Yin Xu

Improve the Performance of LDPC Coded QAM by Selective Bit Mapping in Terrestrial Broadcasting System

In this paper, we employ selective bit mapping to improve the performance of the LDPC coded QAM scheme for terrestrial DTV broadcasting system. The threshold of message-passing decoding can be considerably lowered by selectively mapping the binary components of LDPC codeword to the positions in the m-tuples to be mapped into 2mQAM symbols. In our approach, the mapping pattern is described by bit-mapping polynomials, based on which density evolution can be applied. The optimization algorithm is developed with two implementation concerns, using the Chinese DTMB standard as an example. Numerical results illustrate that our proposed approach can improve the decoding threshold by 0.05 dB to 0.499 dB depending on the code rate and the order of QAM modulation. Simulation results show that the actual BER improvement varies from 0.09 dB to 0.6 dB with different code-modulation combinations in both single-carrier and OFDM modes.

Variable LLR Scaling in Min-Sum Decoding for Irregular LDPC Codes

Min-sum decoding is a low-complexity alternative to the so-called belief propagation and consists in simplification of the nonlinear operation on the log likelihood ratios (LLRs) in the check nodes. The resulting suboptimality may be tempered via appropriate scaling of the LLRs, e.g., the fixed optimal scaling in the normalized min-sum algorithm, and variable scaling algorithms gradually appearing in the literature. However, up to now, none of the papers studied variable scaling both as per iteration and as per different check node degree, due to the prohibitive complexity of multioptimization over space of too many parameters. In this paper, we propose a generalized mutual information (GMI) of LLRs as the criterion to search for the scaling factors for different check node degrees in every iteration in a 1-D thus low-complexity manner. This approach is first analyzed via density evolution, and in addition can be extended to practical LLRs based formulas via Monte Carlo tools to cope with the mismatch issue. Bit error rate simulation results on two low-density parity-check codes show that our proposed GMI metrics have a noticeable gain over the variable scaling schemes that appeared in the literature.

An iterative decoding technique and architecture for RS concatenated TCM coding systems

In this paper, we propose a soft value modification (SVM) algorithm, based on which we further propose a new low-complexity iterative decoding technique for the conventional serial concatenated coding system which consists of Reed-Solomon (RS) code and Trellis coded Modulation (TCM) scheme with an interleaver in between. In our decoding technique, the RS decoder is based on Berlekamp-Massey (BM) algorithm, and the TCM decoder is based on Viterbi (VB) algorithm. After each iteration, the data bits and the err-flag information generated from the output of RS decoder can be fed back to the input of VB decoder as reference information, which combined with the SVM algorithm helps the VB decoder to decide whether and how to modify the corresponding soft values from the channel output. This modification approach makes the soft value more reliable than the previous version and, thus, increases the VB and RS decoders correction capacity. Extensive simulation results in different systems highlight the proposed schemes coding gain over the conventional two-stage decoding algorithm. Finally, a low-complexity architecture for hardware implementation of this novel iterative decoding technique is suggested, and the comparison with the pipeline architecture found in the literature shows the advantages of our proposal.

Variable Min-Sum decoding based on generalized mutual information metric

Min Sum algorithm simplifies the non-linear check node operation of Belief Propagation algorithm via linear approximation, which greatly reduces the complexity of realization of decoder but degrades the performance as well. The resulting sub-optimality could be tempered via scaling of LLRs, e.g. fixed optimal scaling applied to Min Sum output resulting in the Normalized Min Sum algorithm, and variable scaling schemes gradually appear in literature. In this paper, we study the variable scaling decoding algorithm, and propose to generate variable scaling sequences via generalized mutual information (GMI) metric. Simulation results on real LDPC codes for different decoding algorithms have shown that our GMI metric performs better than the variable scaling scheme appearing in literature, and meanwhile improves substantially in terms of BER over the conventional Normalized Min Sum algorithm.

Improved shortening algorithm for irregular QC-LDPC codes using known bits

Shortening is a technique to achieve rate and length adaptable low-density-parity-check (LDPC) codes. Other than the puncturing and extending techniques, shortening aims to remove certain information columns, i.e., the columns standing for the known information bits, from a given parity check matrix. In this paper, we first review the recently suggested largest-extrinsic-sum (LES) algorithm which is especially designed for quasic-cyclic (QC) LDPC codes, and then propose a method based on smallest-row-variance priority (SRVP). Moreover, we obtain both theoretical analysis and simulation results of the codes in 802.11n and 802.16e standards, which shows that: 1) the proposed SRVP algorithm always achieves better Eb/No threshold than the existing LES algorithm and generally, the shortened codes outperform the original codes; 2) severe performance degradation occurs when too many information bits are shortened for low rate codes. The proposed algorithm as well as the corresponding performance evaluations is instructive to practical applications.

Improvements to APSK constellation with gray mapping

Amplitude phase shift keying (APSK) constellation with gray mapping proposed in [2] provides considerable shaping gain compared with quadrature amplitude modulation (QAM). In this paper, some improvements to APSK Constellation with gray mapping are addressed. AP-SK constellation with gray mapping could be adjusted according to different SNR levels to increase its average mutual information (AMI). Two methods to improve AMI, on phase and on amplitude, are proposed. Both AMI of coded modulation (CM-AMI) and AMI of bit-interleaved coded modulation (BICM-AMI) are considered. The improvements are verified by bit error rate simulations in both independent and iterative demapping scenarios.

Constellation shifting based on QAM with gray coding for PAPR reduction of OFDM systems

High PAPR has long been a main drawback of OFDM systems. With the lengthening of OFDM symbol and the increasing popularity of high-order modulation, such as OFDM symbol size of 32768 and 256-QAM in DVB-T2, reducing PAPR is of growing importance. In this paper, a constellation shifting technique based on QAM with gray coding will be introduced to reduce PAPR. This technique keeps the minimum Euclidean distance of the constellation points and gray codings benefit, costs no extra bandwidth, and consumes little extra power.

Multi-rate LDPC codes for DTV transmission by known-bits padding

Modern DTV broadcasting systems, such as DVB and the Chinese DTMB system, usually have multiple code rates for forward error correction to accommodate a variety of channel conditions. In these systems, each code rate corresponds to a special set of code words, which put a limit on rate granularity and thus cannot achieve seamless code rate adaptation. To solve this problem, we propose a known-bits padding scheme to generate multi-code-rate LDPC codes of arbitrary granularity. In our scheme, we take a standardized LDPC code of specific rate as mother code, then pad known-bits according to the targeted code rate and given shortening optimization algorithm. Simulation study shows that our proposed scheme can obtain satisfying performance in terms of code rate flexibility and decoding threshold.

Variable LLR scaling in LDPC min-sum decoding under horizontal shuffled structure

LDPC was first proposed in 1962, after that considerable achievements have been made both in decoding algorithms and also in the structure of the decoder. In terms of decoding algorithm, from belief propagation (BP) to min-sum (MS), then normalized MS (NMS) and finally to a more performance oriented variable MS (VMS) algorithm. In terms of the decoder structure, there are mainly two, flooding and shuffled structure (FS and SS), and flooding structure is mainly used in the past and the selection of variable factors in FS VMS has already been studied in the literature. As is known, the horizontal shuffled structure (HSS) are more hardware friendly and now widely deployed, thus to apply VMS algorithm to HSS has an important meaning for the industry. However, there is no effective method for the selection of variable factors in HSS VMS. Based on the study of FS VMS, this paper describes how to apply the generalized mutual information (GMI) based metric to HSS VMS reasonably and proposes the modified GMI based formula. Simulation results on a certain DVB-S2s LDPC code show that, by using modified formula for HSS VMS, we can obtain 0.13dB gain over HSS NMS and the performance is only 0.1dB away from that of HSS BP in terms of bit error rate (BER) at level 1e-7. And simulation results on a certain DVB-T2s LDPC code show that, by using modified formula for HSS VMS, we can obtain 0.04dB gain over HSS NMS and the performance is only 0.06dB away from that of HSS BP in terms of bit error rate (BER) at level 1e-7.

Consideration and application of smart broadcasting

In this paper, a novel smart broadcasting system is proposed to realize efficient and reliable data distribution. Basically, the system combines the broadcasting and broadband, consisting of Brower server, middleware server, database server, broadcast server, as well as many distribution servers, FTP servers, and is based on one content recommendation algorithm in which Uniform Content Locator technique is also introduced. Besides, intelligent terminal is also presented as an output for the system. Finally, a campus based deployment of our system is described to show a case of real application.