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Efficient Detection Schemes in Molecular Communication Networks

Mosayebi, Reza | 2018

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  1. Type of Document: Ph.D. Dissertation
  2. Language: Farsi
  3. Document No: 51504 (05)
  4. University: Sharif University of Technology
  5. Department: Electrical Engineering
  6. Advisor(s): Nasiri-Kenari, Masoumeh; Aminzadeh Gohari, Amin; Mirmohseni, Mahtab
  7. Abstract:
  8. The progress in the design of nano-scale machines over the past decade has motivated researchers to study the concept of nano-communications. Inspired by biological systems,diffusion-based molecular communication (MC) systems have been proposed as a potential solution for communication in nano-networks where molecules are used as information carriers.Nano-networks are envisioned to facilitate revolutionary applications in areas such as biological engineering, healthcare, and environmental monitoring. In recent years, there has been a significant amount of work on various aspects of MC systems, including transmitter and receiver design, multiple access protocols, and network layer issues. However, the problems of Intersymbol interference cancellation (ISI) and anomaly detection, which are two of the key challenges in many of the applications envisioned for nano-networks such as environmental and health monitoring and disease diagnosis, have not been fully investigated yet.To this end, in this thesis, first we consider the problem of ISI mitigation in diffusion-based MC systems and propose a new modulation scheme that uses reaction to mitigate ISI. Via simulation results, we show that our proposed modulator significantly outperforms previous proposed ISI mitigation techniques.Next, we consider the problem of anomaly detection via MC systems. To this end, first, we consider a simple scenario where several fixed nanosensors (NSs) are observing the environment to detect the presence of anomaly. Upon detection, they send their decisions to a fusion center(FC), where the final decision regarding the presence of anomaly is made. For this problem, we propose several optimum and suboptimal detectors and compare them in terms of false alarm and missed detection probabilities. Second, we consider the problem of anomaly detection in cardiovascular system that has fluid flow velocity. For concreteness, we consider the problem of cancer detection. These cancer cells produce and emit biomarkers, which are symptomatic for the presence of anomaly, into the cardiovascular system. Detection of cancer biomarkers with conventional blood tests is difficult in the early stages of a cancer due to the very low concentration of the biomarkers in the samples taken. However, close to the cancer cells, the concentration of the cancer biomarkers is high. Therefore, we study the use of mobile NSs (MNSs) that are injected at a suitable injection site and can move through the blood vessels.These MNSs can be activated by the biomarkers close to the cancer cells, where the biomarker concentration is sufficiently high. Eventually, the MNSs are collected by a fusion center (FC) where their activation levels are read and exploited to declare the presence of anomaly. We analytically derive the probability mass function of the MNSs’ activation levels and validate the obtained results via particle-based simulations. Then, we derive the optimal decision rule for the FC regarding the presence of anomaly assuming that the entire network is known at the FC. Finally, for the FC, we propose a simple sum detector that does not require knowledge of the network topology. Our simulations reveal that both proposed detectors significantly outperform a benchmark scheme that uses fixed NSs at the FC. Finally, we consider the problem of target detection is a suspicious tissue where the location of the possible target and its biomarker secretion rate are unknown. For this problem, we consider several reactive NSs and a reactive FC. Upon detection, NSs send their decision to the FC. For the final decision at the FC, since some parameters are not known at the FC, we propose two suboptimal detector that do not need the knowledge of unknown parameters and an idealistic detector. Simulation results show that there is a significant gap between the performance of the proposed suboptimal detectors and the idealistic detector which opens a room in this research area
  9. Keywords:
  10. Molecular Communication ; Diffusion ; Optimal Detector ; Inter-Symbol Interference (ISI) ; Suboptimal Detector ; Early Anomaly Detection ; Composite Hypothesis Testing

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