A Turbo Coding System for High Speed Communications
Yan-Xiu Zheng, Yu T. Su
Abstract
Conventional turbo codes (CTCs) usually employ a block-oriented interleaving so that each block is separately encoded and decoded. As interleaving and de-interleaving are performed within a block, the message-passing process associated with an iterative decoder is limited to proceed within the corresponding range. This paper presents a new turbo coding scheme that uses a special interleaver structure and a multiple-round early termination test involving both sign check and a CRC code. The new interleaver structure is naturally suited for high speed parallel processing and the resulting coding system offers new design options and tradeoffs that are not available to CTCs. In particular, it becomes possible for the decoder to employ an efficient inter-block collaborative decoding algorithm, passing the information obtained from termination test proved blocks to other unproved blocks. It also becomes important to have a proper decoding schedule. The combined effect is improved performance and reduction in the average decoding delay (whence the required computing power). A memory (storage) management mechanism is included as a critical part of the decoder so as to provide additional design tradeoff between performance and memory size. It is shown that the latter has a modular-like effect in that additional memory units render enhanced performance due not only to less forced early terminations but to possible increases of the interleaving depth. Depending on the decoding schedule, the degree of parallelism and other decoding resources available, the proposed scheme admits a variety of decoder architectures that meet a large range of throughput and performance demands.
Create a lesson
Related papers
Deterministic Identification over Additive Gaussian Channels
Jonathan E. W. Huffmann, Holger Boche
Knowledge Distillation Driven Semantic NOMA with GAN Refinement for 6G Robotic Vehicle Networks
Qifei Wang, Zhen Gao, Li Qiao et al.
Real-Time Reconstruction of Markov Sources over MPR Channels
Pansee S. Elessawy, Nikolaos Pappas
Minimum Rate For Partially Observable Linear System with Side Information: LQG Plant and Gaussian-Markov Source
Sijie Li, Hyeji Kim
Spectral Approximation and Ergodic-Capacity Convergence of HMIMO Channels under Spatial-Wavenumber Domain Mismatch
Hangsong Yan, Hong Yang, Shu Sun
Sharp Minimax Regret for Infinite-Memory Logistic Prediction
Vaneet Aggarwal