Capacity of a Diffusion-Based Molecular Communication System With Channel Memory and Molecular Noise

By Massimiliano Pierobon, Ian F. Akyildiz. IEEE Transactions on Information Theory, 2013

297 citations recorded by the source corpus.

Subfields: Biomedical Engineering, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/2d175a3e0f4f689e6c896c2c50750a5c91967ca0

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Biomedical Engineering

1. Shuai Nie
2. Ahan Kak
3. Huseyin Birkan Yilmaz
4. Nariman Farsad
5. Andrew W. Eckford
6. Ian F. Akyildiz
7. Chan-Byoung Chae
8. Weisi Guo

In Molecular Biology

1. Shuai Nie
2. Ahan Kak
3. Huseyin Birkan Yilmaz
4. Ian F. Akyildiz
5. Nariman Farsad
6. Josep Miquel Jornet

Citations in the corpus

• 6G and Beyond: The Future of Wireless Communications Systems (2020, methodology): “…diffusion and particle location displacement are used to characterize the channel capacity as a function of a collection of parameters, including the diffusion coefficient of the channel, the temperature, the distance between end-transceivers, and the bandwidth of the transmitted signal [178].”
• A Comprehensive Survey of Recent Advancements in Molecular Communication (2014, background): “They are: diffusion based propagation [31]–[33], flow assisted propagation [34], active transport using molecular motors and cytoskeletal filaments [35], bacterial assisted propagation [36]–[38], and kinesin molecular motors moving over immobilized microtubule (MT) tracks [39], [40].”