Browsing by Subject "channel coding"
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Item Advanced channel coding techniques using bit-level soft information(2009-06-02) Jiang, JingIn this dissertation, advanced channel decoding techniques based on bit-level soft information are studied. Two main approaches are proposed: bit-level probabilistic iterative decoding and bit-level algebraic soft-decision (list) decoding (ASD). In the ?rst part of the dissertation, we ?rst study iterative decoding for high density parity check (HDPC) codes. An iterative decoding algorithm, which uses the sum product algorithm (SPA) in conjunction with a binary parity check matrix adapted in each decoding iteration according to the bit-level reliabilities is proposed. In contrast to the common belief that iterative decoding is not suitable for HDPC codes, this bit-level reliability based adaptation procedure is critical to the conver-gence behavior of iterative decoding for HDPC codes and it signi?cantly improves the iterative decoding performance of Reed-Solomon (RS) codes, whose parity check matrices are in general not sparse. We also present another iterative decoding scheme for cyclic codes by randomly shifting the bit-level reliability values in each iteration. The random shift based adaptation can also prevent iterative decoding from getting stuck with a significant complexity reduction compared with the reliability based parity check matrix adaptation and still provides reasonable good performance for short-length cyclic codes. In the second part of the dissertation, we investigate ASD for RS codes using bit-level soft information. In particular, we show that by carefully incorporating bit?level soft information in the multiplicity assignment and the interpolation step, ASD can significantly outperform conventional hard decision decoding (HDD) for RS codes with a very small amount of complexity, even though the kernel of ASD is operating at the symbol-level. More importantly, the performance of the proposed bit-level ASD can be tightly upper bounded for practical high rate RS codes, which is in general not possible for other popular ASD schemes. Bit-level soft-decision decoding (SDD) serves as an e?cient way to exploit the potential gain of many classical codes, and also facilitates the corresponding per-formance analysis. The proposed bit-level SDD schemes are potential and feasible alternatives to conventional symbol-level HDD schemes in many communication sys-tems.Item Coding with side information(Texas A&M University, 2005-11-01) Cheng, SzemingSource coding and channel coding are two important problems in communications. Although side information exists in everyday scenario, the effect of side information is not taken into account in the conventional setups. In this thesis, we focus on the practical designs of two interesting coding problems with side information: Wyner-Ziv coding (source coding with side information at the decoder) and Gel??fand-Pinsker coding (channel coding with side information at the encoder). For WZC, we split the design problem into the two cases when the distortion of the reconstructed source is zero and when it is not. We review that the first case, which is commonly called Slepian-Wolf coding (SWC), can be implemented using conventional channel coding. Then, we detail the SWC design using the low-density parity-check (LDPC) code. To facilitate SWC design, we justify a necessary requirement that the SWC performance should be independent of the input source. We show that a sufficient condition of this requirement is that the hypothetical channel between the source and the side information satisfies a symmetry condition dubbed dual symmetry. Furthermore, under that dual symmetry condition, SWC design problem can be simply treated as LDPC coding design over the hypothetical channel. When the distortion of the reconstructed source is non-zero, we propose a practical WZC paradigm called Slepian-Wolf coded quantization (SWCQ) by combining SWC and nested lattice quantization. We point out an interesting analogy between SWCQ and entropy coded quantization in classic source coding. Furthermore, a practical scheme of SWCQ using 1-D nested lattice quantization and LDPC is implemented. For GPC, since the actual design procedure relies on the more precise setting of the problem, we choose to investigate the design of GPC as the form of a digital watermarking problem as digital watermarking is the precise dual of WZC. We then introduce an enhanced version of the well-known spread spectrum watermarking technique. Two applications related to digital watermarking are presented.Item On distributed coding, quantization of channel measurements and faster-than-Nyquist signaling(Texas A&M University, 2006-04-12) Liveris, Angelos DimitriouThis dissertation considers three different aspects of modern digital communication systems and is therefore divided in three parts. The first part is distributed coding. This part deals with source and source- channel code design issues for digital communication systems with many transmitters and one receiver or with one transmitter and one receiver but with side information at the receiver, which is not available at the transmitter. Such problems are attracting attention lately, as they constitute a way of extending the classical point-to-point communication theory to networks. In this first part of this dissertation, novel source and source-channel codes are designed by converting each of the considered distributed coding problems into an equivalent classical channel coding or classical source-channel coding problem. The proposed schemes come very close to the theoretical limits and thus, are able to exhibit some of the gains predicted by network information theory. In the other two parts of this dissertation classical point-to-point digital com- munication systems are considered. The second part is quantization of coded chan- nel measurements at the receiver. Quantization is a way to limit the accuracy of continuous-valued measurements so that they can be processed in the digital domain. Depending on the desired type of processing of the quantized data, different quantizer design criteria should be used. In this second part of this dissertation, the quantized received values from the channel are processed by the receiver, which tries to recover the transmitted information. An exhaustive comparison of several quantization cri- teria for this case are studied providing illuminating insight for this quantizer design problem. The third part of this dissertation is faster-than-Nyquist signaling. The Nyquist rate in classical point-to-point bandwidth-limited digital communication systems is considered as the maximum transmission rate or signaling rate and is equal to twice the bandwidth of the channel. In this last part of the dissertation, we question this Nyquist rate limitation by transmitting at higher signaling rates through the same bandwidth. By mitigating the incurred interference due to the faster-than-Nyquist rates, gains over Nyquist rate systems are obtained.