Capacity bounds of neuro-spike communication by exploiting temporal modulations

Keyvan Aghababaiyan, Vahid Shah-Mansouri, Behrouz Maham

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Citations (Scopus)

Abstract

We consider a neuro-spike communication system between two nano-machines, with information conveyed in the time intervals of the input spike train. The main contribution of our paper is modeling of the neuro-spike communication channel by an additive Gamma noise channel model. In this channel, the information is corrupted by Gamma distributed noise. We show that the proposed channel model is efficient for the neuro-spike communication when it exploits temporal modulations to transfer information. Then, we consider the Gamma distributed noise and we derive the upper and lower bounds on the channel capacity. Unlike Additive White Gaussian Noise (AWGN) channels, there is no single quality measure like signal-to-noise ratio for this channel model. Thus, we analyze the channel capacity bounds versus different values of time intervals and the decision threshold of the receiver.

Original languageEnglish
Title of host publication2018 IEEE Wireless Communications and Networking Conference, WCNC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-6
Number of pages6
Volume2018-April
ISBN (Electronic)9781538617342
DOIs
Publication statusPublished - Jun 8 2018
Event2018 IEEE Wireless Communications and Networking Conference, WCNC 2018 - Barcelona, Spain
Duration: Apr 15 2018Apr 18 2018

Other

Other2018 IEEE Wireless Communications and Networking Conference, WCNC 2018
CountrySpain
CityBarcelona
Period4/15/184/18/18

Keywords

  • Capacity bounds
  • Gamma distribution
  • Neuro-spike communication
  • Temporal modulation

ASJC Scopus subject areas

  • Engineering(all)

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