Relay Analysis in Molecular Communications With Time-Dependent Concentration

Wang, Xiayang; Higgins, Matthew D.; Leeson, Mark S.

doi:10.1109/lcomm.2015.2478780

Cited by 47 publications

(26 citation statements)

References 14 publications

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“…During the diffusion process, an additive signal-dependent noise, n(t), will also affect the concentration at the NB. The noise, n(t), is normally distributed with the expression given as [6,8,18,19,23]:…”

Section: The Concentration-based Molecular Communications Modelmentioning

confidence: 99%

“…If the channel is a memory unlimited channel with an infinite ISI length I, the capacity can be calculated by substituting (16), (18), (19) and (24) into (23).…”

Section: Capacity Analysismentioning

confidence: 99%

“…Referring to (16)- (19), it can be deduced that the average error probability stays constant after the i th symbol (i > I + 1). Thus, with p fixed and values of P e0 and P e1 being constant, it can be proven from (24) that: …”

Section: Capacity Analysismentioning

confidence: 99%

“…In [4], the value of the threshold is designed to maximise a posteriori probability, but the system model should be refined by considering the emission effect. Other research such as [18,19] has taken the emission process into account, and the threshold changes with regards to the previously decoded bits. However, the threshold should be further optimised to mitigate the influence of the channel memory and noise.…”

Section: Introductionmentioning

confidence: 99%

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An optimal decoding algorithm for Molecular Communications systems with noise, memory, and pulse width

Wang

Higgins

et al. 2016

Nano Communication Networks

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Molecular Communications (MC) is a promising paradigm to achieve message exchange between nano-machines. Due to the specific characteristics of MC systems, the channel noise and memory significantly influence the MC system performance. Aiming to mitigate the impact of these two factors, an adaptive decoding algorithm is proposed by optimising the symbol determination threshold. In this paper, this novel decoding scheme is deployed onto a concentration-based MC system with the transmitter emission process considered. To evaluate the performance, an information theoretical approach is developed to derive the Bit Error Rate (BER) and the channel capacity. Simulations are also carried out to verify the accuracy of these formulations, to compare the performance difference against other decoding schemes, and to illustrate the performance deviation caused by different designing of relevant parameters. Furthermore, the performance of MC systems with the distance unknown is also analysed. Comparisons between distance-pre-known and distance-unknown systems are provided.

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Section: The Concentration-based Molecular Communications Modelmentioning

confidence: 99%

“…If the channel is a memory unlimited channel with an infinite ISI length I, the capacity can be calculated by substituting (16), (18), (19) and (24) into (23).…”

Section: Capacity Analysismentioning

confidence: 99%

Section: Capacity Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

An optimal decoding algorithm for Molecular Communications systems with noise, memory, and pulse width

Wang

Higgins

et al. 2016

Nano Communication Networks

Self Cite

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show abstract

“…Likewise, several researchers have proposed static relays to improve reliability [1], [12]- [14], but this maybe hard to implement in fluidic environments, as it requires premature planning with prior knowledge of stochastic diffusion propagation paths. Inspired by nature, some bacteria can act as mobile relays for carrying DNA encoded messages (i.e., plasmids) and navigate complex in vivo channels and overcoming the aforementioned environmental changes.…”

Section: Introductionmentioning

confidence: 99%