Return
Minimal Sets for Capacity-Approaching Variable-Length Constrained Sequence Codes
DOI:10.1109/TCOMM.2018.2873345.png)
Abstract
En 中文
The use of constrained sequence (CS) codes is important for the robust operation of transmission and data storage systems. While most analysis and development of CS codes have focused on fixed-length codes, recent research has demonstrated the advantages of variable-length CS codes. In our design of capacity-approaching variable-length CS codes, the construction of minimal sets is critical. In this paper, we propose an approach to construct minimal sets for a variety of constraints based on the finite-state machine (FSM) description of CSs. We develop three criteria to select the optimal state of the FSM that enables the design of a single-state encoder that results in the highest maximum possible code rate, and we apply these criteria to several constraints to illustrate the advantages that can be achieved. We then introduce FSM partitions and propose a recursive construction algorithm to establish the minimal set of the specified state. Finally, we present the construction of single-state capacity-approaching variable-length CS codes to show the improved efficiency and reduced implementation complexity that can be achieved compared with CS codes currently in use.
Keywords:
Constrained sequence codes
variable-length codes
capacity-approaching codes
single-state codes
DC-free codes
run-length-limited codes
visible light communication
DNA-based storage
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
8.3
Papers:
1.2W
Citations:
3.6W

