On the Nanocommunications at THz Band in Graphene-Enabled Wireless Network-on-Chip

Quoc-Tuan Vien, Michael Opoku Agyeman, Tuan Anh Le, Terrence Mak

Research output: Contribution to JournalArticlepeer-review

Abstract

One of the main challenges towards the growing computation-intensive applications with scalable bandwidth requirement is the deployment of a dense number of on-chip cores within a chip package. To this end, this paper investigates the Wireless Network-on-Chip (WNoC), which is enabled by graphene-based nanoantennas (GNAs) in Terahertz frequency band. We first develop a channel model between the GNAs taking into account the practical issues of the propagation medium, such as transmission frequency, operating temperature, ambient pressure and distance between the GNAs. In the Terahertz band, not only dielectric propagation loss (DPL) but also molecular absorption attenuation (MAA) caused by various molecules and their isotopologues within the chip package constitute the loss of signal transmission. We further propose an optimal power allocation to achieve the channel capacity subject to transmit power constraint. By analysing the effects of the MAA on the path loss and channel capacity, the proposed channel model shows that the MAA significantly degrades the performance at certain frequency ranges, e.g. 1.21 THz, 1.28 THz and 1.45 THz, of up to 31.8% compared to the conventional channel model, even when the GNAs are very closely located of only 0.01 mm. More specifically, at transmission frequency of 1 THz, the channel capacity of the proposed model is shown to be much lower than that of the conventional model over the whole range of temperature and ambient pressure of up to 26.8% and 25%, respectively. Finally, simulation results are provided to verify the analytical findings.
Original languageEnglish
Article number9768604
Number of pages13
JournalMathematical Problems in Engineering
Volume2017
DOIs
Publication statusPublished - 9 Jul 2017

Keywords

  • Wireless Network-on-Chip
  • nanocommunication
  • graphenna
  • channel model

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