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.
|Title of host publication||2017 IEEE Information Theory Workshop, ITW 2017|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Number of pages||5|
|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
|Name||IEEE International Symposium on Information Theory - Proceedings|
|Other||2017 IEEE Information Theory Workshop, ITW 2017|
|Country||Taiwan, Province of China|
|Period||17/11/6 → 17/11/10|
Bibliographical noteFunding 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.
© 2017 IEEE.
All Science Journal Classification (ASJC) codes
- Theoretical Computer Science
- Information Systems
- Modelling and Simulation
- Applied Mathematics