ISI Mitigation Techniques in Molecular Communication

Burcu Tepekule, Ali E. Pusane, H. Birkan Yilmaz, Chan Byoung Chae, Tuna Tugcu

Research output: Contribution to journalArticlepeer-review

112 Citations (Scopus)

Abstract

Molecular communication via diffusion (MCvD) is a new field of communication where molecules are used to transfer information. One of the main challenges in MCvD is the intersymbol interference (ISI), which inhibits communication at high data rates. Furthermore, at nanoscale, energy efficiency becomes an essential problem. Before addressing these problems, a pre-determined threshold for the received signal must be calculated to make a decision. In this paper, an analytical technique is proposed to determine the optimum threshold, whereas in the literature, these thresholds are calculated empirically. Since the main goal of this paper is to build an MCvD system suitable for operating at high data rates without sacrificing quality, new modulation and filtering techniques are proposed to decrease the effects of ISI and enhance energy efficiency. As a transmitter-based solution, a modulation technique, molecular transition shift keying (MTSK), is proposed in order to increase the data rate by suppressing ISI. Furthermore, for energy efficiency, a power adjustment technique that utilizes the residual molecules is proposed. Finally, as a receiver-based solution, a new energy efficient decision feedback filter (DFF) is proposed as a substitute for the conventional decoders in the literature. The error performance of DFF and MMSE equalizers are compared in terms of bit error rates, and it is concluded that DFF may be more advantageous when energy efficiency is concerned, due to its lower computational complexity.

Original languageEnglish
Article number7331300
Pages (from-to)202-216
Number of pages15
JournalIEEE Transactions on Molecular, Biological, and Multi-Scale Communications
Volume1
Issue number2
DOIs
Publication statusPublished - 2015 Jun

Bibliographical note

Publisher Copyright:
© 2015 IEEE.

All Science Journal Classification (ASJC) codes

  • Biotechnology
  • Bioengineering
  • Computer Networks and Communications
  • Electrical and Electronic Engineering
  • Modelling and Simulation

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