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Information theoretic Analysis of Joint Time and Concnetration Modulation for Molecular Communications

Mirkarimi, Farhad | 2020

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 53513 (05)
  4. University: Sharif University of Technology
  5. Department: Electrical Engineering
  6. Advisor(s): Nasiri Kenrai, Masoumeh; Mirmohseni, Mahtab
  7. Abstract:
  8. Today communication systems use electromagnetic signals for data transmission. However there are applications, in which the use of these signals is impossible or inefficient. For example in underwater communication, because of salinity of water, electromagnetic signals attenuate very fast. Regarding to this, inspired by nature, molecular communication systems is introduced, which use molecules as carriers of information for transmission of data. One of the main challenges in molecular communication in diffusion medium is that most of these channels suffer from low information capacity. With this respect, this thesis studies the channel capacity of diffusion based molecular channels by exploiting both the concentration and release time of molecules for message encoding which results in improving achievable rates of diffusion based channels. To this end, every time slot for transmission is divided into some sub-intervals. The transmitter releases molecules in one of the chosen sub-intervals with a level of concentration both determined by input message, hereby applying joint time and concentration (JTAC) modulation. To analyze performance of this modulation, we consider two receiver, molecules counting and Timing receiver. We derive the lower and upper bounds on the JTAC channel capacity. In Molecular counting receiver every time slot is divided into some observation sub-intervals (which is not necessarily equal to number of sub-intervals in transmitter) and the receiver counts the received molecules in each observation sub-interval. In this case we derive three achievable rates depending on how the receiver utilizes the number of received molecules in different sub-intervals. In case of using timing receiver each time slot (symbol period) divided into some observation sub-interval which receiver computes the average arrival times of received molecules in each sub-interval. In this scenario we compute the achievable rate, by just considering observation sub-intervals which difference of number of received molecules in that sub-interval and adjacent sub-interval exceeds a specific threshold. %sub-interval another receiver which become active in some specific sub-interval if difference of received molecules in adjacent sub-interval pass a threshold (hence we name it timing threshold based receiver) and we show every achievable rate for this receiver is an achievable rate for timing receiver. Finally by computing conditional mutual information between detected time in a observation sub-interval and input of channel (concentration and time) and choosing the sub-interval with maximum mutual information we conclude a lower bound on capacity of channel with timing receiver. We use detected average arrival times of molecules in each observation sub-interval to conclude a upper bound on capacity of channel with timing receiver. Derived bounds for above receivers (molecule counting and timing) are compared with capacity of channel in each case which is numerically computed using Blahut-Arimoto algorithm. For molecule counting receiver we see that third lower bound provides tighter bound compared with the other two schemes. For the timing receiver if the concentration of released molecules are large, (order of $10^9$) our numerical results indicate that our proposed achievable rates for timing receiver provides a tight lower bound on capacity in this case. Also in both cases (using molecule counting and timing receiver) improvements in achievable rates for the proposed modulation compare with the conventional timing based modulation and concentration based modulation are also discussed
  9. Keywords:
  10. Molecular Communication ; Poisson Distribution ; Channel Capacity ; Achievable Rate Region ; Channel Capacity Bounds

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