Decoding Rate-Compatible 5G-LDPC Codes With Coarse Quantization Using the Information Bottleneck Method
Decoding Rate-Compatible 5G-LDPC Codes With Coarse Quantization Using the Information Bottleneck Method
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DOI：
10.1109/ojcoms.2020.2994048
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发表时间：
2020-01-01
影响因子：
7.9
通讯作者：
Wesel, Richard D.
中科院分区：
文献类型：
--
作者：
Stark, Maximilian;Wang, Linfang;Wesel, Richard D.
提高的数据速率和极低延迟要求对新的5G通信标准中信道解码器的计算复杂度提出了严格的限制。实际的低密度奇偶校验（LDPC）解码器实现使用具有有限精度的消息传递解码，其随着复杂度被更严格地约束而变得粗糙。反过来，随着精度变得更粗糙，性能会降低。最近，信息瓶颈（IB）方法被用来设计相互信息最大化的映射，取代传统的有限精度节点计算。因此，IB方法中交换的消息可以用非常少量的比特来表示。5G LDPC码具有所谓的基于原型图的猛禽类（PBRL）结构，该结构提供了固有的速率兼容性和优异的性能。本文将IB原理扩展到5G中标准化的灵活类PBRL LDPC码。扩展包括用于打孔和速率兼容性的IB解码器设计。与现有的IB解码器设计技术相比，所提出的解码器可以用于具有静态优化映射集的大范围码率。建议的建设方法进行评估的一个典型的范围内的码率和位分辨率范围从3位到5位。误帧率仿真结果表明，该方案始终优于最小和译码算法，接近于双精度和积置信传播译码。此外，替代的查找表实现的互信息最大化的映射进行了研究。
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.