Optimization of Decision Thresholds in Two-Way Molecular Communication via Diffusion With Network Coding

Cheng, Zhen; Tu, Yuchun; Chi, Kaikai; Xia, Ming

doi:10.1109/tmbmc.2022.3182578

Cited by 6 publications

(11 citation statements)

References 31 publications

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“…As the number of released molecules increases, the average error probability decreases [267]. The higher the number of released molecules, the better the performance of the network coding approach [267]. The findings of the simulations can be explained on the one hand by the time required.…”

Section: E Performance Improvement Of Network Codingmentioning

confidence: 89%

“…The numerical simulations in [267] reveal a significantly better performance in terms of the average error probability for the network coding approach compared to no network coding [267]. As the number of released molecules increases, the average error probability decreases [267]. The higher the number of released molecules, the better the performance of the network coding approach [267].…”

Section: E Performance Improvement Of Network Codingmentioning

confidence: 94%

“…Cheng et al [267] present new network coding approaches using a combination of the decode-and-forward relaying protocol, in which the same number of molecules is released by the nanomachines, and the network coding scheme, in which different numbers of molecules are released by the nanomachines. The molecular diffusion-based communication system consists of two source nanomachines and a relay nanomachine in a three-dimensional channel.…”

Section: E Performance Improvement Of Network Codingmentioning

confidence: 99%

“…The relay R is located between the two source transmitters S 1 and S 2 . Furthermore, Cheng et al assume that the transmitters are not within each other's transmission range [267]. The three nodes are passive absorbers, i.e., the molecules can diffuse through them without a reaction taking place.…”

Section: E Performance Improvement Of Network Codingmentioning

confidence: 99%

“…In addition, an algorithm using Particle Swarm Optimization (PSO) [276] is applied in [267] to minimize the average error probability. More specifically, the PSO determines the limit value for OOK for all nanomachines in the system in order to minimize the average error probability.…”

Section: E Performance Improvement Of Network Codingmentioning

confidence: 99%

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Coding in Diffusion-Based Molecular Nanonetworks: A Comprehensive Survey

et al. 2023

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Diffusion-based molecular nanonetworks exploit the diffusion of molecules, e.g., in free space or in blood vessels, for the purpose of communication. This article comprehensively surveys coding approaches for communication in diffusion-based molecular nanonetworks. In particular, all three main purposes of coding for communication, namely source coding, channel coding, and network coding, are covered. We organize the survey of the channel coding approaches according to the different channel codes, including linear block codes, convolutional codes, and inter-symbol interference (ISI) mitigation codes. The network coding studies are categorized into duplex network coding, physical-layer network coding, multi-hop nanonetwork coding, performance improvements of network-coded nanosystems, and network coding in mobile nanonetworks. We also present a comprehensive set of future research directions for the still nascent area of coding for diffusion-based molecular nanonetworks; specifically, we outline research imperatives for each of the three main coding purposes, i.e., for source, channel, and network coding, as well as for overarching research goals.

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Section: E Performance Improvement Of Network Codingmentioning

confidence: 89%