranus, a retransmission because of decoding errors can create a delay of 5 hours. FEC information is usually added to mass storage devices to enable recovery of corrupted data, is widely used in , and is used on systems where the primary memory is ECC memory.
FEC processing in a receiver may be applied to a digital bit stream or in the demodulation of a digitally modulated carrier. For the latter, FEC is an integral part of the initial analogtodigital conversion in the receiver. The Viterbi decoder implements a softdecision algorithm to demodulate digital data from an analog signal corrupted by noise. Many FEC coders can also generate a biterror rate (BER) signal which can be used as feedback to finetune the analog receiving electronics.
The maximum fractions of errors or of missing bits that can be corrected is determined by the design of the ECC, so different forward error correcting codes are suitable for different conditions. In general, a stronger code induces more redundancy that needs to be transmitted using the available bandwidth, which reduces the effective bitrate while improving the received effective signaltonoise ratio. The noisychannel coding theorem of Claude Shannon answers the question of how much bandwidth is left for data communication while using the most efficient code that turns the decoding error probability to zero. This establishes bounds on the theoretical maximum information transfer rate of a channel with some given base noise level. However, the proof is not constructive, and hence gives no insight of how to build a capacity achieving code. Fortunately, after years of research, some advanced FEC systems nowadays come very close to the theoretical maximum.

