Array Gain Analysis in Molecular MIMO Communications
IEEE Access, cilt.6, ss.61091-61102, 2018 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 6
- Basım Tarihi: 2018
- Doi Numarası: 10.1109/access.2018.2875925
- Dergi Adı: IEEE Access
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
- Sayfa Sayıları: ss.61091-61102
- Anahtar Kelimeler: Array gain, artificial neural network, channel modeling, molecular communication via diffusion, multiple-input multiple-output, spatial diversity
- Boğaziçi Üniversitesi Adresli: Evet
Özet
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.