Spatial coding techniques for molecular MIMO

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

doi:10.1109/ITW.2017.8278035

Spatial coding techniques for molecular MIMO

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

School of Integrated Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Citations (Scopus)

Abstract

This paper presents spatial diversity techniques applied to multiple-input multiple-output (MIMO) diffusion-based molecular communications (DBMC). Two types of spatial coding techniques, namely Alamouti-type coding and repetition MIMO coding are suggested and analyzed. In addition, we consider receiver-side equal-gain combining, which is equivalent to maximum-ratio combining in symmetrical scenarios. For numerical analysis, the channel impulse responses of a symmetrical 2 × 2 MIMO-DBMC system are acquired by a trained artificial neural network. It is demonstrated that spatial diversity has the potential to improve the system performance and that repetition MIMO coding outperforms Alamouti-type coding.

Original language	English
Title of host publication	2017 IEEE Information Theory Workshop, ITW 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	324-328
Number of pages	5
ISBN (Electronic)	9781509030972
DOIs	https://doi.org/10.1109/ITW.2017.8278035
Publication status	Published - 2018 Jan 31
Event	2017 IEEE Information Theory Workshop, ITW 2017 - Kaohsiung, Taiwan, Province of China Duration: 2017 Nov 6 → 2017 Nov 10

Publication series

Name	IEEE International Symposium on Information Theory - Proceedings
Volume	2018-January
ISSN (Print)	2157-8095

Other

Other	2017 IEEE Information Theory Workshop, ITW 2017
Country/Territory	Taiwan, Province of China
City	Kaohsiung
Period	17/11/6 → 17/11/10

Bibliographical note

Funding Information:
ACKNOWLEDGMENT The work of H. B. Yilmaz and C.-B. was in part supported by the Basic Science Research Program (2017R1A1A1A05001439) through the NRF of Korea.

Publisher Copyright:
© 2017 IEEE.

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
Information Systems
Modelling and Simulation
Applied Mathematics

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10.1109/ITW.2017.8278035

Cite this

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title = "Spatial coding techniques for molecular MIMO",

abstract = "This paper presents spatial diversity techniques applied to multiple-input multiple-output (MIMO) diffusion-based molecular communications (DBMC). Two types of spatial coding techniques, namely Alamouti-type coding and repetition MIMO coding are suggested and analyzed. In addition, we consider receiver-side equal-gain combining, which is equivalent to maximum-ratio combining in symmetrical scenarios. For numerical analysis, the channel impulse responses of a symmetrical 2 × 2 MIMO-DBMC system are acquired by a trained artificial neural network. It is demonstrated that spatial diversity has the potential to improve the system performance and that repetition MIMO coding outperforms Alamouti-type coding.",

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

note = "Funding Information: ACKNOWLEDGMENT The work of H. B. Yilmaz and C.-B. was in part supported by the Basic Science Research Program (2017R1A1A1A05001439) through the NRF of Korea. Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 IEEE Information Theory Workshop, ITW 2017 ; Conference date: 06-11-2017 Through 10-11-2017",

year = "2018",

month = jan,

day = "31",

doi = "10.1109/ITW.2017.8278035",

language = "English",

series = "IEEE International Symposium on Information Theory - Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "324--328",

booktitle = "2017 IEEE Information Theory Workshop, ITW 2017",

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Damrath, M, Yilmaz, HB, Chae, CB & Hoeher, PA 2018, Spatial coding techniques for molecular MIMO. in 2017 IEEE Information Theory Workshop, ITW 2017. IEEE International Symposium on Information Theory - Proceedings, vol. 2018-January, Institute of Electrical and Electronics Engineers Inc., pp. 324-328, 2017 IEEE Information Theory Workshop, ITW 2017, Kaohsiung, Taiwan, Province of China, 17/11/6. https://doi.org/10.1109/ITW.2017.8278035

Spatial coding techniques for molecular MIMO. / Damrath, Martin; Yilmaz, H. Birkan; Chae, Chan Byoung et al.
2017 IEEE Information Theory Workshop, ITW 2017. Institute of Electrical and Electronics Engineers Inc., 2018. p. 324-328 (IEEE International Symposium on Information Theory - Proceedings; Vol. 2018-January).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AU - Damrath, Martin

AU - Yilmaz, H. Birkan

AU - Chae, Chan Byoung

AU - Hoeher, Peter Adam

N1 - Funding Information: ACKNOWLEDGMENT The work of H. B. Yilmaz and C.-B. was in part supported by the Basic Science Research Program (2017R1A1A1A05001439) through the NRF of Korea. Publisher Copyright: © 2017 IEEE.

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N2 - This paper presents spatial diversity techniques applied to multiple-input multiple-output (MIMO) diffusion-based molecular communications (DBMC). Two types of spatial coding techniques, namely Alamouti-type coding and repetition MIMO coding are suggested and analyzed. In addition, we consider receiver-side equal-gain combining, which is equivalent to maximum-ratio combining in symmetrical scenarios. For numerical analysis, the channel impulse responses of a symmetrical 2 × 2 MIMO-DBMC system are acquired by a trained artificial neural network. It is demonstrated that spatial diversity has the potential to improve the system performance and that repetition MIMO coding outperforms Alamouti-type coding.

AB - This paper presents spatial diversity techniques applied to multiple-input multiple-output (MIMO) diffusion-based molecular communications (DBMC). Two types of spatial coding techniques, namely Alamouti-type coding and repetition MIMO coding are suggested and analyzed. In addition, we consider receiver-side equal-gain combining, which is equivalent to maximum-ratio combining in symmetrical scenarios. For numerical analysis, the channel impulse responses of a symmetrical 2 × 2 MIMO-DBMC system are acquired by a trained artificial neural network. It is demonstrated that spatial diversity has the potential to improve the system performance and that repetition MIMO coding outperforms Alamouti-type coding.

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Spatial coding techniques for molecular MIMO

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