Density evolution analysis for joint iterative decoding of wireless progressive image transmission

The embedded codestream structures, associated with a variety of progressive image compression methods, suffer from severe error sensitivity when transmitted over wireless channels. In addition to employing forward error correction (FEC) codes, joint source-channel coding (JSCC) is a typical approach to combat the significant quality degradation. In this paper, a joint source-channel decoding (JSCD) method is designed when transmitting the JPEG2000 codestream over uncorrelated flat fading channels using low-density parity-check (LDPC) codes. Error resilience modes implemented in the JPEG2000 codec makes it possible to provide new messages as feedback to the channel decoder. Thus, the log-domain sum-product decoding procedure for LDPC codes is updated during each iteration according to the feedback information from the JPEG2000 decoder. Two adaptive modification algorithms are proposed to update the log-likelihood ratio (LLR) of the bit nodes at the receiver with and without channel side information (CSI), respectively. Simulation results show that the joint source-channel decoding methods not only improve the quality of the reconstructed image greatly but also reduce the number of iterations significantly.

A modified joint source-channel decoding (JSCD) algorithm based on low-density parity-check (LDPC) codes and hidden Markov estimation has been presented and extended to applying over Rayleigh fading channels. The proposed algorithm utilizes the source residual redundancy lack of any priori information of the source parameters, and the modifications employ the self-checking and convergence mechanisms of LDPC codes in adjusting the error probability of the hidden Markov model (HMM). To show the validation of the proposed JSCD methods, we also give a framework for the density evolution analysis for JSCD. Simulation results show that the joint decoding scheme on Rayleigh fading channels greatly reduces the number of iterations and improves the system performance more than 0.7 dB. Moreover, the modified JSCD algorithm leads to the joint decoder to converge at least 10% faster than the unmodified method without any degradation in the decoding performance

Low-density parity-check (LDPC) codes have been widely considered as error-correcting codes for next generation communication systems. A good LDPC decoder design requires both implementation friendly LDPC codes and efficient decoder architectures. The quality of LDPC code is crucial in determining the coding gain and implementation complexity of LDPC hardware decoders. This paper presented a genetic algorithm (GA) based LDPC code search algorithm with hardware considerations. Regular quasi-cyclic LDPC codes are used due to its friendliness to hardware implementation. Our hardware architecture design schedules pipeline LDPC decoding operation to boost the hardware utilization efficiency (HUE) of LDPC decoder. A LDPC decoder with a block size of 12288 is implemented in FPGA to validate our code and architecture design.

In this paper, we propose a concatenated code by combining a Recursive Systematic Convolutional (RSC) code with a Low-Density Parity-Check (LDPC) code. The proposed concatenated code is encoded in parallel by an RSC encoder and an LDPC encoder without interleavers between them. When decoding the proposed concatenated code, the information bits are decoded by two decoding algorithms, and soft information is exchanged between the RSC decoder and the LDPC decoder. This allows for the elimination of wrong codewords output by each decoder. The use of an LDPC code allows us to halt the decoding process when the valid codeword is obtained. We evaluate the error rate performance of the proposed concatenated code by computer simulations. We show that the proposed concatenated code does not have a high error floor, and achieves better BLock Error Rate (BLER) performance than either conventional LDPC codes or conventional turbo codes in the high Eb/No region. We also show that since the proposed concatenated code can correct wrong codewords output by each decoder, it achieves better BLER than the regular LDPC code at the same Bit Error Rate (BER).

We investigate a systematic construction of regular low density parity check (LDPC) codes based on (γργ-1, ργ, ρ, γ{0,1}) combinatorial designs. The proposed (γ,ρ) regular LDPC ensemble has rate $${\left( {1 - \tfrac{1}{\rho }} \right)^\gamma }$$ girth ≥2γ+1, and exists for all γ≥2. The codes are a subset of Gallager's random ensemble, but contains a good combination of structure and (pseudo)randomness. In particular, the simple case of γ=2 results in a class of codes that are high-rate, systematic, quasi-cyclic, linear-time encodable and decodable, and free of length-4 and length-6 cycles. Analysis on distance spectrum shows that they are better than the Gallager ensemble of the same parameters. Simulation of the proposed codes on intersymbol interference channels show that they perform comparably to random LDPC codes. Unlike random codes, the proposed structured LDPC codes can lend themselves to a low-complexity implementation for high-speed applications.

In this letter, we obtain lower and upper bounds on the minimum distance $d_{\min }$ of low-density parity-check (LDPC) codes. The bounds are derived by categorizing the non-zero code words of an LDPC code into two categories of elementary and non-elementary. The first category contains code words whose induced subgraph has only degree-2 check nodes. We propose an efficient search algorithm that can find the elementary code words of an LDPC code with weight less than a certain value $a_{\max }$ , exhaustively. We also derive a lower bound $L_{ne}$ on the weight of non-elementary code words. By performing the search with $a_{\max } = L_{ne}$ , we either obtain an elementary code word with the smallest weight $d_{\min }$ , or establish the lower bound of $L_{ne}$ on $d_{\min }$ . For the upper bound, we modify our search algorithm to reach elementary codewords of larger weights at the cost of being non-exhaustive. Once such a codeword is found, its weight acts as an upper bound on $d_{\min }$ . We examine a large number of regular and irregular LDPC codes, and demonstrate the efficiency and versatility of our technique in finding lower and upper bounds on, and in many cases the exact value of, $d_{\min }$ . Finding $d_{\min }$ , or establishing search-based lower or upper bounds, for many of the examined codes are out of the reach of any existing algorithm.

A Variable Node Processing Unit (VNPU) and a Check Node Processing Unit (CNPU) are designed in order to be used in Low Density Parity Check (LDPC) decoding by the Min-Sum Algorithm (MSA). The designed blocks are fully parallel and flexible to be used for different block length when a regular (3, 6) LDPC codes are required. The proposed VNPU and CNPU have been first designed and implemented in software using Simulink tool following a modular design approach. In a second step, these blocks were described and simulated using Very High Speed integrated circuits Hardware Description Language (VHDL). Comparison between these two implementations shows that the proposed high level methodology is efficient to test and validate digital circuits before being implemented on desired Field Programmable Gate Array (FPGA) device.

A family of rate-compatible capacity-approaching codes is obtained by spatially coupling multiple identical copies of rate-compatible base codes. The base code consists of a given regular low-density parity-check (LDPC) code and a parameter-adjustable repeat-accumulate (RA) extension. The RA-extension repeatedly accumulates all of the variable nodes of the given LDPC code by q + 1 times to generate q + 1 blocks of accumulated nodes, in which all of the accumulated variable nodes in the first q blocks and the α-fractional accumulated variable nodes in the last block are transmitted. The spatially coupled versions of the base codes, called RA-extended spatially coupled LDPC (SC-LDPC) codes, achieve arbitrary rates by simply adjusting parameters q and α, and thus they are rate-compatible. The potential thresholds of the base code ensembles are calculated to predict the iterative decoding performance of the proposed RA-extended SC-LDPC codes. Numerical results and simulations show that the authors’ proposed rate-compatible codes are capacity-approaching over binary erasure channels.

In mobile communications, the quality of signal is deteriorated by fading. The spatial diversity technique is used to reduce the degradation of the signal by fading. There are several techniques to realize the spatial diversity gain, such as Single- Input Multiple-Output (SIMO), Space-Time Block Code (STBC), and so on. The SIMO system realizes the receive diversity. The error correcting code can be combined with spatial diversity gain. Low-Density Parity Check (LDPC) codes can achieve good performance approaching Shannon limit. In particular, an irregular LDPC code with optimum degree distribution achieves better performance than a regular LDPC code. The optimum degree distribution of the irregular LDPC code depends both on the channel and the system. In this paper, we derive the Eb/No thresholds of a regular LDPC codes and the irregular LDPC codes for SIMO systems with several diversity orders. The Eb/No threshold is the smallest Eb/No that the decoder can achieve the error free. We also derive the optimum degree distributions of the irregular LDPC codes for SIMO systems with several diversity orders. We show that with low diversity order, the optimum degree distributions of the irregular LDPC code depends on the diversity order largely, while with high diversity order, the optimum degree distribution depends both on the diversity order and the combining scheme largely. We also show that comparing the optimum degree distributions for MRC and STBC, when the diversity orders are the same, the optimum degree distributions are also the same.

In this paper, in order to improve bit error performance, bandwidth efficiency and reduction of complexity compared to related schemes such as turbo codes, we combine low density parity check (LDPC) codes and continuous phase frequency shift keying (CPFSK) modulation and introduce a new scheme, called ‘low density parity check coded‐continuous phase frequency shift keying (LDPCC‐CPFSK)’. Since LDPC codes have very large Euclidean distance and use iterative decoding algorithms, they have high error correcting capacity and have very close performances to Shannon limit. In all communication systems, phase discontinuities of modulated signals result extra bandwidth requirements. Continuous phase modulation (CPM) is a powerful solution for this problem. Beside CPM provides good bandwidth efficiency; it also improves bit error performance with its memory unit. In our proposed scheme, LDPC and CPFSK, which is a special type of CPM, are considered together to improve both error performance and bandwidth efficiencies. We also obtain error performance curves of LDPCC‐CPFSK via computer simulations for both regular and irregular LDPC code. Simulation results are drawn for 4‐ary CPFSK, 8‐ary CPFSK and 16‐ary CPFSK over AWGN, Rician and Rayleigh fading channels for maximum 100 iterations, while the frame size is chosen as 504. Copyright © 2006 John Wiley & Sons, Ltd.

A modified joint source channel decoding (JSCD) algorithm based on low-density parity-check (LDPC) coding and hidden Markov estimation is proposed to employ the self-checking mechanism of LDPC codes in adjusting the error probability p of the hidden Markov model (HMM) and the JSCD scheme utilizes the source residual redundancy while no priori information of the source parameters is available. We also extend and apply the algorithm over image transmission system. Simulation results show that the modified JSCD algorithm leads to the joint decoder converge at least 10% faster than the unmodified method without any degradation in the decoding performance. The method also obtains substantial improved performance in image quality of 3.0 dB-8.0 dB (PSNR) at 0.6 dB in E <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">b</sub> /N <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sub> when it is employed in still image transmission systems

Recently, multicarrier modulation in the form of orthogonal frequency division multiplexing (OFDM) has been shown feasible for underwater acoustic communications via effective algorithms to handle the channel time-variability. In this paper, we propose to use nonbinary low density parity check (LDPC) codes to address two other main issues in OFDM: (i) plain (or uncoded) OFDM has poor performance in fading channels, and (ii) OFDM transmission has high peak to average power ratio (PAPR). We develop new methods to construct nonbinary regular and irregular LDPC codes that achieve excellent performance, match well with the underlying modulation, and can be encoded in linear time and in a parallel fashion. Based on the fact that the generator matrix of LDPC codes has high density, we further show how to reduce the PAPR considerably with minimal overhead. Experimental results confirm the excellent performance of the proposed nonbinary LDPC codes in multicarrier underwater acoustic communications.

Recently, low-density parity-check (LDPC) codes have attracted much attention especially in mobile communication system as a good simple error correcting codes achieving the data throughput near Shannon limit with lower complexity. In this paper, we design some regular LDPC codes with very low bit error rate (BER) and frame error rate (FER) according to the downlink parameters in TD-SCDMA system. We construct the downlink physical layer emulation model with matlab according to TD-SCDMA system's baseband signal disposing flow chart, and execute the link simulation with the performance analysis for some available channel codes and the designed regular LDPC codes based on the proposed emulation model. Passing the simulation, we obtain some conclusions that the regular LDPC codes are better than the convolutional codes or turbo codes in error rate performance.

Summary form only given. The ultimate performance limit or threshold of low-density parity-check (LDPC) codes is close to capacity over various memoryless channels (S.-Y. Chung, IEEE Trans. Info. Theory, vol. 47, pp. 657-670, 2001). Since the capacity of binary-input partial response (PR) channels is unknown, we estimate the capacity by calculating the threshold of capacity-approaching LDPC codes over these channels. We assume a BCJR equalizer for the channel and a sum-product message-passing decoder for the LDPC code. We also assume that the log-likelihood ratios (LLRs) in the channel BCJR and the LDPC decoder are Gaussian. We use our results to guide the design of decoder schedules that minimize the number of computationally expensive BCJR steps. The threshold calculation method can be used to optimize the left and right degree sequences of the LDPC code factor graph, using fast linear programming methods, to provide better thresholds than regular codes.

Recently, in multi-way relay systems employing physical-layer network coding (PNC), channel condition-based pair selection for pairwise information exchange has drawn increased attention as it provides improved performance over the alternative approaches such as round-robin scheduling of node pairs. With pairwise information exchange, there is additional time diversity available due to transmission of the same coded information block of most of the nodes twice in two adjacent time slots. This additional time diversity can be exploited to further enhance the system performance by means of joint channel decoding-network coding. To this end, a joint belief propagation (BP)-based channel decoding-network coding algorithm was proposed by us in [9] for the relay node of low density parity check (LDPC)-coded multi-way relay systems. Even though the algorithm of [9] offers much superior performance over separate channel decoding, it is highly computational expensive and may not be suitable for applications in wireless sensor networks. Alternatively, bit-flipping (BF)-based LDPC decoding can be adopted at much lower computational complexity. In this paper, we develop a low complexity joint bit-flipping (BF)-based channel decoding and network coding algorithm for LDPC-based multi-way relay systems. The BER performance of the proposed algorithm is investigated using computer simulation for two commonly used LDPC codes. The simulation results demonstrate that superior BER performance can be achieved using the proposed joint decoding algorithm over separate and independent bit-flipping-based LDPC channel decoding at the relay. The simulation results also verify that our proposed algorithm is capable of harnessing the aforesaid additional time diversity available. Though the performance of the proposed joint decoding algorithm is inferior to the BP-based algorithm of [9], due to its low computationally complexity, this algorithm may be appealing for applications in relay nodes with low computational capabilities and memory constraints.