ADAPTIVE AUTOMATIC REPEAT REQUEST SCHEMES FOR DIGITAL COMMUNICATION SYSTEMS

Abstract

Hybrid automatic repeat request (ARQ) schemes are packet retransmission techniques employing error correction and error detection coding to achieve reliable digital communication over noisy channels. It is currently accepted that error-control coding is a practical technique for increasing the transmission efficiency of virtually all digital communication channels. An important step in the design of a coded communication system is the selection of an appropriate code rate which matches the channel noise condition. As most communication channels are time-varying or nonstationary, to achieve efficient data transmission over such channels, the system must be made adaptive to the time varying channel noise condition. The main shortcoming of existing ARQ schemes motivated the work that will be described in this thesis. Three adaptive hybrid ARQ schemes employing trellis codes and Viterbi decoding are proposed and their performances are studied. In conventional type I hybrid ARQ schemes with fixed code rate, the code rate of the error-correction code must be carefully chosen to match the channel bit error rate (BER), in order to maximize the system throughput. Whenever there is a mismatch between the code rate and the channel BER, the throughput suffers. Therefore, it is highly desirable to design a scheme that can dynamically match its code rate to the channel BERs. In chapter two, we present a rate adaptive ARQ scheme using punctured convolutional codes. This proposed ARQ scheme can automatically adjust its code rates to match either channel BBR in binary symmetry channel (BSC) or channel signal-to-noise ratio (SNR) in additive white Gaussian noise (A WON) channel. Trellis coded modulation (TCM), pioneered by Ungerboeck, has recently become widely used for achieving power efficient communication over bind-limited channels. A TCM ARQ scheme employing sequence combining over nonstationary block interference (BI) A WGN channel is presented in chapter three. This scheme uses sequence combining to adapt to the channel conditions instead of adjusting its code rates. Chapter four discusses a rate adaptive ARQ scheme using pragmatic TCM in A WGN channel. This scheme is an extension of the scheme presented in chapter two. The ARQ scheme in chapter two is power efficient only due to the use of binary convolutional codes, whereas the scheme in chapter four is both bandwidth and power efficient due to the use of pragmatic TCM and soft decision Viterbi decoding. The adaptive ARQ schemes proposed in chapters two to four are best suited for slowly time-varying channels. However, many digital communication channels are fast time-varying, and such channels may be modeled by Markov chains. A proposal for future research on ARQ schemes over Markov chain channel models is given in chapter five.