Loading...

Design of Toeplitz Measurement Matrices with Applications to Sparse Channel Estimation in Single-Carrier Communication

Mohaghegh Dolatabadi, Hadi | 2017

1025 Viewed
  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 50531 (05)
  4. University: Sharif University of Technology
  5. Department: Electrical Engineering
  6. Advisor(s): Amini, Arash
  7. Abstract:
  8. Channel estimation is one of the fundamental challenges in every communication system and different algorithms have been proposed to deal with it. Obviously, type of a communication channel is an important factor in choosing the appropriate method for channel estimation. Sparse channels are one kind of them that occur in many real-world applications such as wireless communication systems. In addition, emergence of a new means in signal processing to deal with sparse signals, known as Compressed Sensing(CS), paved the way for their extensive usage in many applications including sparse channel estimation.On the other hand, one of the most fundamental problems in sparse signal recovery using CS is determination of sensing (measurement) matrix; because some specific properties of this matrix is used to prove recovery guarantees. Based on that, the problem of designing sensing matrices has gained a lot of attention from the beginning. Typically,there are two kind of measurement matrices: random and deterministic. However, due to their better properties such as the less memory occupation in saving them, interests have been raised toward utilizing deterministic matrices recently. In this thesis, we will delve into channel estimation in bandlimited communication systems. First of all, we will show how a channel estimation problem can be related to a signal recovery counterpart in CS context with a Toeplitz measurement matrix. Then, we will propose a new design for Toeplitz sensing matrices and derive an upper-bound for its coherence using the results that exist about exponential sums in Analytical Number’s Theory. It will be shown that the performance of the designed matrix is comparable to its random counterparts. In addition, we will show that the designed matrices have the advantage that their elements are of the same magnitude and hence, they can be quantized using a specific number of bits which is an important property in their implementation
  9. Keywords:
  10. Sparse Channel Estimation ; Compressive Sensing ; Measurement Matrix ; Coherence Parameter ; Single Carrier Wireless System ; Toeplitz Matrix ; Pilot Sequence Desigin

 Digital Object List

 Bookmark

...see more