On distributed coding for relay channels

Sammanfattning: Cooperative transmission is considered to be a key-technique for increasing the robustness, the efficiency, or the coverage of wireless communication networks. The basic concept is that the information transmission from a sender to a receiver can be aided by one or several relay nodes in a cooperative manner under constraints on power, complexity or delay.The main part of this thesis is devoted to studies on practical realizations of cooperative communication systems. Coding solutions that implement the decode-and-forward protocol in three-node relay channels are proposed by employing convolutional and Turbo codes. Distributed Turbo coding (DTC) was the first technique to bring parallel code concatenation into relay networks. To complement the research on parallel concatenated codes, we propose distributed serially concatenated codes (DSCCs) which provide a better error-floor performance and an increased robustness compared with DTCs. Thereafter, we present a flexible distributed code design which can be adapted to the channel conditions in a simple way. For both the cases with perfect and limited channel-state information, the adaptive coding scheme outperforms static codes, like DTCs and DSCCs, in terms of transmission rate and application range.The aforementioned implementations of relaying are based on blockwise decoding and re-encoding at the relay. In some applications, however, these techniques are not feasible due to limited processing and storage capabilities of the relay nodes. Therefore, we propose to combine instantaneous relaying strategies with bit-interleaved coded modulation. A significant gain can be obtained by using sawtooth and constellation rearrangement relaying with optimized bit-to-symbol mappings compared with conventional instantaneous relaying strategies and compared with standard mappings optimized for point-to-point communications. Both the parameters of the instantaneous relaying schemes and the bit-to-symbol mappings are optimized to maximize mutual information.