An analytical framework integrating performance characterization and coding theory is proposed to mitigate sneak path (SP) interference in resistive random-access memory (ReRAM) crossbar arrays. The core innovation is identified in the mathematical decomposition of ReRAM’s non-ergodic data-dependent channel into multiple stationary memoryless subchannels. Through information-theoretic analysis, an approximate finite-length characterization of the theoretical lower bound for decoding word error probability (WEP) is established. This is achieved by systematically analyzing the SP occurrence rate in constrained array geometries combined with comprehensive evaluation of both mutual information and dispersion metrics across the decomposed channel components. Building upon this decomposition paradigm, a systematic code construction methodology is developed using density evolution principles for sparse-graph code design. The designed codes not only exhibit capacity-approaching decoding thresholds but also yield word error rate simulation results that are close to the derived WEP bound under practical crossbar configurations.

In this article, we explore the application of hybrid automatic repeat request (HARQ) within the intelligent reflection surface-assisted nonorthogonal multiple access (IRS-NOMA) system. We investigate the closed-form expressions for the outage probability of multiple users in the HARQ-assisted IRS-NOMA system, considering scenarios with perfect successive interference cancellation (pSIC) and imperfect successive interference cancellation (ipSIC), respectively. A definite integral approximation method for multidimensional functions based on Gauss-Chebyshev quadrature (GCQ) is proposed to conduct the performance analysis of the proposed HARQ-assisted IRS-NOMA system. Based on the asymptotic outage probability, the diversity order of multiple users for HARQ-assisted IRS-NOMA is obtained. Under the analytical results, the diversity order of the mth$(m\gt 1)$user for the HARQ-assisted IRS-NOMA with ipSIC is zero, and that of the mth user for the HARQ-assisted IRS-NOMA with pSIC is in connection with the number of reflecting elements and the number of transmission rounds. The simulation results are presented to substantiate the accuracy of the analytical results. The results demonstrate that: 1) the HARQ-assisted IRS-NOMA systems can achieve a significant gain compared with the IRS-NOMA systems; 2) the HARQ-assisted IRS-NOMA outperforms the HARQ-assisted IRS-orthogonal multiple access in terms of outage probability and diversity order; and 3) the HARQ with incremental redundancy (HARQ-IR)-assisted IRS-NOMA system has a better performance than the HARQ with chase combining (HARQ-CC)-assisted IRS-NOMA system.

In this paper, a simplified successive cancellation (SC) decoding algorithm for polar codes on insertion/deletion error channels is proposed. First, the SC decoding is designed to decode polar codes on insertion/deletion channels and the joint weight distribution is derived to measure the occurrence probability of different scenarios. Some scenarios with small occurrence probability can be pruned to obtain lower decoding complexity with negligible performance loss. Inspired by this, a fixed pruning strategy (FPS) is proposed to reduce the decoding complexity, which can prune as many scenarios as possible with the given performance requirement. By exploiting the periodicity of the joint weight distribution, the upper bound of the block error rate of the pruned SC decoding is derived. Furthermore, according to the convergence of the upper bound, a dynamic self-adjusting pruning strategy is designed to further reduce the decoding complexity and improve the flexibility of the pruning algorithm. Simulation results show that the decoding complexity of the proposed pruning-based decoding algorithms is significantly reduced compared to the state-of-the-art scenario simplified SC decoding algorithm.

Impulsive noises severely degrade the performance of a communication system. This study deals with the performance of the soft decision decoder for low‐density parity‐check codes over impulsive noise channels. To simplify the calculation of log likelihood ratio (LLR) and cooperate with the soft decision decoder, a new non‐linear approximation named inverse demapper of LLR over the impulsive noise is proposed. Without carrying the noise statistics, the inverse demapper performs close to the optimal demapper. In addition, the density evolution is employed to obtain optimal parameters of the inverse demapper. Then, the extrinsic information transfer chart analysis and simulation results are presented to verify the effectiveness of the authors' proposed demapper.

This paper tackles the problem of channel estimation and decoding in environments that exhibit time-varying block-memoryless impulsive noise. In order to perform the estimation in continuous value space and the decoding in discrete value space jointly, a novel message passing framework is proposed that combines the sampling-importance resampling (SIR) estimator and the LDPC sum-product decoder in an iterative manner. The resampling process within the framework is further improved based on the asymptotic performance analysis for mismatched decoding. The simulation results prove the validity of the enhanced SIR estimator in the proposed method and demonstrate our method can achieve better performance than the LDPC decoder with quantile estimator.