Array Gain Analysis in Molecular MIMO Communications

Martin Damrath; H. Birkan Yilmaz; Chan Byoung Chae; Peter Adam Hoeher

doi:10.1109/ACCESS.2018.2875925

Array Gain Analysis in Molecular MIMO Communications

Martin Damrath, H. Birkan Yilmaz, Chan Byoung Chae, Peter Adam Hoeher

School of Integrated Technology

Research output: Contribution to journal › Article › peer-review

23 Citations (Scopus)

Abstract

In this paper, spatial transmission techniques in the area of multiple-input multiple-output (MIMO) diffusion-based molecular communications (DBMC) are investigated. For transmitter-side spatial coding, Alamouti-type coding and repetition MIMO coding are analyzed. At the receiver-side, selection diversity and equal-gain combining are studied as combining strategies. Throughout the numerical analysis, a symmetrical 2 × 2 MIMO-DBMC system is assumed. Furthermore, a trained artificial neural network is utilized to acquire the channel impulse responses. The numerical analysis demonstrates that there is no spatial diversity gain in the DBMC system under investigation, but that it is possible to achieve an array gain instead. In addition, it is shown that for MIMO-DBMC systems repetition MIMO coding is superior to Alamouti-type coding.

Original language	English
Article number	8491259
Pages (from-to)	61091-61102
Number of pages	12
Journal	IEEE Access
Volume	6
DOIs	https://doi.org/10.1109/ACCESS.2018.2875925
Publication status	Published - 2018

Bibliographical note

Funding Information:
The work of H. B. Yilmaz and C.-B. Chae was supported in part by the Basic Science Research Program through the NRF of Korea under Grant 2017R1A1A1A05001439 and Grant 2016K2A9A1A06926542 and in part by the Ministry of Science and ICT, South Korea, through the ICT Consilience Creative Program under Grant IITP-2018-2017-0-01015.

Publisher Copyright:
© 2013 IEEE.

All Science Journal Classification (ASJC) codes

Computer Science(all)
Materials Science(all)
Engineering(all)

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10.1109/ACCESS.2018.2875925

Cite this

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title = "Array Gain Analysis in Molecular MIMO Communications",

abstract = "In this paper, spatial transmission techniques in the area of multiple-input multiple-output (MIMO) diffusion-based molecular communications (DBMC) are investigated. For transmitter-side spatial coding, Alamouti-type coding and repetition MIMO coding are analyzed. At the receiver-side, selection diversity and equal-gain combining are studied as combining strategies. Throughout the numerical analysis, a symmetrical 2 × 2 MIMO-DBMC system is assumed. Furthermore, a trained artificial neural network is utilized to acquire the channel impulse responses. The numerical analysis demonstrates that there is no spatial diversity gain in the DBMC system under investigation, but that it is possible to achieve an array gain instead. In addition, it is shown that for MIMO-DBMC systems repetition MIMO coding is superior to Alamouti-type coding.",

author = "Martin Damrath and {Birkan Yilmaz}, H. and Chae, {Chan Byoung} and Hoeher, {Peter Adam}",

note = "Funding Information: The work of H. B. Yilmaz and C.-B. Chae was supported in part by the Basic Science Research Program through the NRF of Korea under Grant 2017R1A1A1A05001439 and Grant 2016K2A9A1A06926542 and in part by the Ministry of Science and ICT, South Korea, through the ICT Consilience Creative Program under Grant IITP-2018-2017-0-01015. Publisher Copyright: {\textcopyright} 2013 IEEE.",

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doi = "10.1109/ACCESS.2018.2875925",

language = "English",

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AU - Chae, Chan Byoung

AU - Hoeher, Peter Adam

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PY - 2018

Y1 - 2018

N2 - In this paper, spatial transmission techniques in the area of multiple-input multiple-output (MIMO) diffusion-based molecular communications (DBMC) are investigated. For transmitter-side spatial coding, Alamouti-type coding and repetition MIMO coding are analyzed. At the receiver-side, selection diversity and equal-gain combining are studied as combining strategies. Throughout the numerical analysis, a symmetrical 2 × 2 MIMO-DBMC system is assumed. Furthermore, a trained artificial neural network is utilized to acquire the channel impulse responses. The numerical analysis demonstrates that there is no spatial diversity gain in the DBMC system under investigation, but that it is possible to achieve an array gain instead. In addition, it is shown that for MIMO-DBMC systems repetition MIMO coding is superior to Alamouti-type coding.

AB - In this paper, spatial transmission techniques in the area of multiple-input multiple-output (MIMO) diffusion-based molecular communications (DBMC) are investigated. For transmitter-side spatial coding, Alamouti-type coding and repetition MIMO coding are analyzed. At the receiver-side, selection diversity and equal-gain combining are studied as combining strategies. Throughout the numerical analysis, a symmetrical 2 × 2 MIMO-DBMC system is assumed. Furthermore, a trained artificial neural network is utilized to acquire the channel impulse responses. The numerical analysis demonstrates that there is no spatial diversity gain in the DBMC system under investigation, but that it is possible to achieve an array gain instead. In addition, it is shown that for MIMO-DBMC systems repetition MIMO coding is superior to Alamouti-type coding.

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Array Gain Analysis in Molecular MIMO Communications

Abstract

Bibliographical note

All Science Journal Classification (ASJC) codes

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