Spatial Diversity in Molecular Communications

In this work, spatial diversity 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 proposed and analyzed. At the receiver-side, selection diversity, equal-gain combining, and maximum-ratio combining are studied as combining strategies. Throughout the numerical analysis, a symmetrical $2\times 2$ MIMO-DBMC system is assumed. Furthermore, a trained artificial neural network is utilized to acquire the channel impulse responses. The numerical analysis demonstrates that it is possible to achieve a diversity gain in molecular communications. In addition, it is shown that for MIMO-DBMC systems repetition MIMO coding is superior to Alamouti-type coding.

[1]  Andrew W. Eckford,et al.  A Comprehensive Survey of Recent Advancements in Molecular Communication , 2014, IEEE Communications Surveys & Tutorials.

[2]  Peter Adam Hoeher,et al.  Equivalent Discrete-Time Channel Modeling for Molecular Communication With Emphasize on an Absorbing Receiver , 2017, IEEE Transactions on NanoBioscience.

[3]  Ian F. Akyildiz,et al.  Modulation Techniques for Communication via Diffusion in Nanonetworks , 2011, 2011 IEEE International Conference on Communications (ICC).

[4]  Marvin K. Simon,et al.  Alamouti-type space-time coding for free-space optical communication with direct detection , 2005, IEEE Transactions on Wireless Communications.

[5]  Raviraj S. Adve,et al.  Molecular Communication in Fluid Media: The Additive Inverse Gaussian Noise Channel , 2010, IEEE Transactions on Information Theory.

[6]  Maïté Brandt-Pearce,et al.  Optical repetition MIMO transmission with multipulse PPM , 2005, IEEE Journal on Selected Areas in Communications.

[7]  Tadashi Nakano,et al.  Oscillation and Synchronization of Molecular Machines by the Diffusion of Inhibitory Molecules , 2013, IEEE Transactions on Nanotechnology.

[8]  Andrea J. Goldsmith,et al.  Machine learning based channel modeling for molecular MIMO communications , 2017, 2017 IEEE 18th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC).

[9]  Massimiliano Pierobon,et al.  A physical end-to-end model for molecular communication in nanonetworks , 2010, IEEE Journal on Selected Areas in Communications.

[10]  Tatsuya Suda,et al.  Molecular Communication Technology as a Biological ICT , 2011 .

[11]  Chan-Byoung Chae,et al.  Simulation study of molecular communication systems with an absorbing receiver: Modulation and ISI mitigation techniques , 2014, Simul. Model. Pract. Theory.

[12]  Yi Lu,et al.  The Effect of Two Receivers on Broadcast Molecular Communication Systems , 2016, IEEE Transactions on NanoBioscience.

[13]  Massimiliano Pierobon,et al.  Detection Techniques for Diffusion-based Molecular Communication , 2013, IEEE Journal on Selected Areas in Communications.

[14]  Andrew W. Eckford,et al.  Molecular MIMO: From Theory to Prototype , 2016, IEEE Journal on Selected Areas in Communications.

[15]  H. T. Mouftah,et al.  On the characterization of binary concentration-encoded molecular communication in nanonetworks , 2010, Nano Commun. Networks.

[16]  Younan Xia,et al.  One‐Dimensional Nanostructures: Synthesis, Characterization, and Applications , 2003 .

[17]  Arogyaswami Paulraj,et al.  A transmit diversity scheme for channels with intersymbol interference , 2000, 2000 IEEE International Conference on Communications. ICC 2000. Global Convergence Through Communications. Conference Record.

[18]  Chan-Byoung Chae,et al.  Novel Modulation Techniques using Isomers as Messenger Molecules for Nano Communication Networks via Diffusion , 2012, IEEE Journal on Selected Areas in Communications.

[19]  Tuna Tugcu,et al.  ISI-Aware Modeling and Achievable Rate Analysis of the Diffusion Channel , 2016, IEEE Communications Letters.

[20]  Siavash M. Alamouti,et al.  A simple transmit diversity technique for wireless communications , 1998, IEEE J. Sel. Areas Commun..

[21]  Peter Adam Hoeher,et al.  Low-Complexity Adaptive Threshold Detection for Molecular Communication , 2016, IEEE Transactions on NanoBioscience.

[22]  Huseyin Birkan Yilmaz,et al.  Arrival modelling for molecular communication via diffusion , 2014 .

[23]  Robert Schober,et al.  Optimal Receiver Design for Diffusive Molecular Communication With Flow and Additive Noise , 2013, IEEE Transactions on NanoBioscience.

[24]  Bin Li,et al.  Molecular communications: channel model and physical layer techniques , 2015, IEEE Wireless Communications.

[25]  Andrew W. Eckford,et al.  Molecular MIMO communication link , 2015, 2015 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS).

[26]  Ian F. Akyildiz,et al.  Nanonetworks: A new communication paradigm , 2008, Comput. Networks.

[27]  Özgür B. Akan,et al.  Body area nanonetworks with molecular communications in nanomedicine , 2012, IEEE Communications Magazine.

[28]  Tuna Tugcu,et al.  Three-Dimensional Channel Characteristics for Molecular Communications With an Absorbing Receiver , 2014, IEEE Communications Letters.

[29]  Jan Mietzner,et al.  Boosting the performance of wireless communication systems: theory and practice of multiple-antenna techniques , 2004, IEEE Communications Magazine.

[30]  Ian F. Akyildiz,et al.  MIMO communications based on molecular diffusion , 2012, 2012 IEEE Global Communications Conference (GLOBECOM).

[31]  Hussein Mouftah,et al.  Spatiotemporal distribution and modulation schemes for concentration-encoded medium-to-long range molecular communication , 2010, 2010 25th Biennial Symposium on Communications.