Increased data rates and very low-latency requirements place strict constraints on the computational complexity of channel decoders in the new 5G communications standard. Practical low-density parity-check (LDPC) decoder implementations use message-passing decoding with finite precision, which becomes coarse as complexity is more severely constrained. In turn, performance degrades as the precision becomes more coarse. Recently, the information bottleneck (IB) method was used to design mutual-information-maximizing mappings that replace conventional finite-precision node computations. As a result, the exchanged messages in the IB approach can be represented with a very small number of bits. 5G LDPC codes have the so-called protograph-based raptor-like (PBRL) structure which offers inherent rate-compatibility and excellent performance. This paper extends the IB principle to the flexible class of PBRL LDPC codes as standardized in 5G. The extensions include IB decoder design for puncturing and rate-compatibility. In contrast to existing IB decoder design techniques, the proposed decoder can be used for a large range of code rates with a static set of optimized mappings. The proposed construction approach is evaluated for a typical range of code rates and bit resolutions ranging from 3 bit to 5 bit. Frame error rate simulations show that the proposed scheme always outperforms min-sum decoding algorithms and operates close to double-precision sum-product belief propagation decoding. Furthermore, alternatives to the lookup table implementations of the mutual-information-maximizing mappings are investigated.

中文翻译：

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使用信息瓶颈方法的粗量化解码速率兼容的5G-LDPC码

更高的数据速率和非常低的延迟要求对新的5G通信标准中的信道解码器的计算复杂度提出了严格的限制。实用的低密度奇偶校验（LDPC）解码器实现使用具有有限精度的消息传递解码，随着复杂度受到更严格的限制，该解码变得很粗糙。随着精度的提高，性能也会下降。最近，信息瓶颈（IB）方法用于设计互信息最大化映射，以取代常规的有限精度节点计算。结果，可以用非常少量的比特来表示IB方法中交换的消息。5G LDPC码具有所谓的基于原型的猛禽式（PBRL）结构，可提供固有的速率兼容性和出色的性能。本文将IB原理扩展到5G中标准化的PBRL LDPC码的灵活类别。这些扩展包括用于打孔和速率兼容的IB解码器设计。与现有的IB解码器设计技术相比，提出的解码器可用于带有一组静态优化映射的大范围的码率。针对3至5位范围内的典型码率和位分辨率，评估了建议的构造方法。帧误码率仿真表明，该方案始终优于最小和解码算法，并且在接近双精度和-乘积置信传播解码的情况下运行。此外，研究了互信息最大化映射的查找表实现的替代方法。