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Hardware Implementation of ANFIS Based Equalizer

Hakimi Toroghi, Navid | 2013

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  1. Type of Document: M.Sc. Thesis
  2. Language: English
  3. Document No: 44351 (55)
  4. University: Sharif University of Technology, International Campus, Kish Island
  5. Department: Science and Engineering
  6. Advisor(s): Bagheri Shouraki, Saeed; Ghorshi, Mohammad Ali
  7. Abstract:
  8. Nowadays, prolific usage of free air as a medium for data transmission leads interests to optimize the conditions of devices which are involved in wireless communication systems. Inter-Symbol Interference (ISI) distortion is a natural characteristic of wireless channels that occurs due to propagating electromagnetic waves in different directions. Due to different paths between a transmitter and a receiver, the received signal consists of several copies of the transmitted signal with different delays. The most common way of eliminating or mitigating the effects of ISI is channel equalization. The present work leads to implementing a supervised equalization in wireless communication. The adaptive algorithm which is used in the present work is a kind of fuzzy adaptive network which is called ANFIS (Adaptive Network-based Fuzzy Inference System). ANFIS estimates the characteristics of the channel by the pilot signal which is known by both the transmitter and the receiver. In fact, ANFIS takes advantages of both learning capability of neural networks and the inference power of fuzzy systems to identify the channel. This identification is based on obtained information from the operated function on the pilot signal. Practically, due to computational cost of nonlinear filters like ANFIS, for online communication usage, a hardware implementation is more reasonable in comparison with software development. The presented hardware implementation is based on a memristor crossbar that is recently proposed to model biological neurons. Finally, to evaluate the equalizer, some known models of the channel are used as a medium and the ANFIS-based equalizer is tested in different situations
  9. Keywords:
  10. Memristor ; Neuro-Fuzzy Systems ; Adaptive Neuro-Fuzzy Inference System (ANFIS) ; Wireless Channel System ; Inter-Symbol Interference (ISI)

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