Coding Techniques for Noisy Channels with Gain and/or Offset Mismatch

Abstract

Data transmission is ubiquitous in all walks of life, ranging from basic home and office appliances like compact disc players and hard disk drives to deep space communication. More often than not, the communication and storage channels are noisy, and data might be distorted during transmission. However, noise is not the only disturbance during the data transmission, and information can sometimes be seriously distorted by the phenomena of unknown channel gain or offset (drift) mismatch. The conventional minimum Euclidean distance based detection, where the receiver picks a codeword from the codebook to minimize the Euclidean distance with the received word, has a poor performance under the gain and/or offset mismatch. Recently, a Pearson distance based detection was introduced, which is immune to unknown offset and/or gain mismatch, but the drawback is that it is pretty sensitive to errors caused by the noise. This thesis investigates possible coding techniques to improve decoders’ performance in noisy channel conditions while maintaining the resistance against the gain and/or offset mismatch. The results discussed in the thesis are divided into four parts, based on different assumptions on the gain and/or offset mismatch.