The Encoding And Decoding Of Rateless Codes And Their Applications In Relay And Cognitive Radio Networks

With the rapid development of various wireless communication applications, the codec tech-nology ensuring reliable and efficient data transmission has attracted more and more research efforts. Because of the complexity and variability of wireless communication environment, in many cases, the transmitting side is often not able to accurately predict the channel state in-formation and design a code with a fixed rate before transmission. In addition, when applying conventional fixed-rate codes, the repeat request in case of transmission failure involves consid-erable amount of feedback messages, which reduces the transmission efficiency. Rateless codes, a new ensemble of rate-compatible and capacity-approaching channel codes, provide us a new insight in tackling the above problems. As its name implies, the coding rate of rateless codes is not fixed but adaptively variant to the channel realizations. Benefitting from its capability of forward error correction with incremental redundancy, there is no need for any feedback message to request data retransmission. The properties of error correction and rate adaption make rateless codes a feasible way of enhancing the reliability and improving the efficiency of data transmis-sion in wireless communications. This dissertation gives an intensive investigation on the design of novel encoding and decoding technologies of rateless codes and their applications in wireless relay and cognitive radio networks. The contents of this work are listed as follows:A novel belief propagation algorithm with gradual edge removal (ERBP) is proposed for the decoding of Raptor codes over additional white gaussian noise channel. Specifically, the variable nodes with sufficiently high confidence and the corresponding edges are removed grad-ually from the Tanner graph during the BP iterations so as to reduce the decoding complexity. Then considering the intrinsic nature of incremental redundancy of Raptor codes, we extend the ERBP algorithm into a progressive manner, i.e., the so-called PERBP algorithm, which not only conducts edge-removal operation but also makes use of the decoding states from the previous de-coding attempts. We prove that compared with conventional BP algorithm, both the ERBP and PERBP algorithms provide drastically reduced decoding complexity without the loss of coding performance in terms of the bit error rate.For the design of a novel class of rateless codes applicable to noisy channel, that is, the so-called accumulate rateless (AR) codes, its convergence performance of iterative decoding is analyzed and the optimal degree distribution is derived. First, by revisiting the problem of error floor suffered by LT codes over noisy channel, we point out that the post-positioned accumulator introduced by the new coding structure of AR codes is not only effective in reducing the error floor, but also quite simple for realization. Then, according to the property of rate-adaption, for both the systematic and non-systematic AR codes, the extrinsic information transfer charts and the corresponding projection of intersectant curves which effectively characterize the mutual information evolution in iterative decoding process are analyzed. Based on these, we further investigate the convergence performance of AR codes and optimize the degree distribution which leads to comparable coding performance to that of Raptor codes over noisy channel.For the application of rateless codes in wireless relay network, a concatenated channel-and-network coding approach for two-path successive relay (TPSR) network is investigated. In particular, at the source node, rateless code is used to encode the original data so as to provide resilience to any unamendable residual inter-relay interference and reduce the retransmissions, which maintains the TPSR network in steady state. Then at the relay node, by recognizing the special interference structure, a maximum-likelihood-detection-based physical-layer network coding scheme is incorporated into the forwarding scheme to exploit network diversity and im-prove system efficiency. At the destination node, based on the concatenated structure of Tanner graph of the coding approach, we design an iterative decoding algorithm to effectively recover the original data. Finally, by employing extrinsic information transfer analysis, the minimum number of required code symbols for successful data recovery is calculated, and degree distribu-tion of the employed rateless codes is optimized.For the application of rateless codes in multi-user cognitive radio (CR) networks, we investi-gate the distributed spectrum access in a multi-channel CR network and the joint feedback design in a multi-antenna CR network. In the former case, each secondary user (SU) uses rateless codes to increase the tolerance of interference from multi-user data transmission. With the purpose of protecting primary user (PU) from interference as well as maximizing the throughput of SUs, based on periodical spectrum sensing and random spectrum access model of SU, we propose a channel selection algorithm to obtain the optimal number of channels selected by SU. In the latter case, from a feedback resources allocation aspect, a joint spectrum sensing and access tradeoff framework is proposed. Firstly, by employing rateless codes, the feedback message to request data retransmission is unnecessary. Then the intrinsic relationship between multi-user coopera-tive sensing and multi-antenna beamforming is addressed. Finally, with the aim of maximizing the spectrum efficiency, we propose an optimal feedback bit allocation method to determine the proportions of the limited feedback bits allocated for both the sensing and access phases.