This paper analyzes the rate-matching algorithms for LDPC codes in 5G New Radio (NR) framework. Key features of NR LDPC rate-matching design includes flexible bit-selection based on circular buffer operation, enhanced decoding latency via code construction based on a single-parity-check extension from a high rate code, systematic bit puncturing, and support for limited buffer rate-matching (LBRM). IR-HARQ is supported via several redundancy versions (RVs) defined non-uniformly over the transmit circular buffer, enabling possibility of multiple self-decodable RVs. This paper, discusses NR LDPC structure, design, and its key features, followed by an in-depth investigation of IR-HARQ functionality, rate-matching, and (re-)transmissions via different RV ordering selections. Performance of single transmissions, as well as re-transmissions using different schemes are studied and evaluated using throughput and BLER metrics. This study attests the flexibility and robustness of NR LDPC design in addition to efficient support of IR-HARQ operation.

Contemporary wireless networks are tasked with supporting different connection profiles, including real-time traffic and delay-sensitive communications. This creates a need to better understand the fundamental limits of forward error correction in non-asymptotic regimes. This paper characterizes the performance of block codes over finite-state channels and evaluates their queueing performance under maximum-likelihood decoding. Classical results from digital communications are revisited in the context of channels with rare transitions, and bounds on the probabilities of decoding failure are derived for random codes. This creates an analysis framework where channel dependencies within and across codewords are preserved. These results are subsequently integrated into a queueing problem formulation.

This paper considers the queueing performance of a communication system that transmits BCH-coded data over the correlated-error channel first studied by Gilbert and Elliott in the 1960s. For some arrival processes, one can join the queue length and channel state so that the pair forms a Markov chain; this provides a powerful tool to analyze the tail probability of the queue. For Bernoulli packet arrivals, this approach works but does not allow for fair comparisons between different block-length codes. In this paper, a Poisson arrival model is assumed in order to make fair comparisons between codes with arbitrary block length and code rate. This enables one to optimize code parameters for delay-sensitive communication systems over time-varying channels. Finally, the analysis is supported through a Monte Carlo simulation.