Symbol-Level Synchronization Channel Modeling With Real-World Application: From Davey-MacKay, Fritchman to Markov

被引:1
|
作者
Achari, Shamin [1 ]
Holmes, Daniel G. [1 ]
Cheng, Ling [1 ]
机构
[1] Univ Witwatersrand, Sch Elect & Informat Engn, ZA-2000 Johannesburg, South Africa
来源
IEEE ACCESS | 2021年 / 9卷
基金
新加坡国家研究基金会;
关键词
Synchronization; Channel models; Mathematical model; Hidden Markov models; Markov processes; Data models; DNA; Channel modeling; finite-state Markov channel; memory models; synchronization models; COMMUNICATION; MEMORY; NOISE;
D O I
10.1109/ACCESS.2021.3084115
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Errors in realistic channels contain not only substitution errors, but synchronization errors as well. Moreover, these errors are rarely statistically independent in nature. By extending on the idea of the Fritchman channel model, a novel error category-based methodology for determining channel characteristics is described for memory channels that contain insertion, deletion, and substitution errors. The practicality of such a methodology is reinforced by making use of real communication data from a visible light communication system. Simulation results show that the error-free and error runs using this new method of defining the channel clearly deviates from the Davey-MacKay synchronization model which is memoryless in nature. This further emphasizes the inherent memory in these synchronization channels which we are now able to characterize. Additionally, a new method to determine the parameters of a synchronization memory channel using the Levenshtein distance metric is detailed. This method of channel modeling allows for more realistic communication models to be simulated and can easily extend to other areas of research such as DNA barcoding in the medical domain.
引用
收藏
页码:79752 / 79765
页数:14
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