Code design for energy harvesting and Joint energy and information transfer Using run length limited codes

Energy harvesting wireless networks and networks that bene t from wireless energy transfer have become popular in the last decade. In these networks, the users can obtain the required energy for transmission from an external source, which eliminates the need of battery replacement. Therefore, such networks have a high potential for applications in different areas including wireless sensor networks, wireless body networks and Internet of Things (IoT). While there have been many advancements for energy harvesting communications and joint energy and information transfer from information and communication theoretic perspectives in the literature, these subjects have not been studied from a practical coding and transmission point of view in depth. With the above motivation, in this thesis, we propose a serially concatenated coding scheme to communicate over binary energy harvesting communication channels with additive white Gaussian noise (AWGN), and design explicit and implementable codes for both long and short block lengths. Run length limited (RLL) codes are used to induce the required nonuniform input distributions for both cases. We employ low density parity check (LDPC) codes for long block lengths, while for short block length designs, we utilize convolutional codes for error correction. We consider different decoding approaches for the two cases, i.e., an iterative decoder is used for the former while Bahl-Cocke-Jelinek-Raviv (BCJR) algorithm over the product trellis of the convolutional and run length limited codes is used for the latter. Also, by noticing that similar coding solutions can be employed, we extend our work to joint energy and information transfer for both scenarios. Numerical examples demonstrate that the newly optimized codes with an inner RLL code are superior to the point-to-point optimal codes for AWGN channels for long block lengths when energy harvesting or joint energy and information transfer is considered, and that, for the short block length case, concatenated convolutional and RLL codes with higher minimum distances offer excellent performance.