1 / 72

Information-theoretic problems in molecular and nanoscale communication

Andrew W. Eckford Department of Computer Science and Engineering, York University Joint work with: N. Farsad and L. Cui, York University K. V. Srinivas, S. Kadloor, and R. S. Adve, University of Toronto S. Hiyama and Y. Moritani, NTT DoCoMo.

hedwig
Download Presentation

Information-theoretic problems in molecular and nanoscale communication

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Andrew W. Eckford Department of Computer Science and Engineering, York University Joint work with: N. Farsad and L. Cui, York University K. V. Srinivas, S. Kadloor, and R. S. Adve, University of Toronto S. Hiyama and Y. Moritani, NTT DoCoMo Information-theoretic problems in molecular and nanoscale communication

  2. How do tiny devices communicate?

  3. How do tiny devices communicate? Most information theorists are concerned with communication that is, in some way, electromagnetic: - Wireless communication using free-space EM waves - Wireline communication using voltages/currents - Optical communication using photons

  4. How do tiny devices communicate? Most information theorists are concerned with communication that is, in some way, electromagnetic: - Wireless communication using free-space EM waves - Wireline communication using voltages/currents - Optical communication using photons Are these appropriate strategies for nanoscale devices?

  5. How do tiny devices communicate? There exist “nanoscale devices” in nature.

  6. How do tiny devices communicate? There exist “nanoscale devices” in nature. Image source: National Institutes of Health

  7. How do tiny devices communicate? Bacteria (and other cells) communicate by exchanging chemical “messages” over a fluid medium. - Example: Quorum sensing. Bacteria transmit rudimentary chemical messages to their neighbors to estimate the local population of their species.

  8. How do tiny devices communicate? Bacteria (and other cells) communicate by exchanging chemical “messages” over a fluid medium. - Example: Quorum sensing. Bacteria transmit rudimentary chemical messages to their neighbors to estimate the local population of their species. This communication is poorly understood from an information-theoretic perspective. - Biological literature tends to explain, not exploit - However, genetic components of quorum sensing can be engineered [Weiss et al. 2003] - Recognized as an important emerging technology [Hiyama et al. 2005], [Eckford 2007]

  9. Communication Model Communications model

  10. Communication Model Communications model m Tx Tx Rx Medium m m' 1, 2, 3, ..., |M| m = m'? M:

  11. Communication Model Communications model Noise m Tx Tx Rx Medium m m' 1, 2, 3, ..., |M| m = m'? M:

  12. Say it with Molecules Timing: Sending 0 Release a molecule now Cell 1 Cell 2

  13. Say it with Molecules Timing: Sending 1 WAIT … Cell 1 Cell 2

  14. Say it with Molecules Timing: Sending 1 Release at time T>0 Cell 1 Cell 2

  15. Say it with Molecules Timing: Receiving Measure arrival time Cell 1 Cell 2

  16. Ideal System Model Communications model Noise m Tx Tx Rx m m' 1, 2, 3, ..., |M| m = m'? M:

  17. Ideal System Model In an ideal system:

  18. Ideal System Model In an ideal system: 1) Transmitter and receiver are perfectly synchronized.

  19. Ideal System Model In an ideal system: 1) Transmitter and receiver are perfectly synchronized. Transmitter perfectly controls the release times and physical state of transmitted particles.

  20. Ideal System Model In an ideal system: 1) Transmitter and receiver are perfectly synchronized. 2) Transmitter perfectly controls the release times and physical state of transmitted particles. 3) Receiver perfectly measures the arrival time and physical state of any particle that crosses the boundary.

  21. Ideal System Model In an ideal system: 1) Transmitter and receiver are perfectly synchronized. 2) Transmitter perfectly controls the release times and physical state of transmitted particles. 3) Receiver perfectly measures the arrival time and physical state of any particle that crosses the boundary. 4) Receiver immediately absorbs (i.e., removes from the system) any particle that crosses the boundary.

  22. Communication Model Communications model Noise m Tx Tx Rx Medium m m' 1, 2, 3, ..., |M| m = m'? M:

  23. Propagation Medium Two-dimensional Brownian motion Tx Rx 0 d

  24. Propagation Medium Two-dimensional Brownian motion Tx Rx 0 d

  25. Propagation Medium Two-dimensional Brownian motion Tx Rx 0 d Uncertainty in propagation is the main source of noise!

  26. Approaches Two approaches:

  27. Approaches • Two approaches: • Discrete time, ISI allowed

  28. Approaches • Two approaches: • Discrete time, ISI allowed • Delay Selector Channel

  29. Approaches • Two approaches: • Discrete time, ISI allowed • Delay Selector Channel • Continuous time, ISI not allowed

  30. Approaches • Two approaches: • Discrete time, ISI allowed • Delay Selector Channel • Continuous time, ISI not allowed • Additive Inverse Gaussian Channel

  31. Delay Selector Channel Transmit: 1 0 1 1 0 1 0 0 1 0 Delay: 1

  32. Transmit: 1 0 1 1 0 1 0 0 1 0 Delay: 1 Receive: 0 1 0 0 0 0 0 0 0 0 Delay Selector Channel

  33. Transmit: 1 01 1 0 1 0 0 1 0 Delay: 1 Receive: 0 1 0 0 1 0 0 0 0 0 Delay Selector Channel

  34. Transmit: 1 0 11 0 1 0 0 1 0 Delay: 1 Receive: 0 1 0 0 2 0 0 0 0 0 Delay Selector Channel

  35. Transmit: 1 0 1 1 01 0 0 1 0 Delay: 1 Receive: 0 1 0 0 2 0 0 1 0 0 Delay Selector Channel

  36. Transmit: 1 0 1 1 01 0 01 0 Delay: 1 Receive: 0 1 0 0 2 0 0 1 1 0 Delay Selector Channel

  37. Transmit: 1 0 1 1 01 0 01 0 Delay: Receive: 0 1 0 0 2 0 0 1 1 0 Delay Selector Channel

  38. I Receive: 0 1 0 0 2 0 0 1 1 0 Delay Selector Channel

  39. I Receive: 0 1 0 0 2 0 0 1 1 0 … Transmit = ? Delay Selector Channel

  40. The Delay Selector Channel

  41. The Delay Selector Channel

  42. Delay Selector Channel

  43. Delay Selector Channel

  44. Delay Selector Channel [Cui, Eckford, CWIT 2011]

  45. Delay Selector Channel The DSC admits zero-error codes.

  46. Delay Selector Channel The DSC admits zero-error codes. E.g., m=1: 1: [1, 0] 0: [0, 0]

  47. Delay Selector Channel The DSC admits zero-error codes. E.g., m=1: 1: [1, 0] 0: [0, 0] Receive: 0 0 1 0 0 1 1 0 0 0 0 1

  48. Delay Selector Channel The DSC admits zero-error codes. E.g., m=1: 1: [1, 0] 0: [0, 0] Receive: 0 0 1 0 0 1 1 0 0 0 0 1

  49. Delay Selector Channel The DSC admits zero-error codes. E.g., m=1: 1: [1, 0] 0: [0, 0] Receive: 0 0 1 0 0 1 1 0 0 0 0 1 0 0 1 0 1 0 1 0 0 0 1 0

  50. Delay Selector Channel The DSC admits zero-error codes. E.g., m=1: 1: [1, 0] 0: [0, 0] Receive: 0 0 1 0 0 1 1 0 0 0 0 1 0 0 1 0 1 0 1 0 0 0 1 0

More Related