Abstract
We study the ability of recently developed variable-length constrained sequence codes to determine codeword boundaries in the received sequence upon initial receipt of the sequence and if errors in the received sequence cause synchronization to be lost. We first investigate construction of these codes based on the finite state machine description of a given constraint, and develop new construction criteria to achieve high synchronization probabilities. Given these criteria, we propose a guided partial extension algorithm to construct variable-length constrained sequence codes with high synchronization probabilities. With this algorithm we construct new codes and determine the number of codewords and coded bits that are needed to recover synchronization once synchronization is lost. We consider a large variety of constraints including the runlength limited (RLL) constraint, the DC-free constraint, the Pearson constraint and constraints for inter-cell interference mitigation in flash memories. Simulation results show that the codes we construct exhibit excellent synchronization properties, often resynchronizing within a few bits.
Highlights
Constrained sequence (CS) codes have been widely used to increase the efficiency and reliability of data storage and digital communication systems such as optical recording, magnetic recording, flash memories, DNA-based storage, cable transmission, visible light communications and wireless energy harvesting, among other applications [1]–[4]
NUMERICAL RESULTS we present results regarding the efficiency and sync probability of codes constructed based on the procedures outlined above
UPPER BOUNDS OF THE AVERAGE NUMBER OF CODEWORDS AND BITS BEFORE RESYNCHRONIZATION We first derive an upper bound on the number of codewords and the number of coded bits that are required for the decoder to regain synchronization once synchronization is lost
Summary
Constrained sequence (CS) codes have been widely used to increase the efficiency and reliability of data storage and digital communication systems such as optical recording, magnetic recording, flash memories, DNA-based storage, cable transmission, visible light communications and wireless energy harvesting, among other applications [1]–[4]. Since CS codes typically do not have strong error-correction capabilities, decoding of CS codes may result in error propagation. In practical systems CS codes are commonly used in conjunction with an interleaver and an error control code (ECC) such as an LDPC code [27], a polar code [28]–[31] or a. Product code [32]–[35] to overcome error propagation that may occur during CS decoding. Automatic repeat request (ARQ) could be used such that when errors are detected at the output of the CS decoder, the system requests retransmission until the decoded sequence is error free
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
