A machine learning-based concentration-encoded molecular communication system

Nano Communication Networks - Tập 35 - Trang 100433 - 2023
Su-Jin Kim1, Pankaj Singh1, Sung-Yoon Jung1
1Department of Electronic Engineering, Yeungnam University, Gyeongsan, Gyeongsangbuk 38541, Republic of Korea

Tài liệu tham khảo

Nakano, 2013 Suda, 2005, Exploratory research on molecular communication between nanomachines, vol. 25, 29 Akyildiz, 2008, Nanonetworks: A new communication paradigm, Comput. Netw., 52, 2260, 10.1016/j.comnet.2008.04.001 Akyildiz, 2011, Nanonetworks: A new frontier in communications, Commun. ACM, 54, 84, 10.1145/2018396.2018417 Farsad, 2016, A comprehensive survey of recent advancements in molecular communication, IEEE Commun. Surv. Tutor., 18, 1887, 10.1109/COMST.2016.2527741 Nakano, 2012, Molecular communication and networking: Opportunities and challenges, IEEE Trans. Nanobiosci., 11, 135, 10.1109/TNB.2012.2191570 Chude-Okonkwo, 2017, Molecular communication and nanonetwork for targeted drug delivery: A survey, IEEE Commun. Surv. Tutor., 19, 3046, 10.1109/COMST.2017.2705740 Islam, 2021, A molecular communication-based simultaneous targeted-drug delivery scheme, IEEE Access, 9, 96658, 10.1109/ACCESS.2021.3094892 Chahibi, 2013, A molecular communication system model for particulate drug delivery systems, IEEE Trans. Biomed. Eng., 60, 3468, 10.1109/TBME.2013.2271503 Chahibi, 2017, Molecular communication for drug delivery systems: A survey, Nano Commun. Netw., 11, 90, 10.1016/j.nancom.2017.01.003 Chahibi, 2015, An intra-body molecular communication networks framework for continuous health monitoring and diagnosis, 4077 Akyildiz, 2015, The internet of bio-nano things, IEEE Commun. Mag., 53, 32, 10.1109/MCOM.2015.7060516 Malak, 2012, Molecular communication nanonetworks inside human body, Nano Commun. Netw., 3, 19, 10.1016/j.nancom.2011.10.002 Yetimoğlu, 2021, Underwater testbed for molecular communication, 1 Huang, 2019, Space shift keying for molecular communication: Theory and experiment, 1 Gulec, 2020, A droplet-based signal reconstruction approach to channel modeling in molecular communication, IEEE Trans. Mol., Biol. Multi-Scale Commun., 7, 64, 10.1109/TMBMC.2020.3043484 Pierobon, 2010, A physical end-to-end model for molecular communication in nanonetworks, IEEE J. Sel. Areas Commun., 28, 602, 10.1109/JSAC.2010.100509 Atakan, 2016 Mahfuz, 2016, Achievable strength-based signal detection in quantity-constrained PAM OOK concentration-encoded molecular communication, IEEE Trans. NanoBiosci., 15, 619, 10.1109/TNB.2016.2625340 Okaie, 2020, Binary concentration shift keying with multiple measurements of molecule concentration in mobile molecular communication, 42 Mahfuz, 2014, A comprehensive study of sampling-based optimum signal detection in concentration-encoded molecular communication, IEEE Trans. Nanobiosci., 13, 208, 10.1109/TNB.2014.2341693 Mahfuz, 2016, Concentration-encoded subdiffusive molecular communication: Theory, channel characteristics, and optimum signal detection, IEEE Trans. Nanobiosci., 15, 533, 10.1109/TNB.2016.2588323 Kuran, 2011, Modulation techniques for communication via diffusion in nanonetworks, 1 Llatser, 2013, Detection techniques for diffusion-based molecular communication, IEEE J. Sel. Areas Commun., 31, 726, 10.1109/JSAC.2013.SUP2.1213005 Mahfuz, 2010, On the characterization of binary concentration-encoded molecular communication in nanonetworks, Nano Commun. Netw., 1, 289, 10.1016/j.nancom.2011.01.001 Kuran, 2012, Interference effects on modulation techniques in diffusion based nanonetworks, Nano Commun. Netw., 3, 65, 10.1016/j.nancom.2012.01.005 Garralda, 2011, Diffusion-based physical channel identification in molecular nanonetworks, Nano Commun. Netw., 2, 196, 10.1016/j.nancom.2011.07.001 Pierobon, 2012, Capacity of a diffusion-based molecular communication system with channel memory and molecular noise, IEEE Trans. Inform. Theory, 59, 942, 10.1109/TIT.2012.2219496 Llatser, 2012, Networking challenges and principles in diffusion-based molecular communication, IEEE Wirel. Commun., 19, 36, 10.1109/MWC.2012.6339470 Pierobon, 2011, Noise analysis in ligand-binding reception for molecular communication in nanonetworks, IEEE Trans. Signal Process., 59, 4168, 10.1109/TSP.2011.2159497 Einolghozati, 2011, Capacity of diffusion-based molecular communication with ligand receptors, 85 Mahfuz, 2014, Strength-based optimum signal detection in concentration-encoded pulse-transmitted OOK molecular communication with stochastic ligand-receptor binding, Simul. Model. Pract. Theory, 42, 189, 10.1016/j.simpat.2013.11.005 Luo, 2020 Morocho-Cayamcela, 2019, Machine learning for 5G/B5G mobile and wireless communications: Potential, limitations, and future directions, IEEE Access, 7, 137184, 10.1109/ACCESS.2019.2942390 Jagannath, 2019, Machine learning for wireless communications in the internet of things: A comprehensive survey, Ad Hoc Netw., 93, 10.1016/j.adhoc.2019.101913 Jiang, 2016, Machine learning paradigms for next-generation wireless networks, IEEE Wirel. Commun., 24, 98, 10.1109/MWC.2016.1500356WC Kim, 2014, Symbol interval optimization for molecular communication with drift, IEEE Trans. Nanobiosci., 13, 223, 10.1109/TNB.2014.2342259 Mahfuz, 2010, Characterization of molecular communication channel for nanoscale networks, 327 Tyrrell, 2013 Milo, 2016 Lee, 2017, Machine learning based channel modeling for molecular MIMO communications, 1 Huang, 2016, Communication: Understanding molecular representations in machine learning: The role of uniqueness and target similarity, J. Chem. Phys., 145, 10.1063/1.4964627 Tepekule, 2015, ISI mitigation techniques in molecular communication, IEEE Trans. Mol., Biol. Multi-Scale Commun., 1, 202, 10.1109/TMBMC.2015.2501745 Sheikholeslami, 2019