分子擴散之數位通訊系統

Digital System Design for Diffusion-based Molecular Communication

邱泓瑞(Hung-Jui Chiu)

指導教授 ： 葉丙成

共同指導教授 ： 李佳翰

國立臺灣大學/電機資訊學院/電信工程學研究所/碩士(2013年)

https://doi.org/10.6342/NTU.2013.01285

摘要

奈米科技近年來的快速發展讓許多奈米機器能夠展現基本的通訊功能。為了讓這些奈米機器能夠互相溝通，分子通訊是一種用分子來傳輸訊息且有前途的通訊機制。但是跟傳統的電磁波通訊相比，分子通訊常常因為分子緩慢的擴散過程和分子之間的干擾，使其可靠度不高。在本論文中，我們提供了一種低複雜度的系統設計去解決上述問題。我們先提出最好的接收端設計，但因為複雜度的問題，我們用普瓦松分配去近似普瓦松二項式分配降低接收端的複雜度。接下來我們提出最好的傳送端設計讓系統運作得更好，並提出了分子通訊中的噪音模型讓系統更具真實性。最後為了解決分子緩慢的擴散過程，我們提出了多重振幅調變讓傳輸效率更好。

關鍵字

擴散程序 ； 分子通訊 ； 交互符號干擾

並列摘要

Dramatic progress in nanotechnology has enabled nano-machines to perform basic functions of communication. To interconnect nano-machines, molecular communication is one of the most promising communication mechanisms, in which molecules are used to deliver information. However, compared to classical communication schemes, the reliability of molecular communication is often criticized due to the slow diffusion process and the inter-symbol interference (ISI). In this thesis, we propose a low complexity system design for diffusion-based molecular communication to solve the above problems. We first derive the optimal receiver and then use the Poisson distribution to approximate the Poisson binomial distribution in order to obtain a receiver with lower complexity. After solving the ISI problem, we derive the optimal transmitter design to enhance the system performance and, moreover, we propose a noise model to make the system more practical. To solve the slow diffusion process problem, we propose multiple amplitude modulation to improve the transmission efficiency. In conclusion, we propose system design in diffusion-based molecular communication to solve the ISI and slow diffusion process problem.

並列關鍵字

Diffusion process ； Molecular communication ； Inter-symbol interference

參考文獻

[1] Ian F. Akyildiz, Fernando Brunetti, and Cristina Blazquez, “Nanonetworks: A new ’

2279, Aug. 2008.

[2] T. Suda, M. Moore, T. Nakano, R. Egashira, and A. Enomoto, “Exploratory research on molecular communication between nanomachines,” in Proc. Genetic and

Evolutionary Computation Conference (GECCO), Jun. 2005.

[5] M. Pierobon and I. F. Akyildiz, “Diffusion-based noise analysis for molecular communication in nanonetworks,” IEEE Trans. Signal Processing, vol. 59, no. 6, pp.