Jarir Logo

Performance evaluation of channel estimation techniques for an LTE downlink system

Printed Book
SR 293
Inclusive of VAT
Sold as: EACH
SR17Per Month/24 months
Author:Kiross, Kahsay
Date of Publication: 2017
Book classification:Engineering,English Books
No. of pages:102 Pages
Format:Paperback

This book is printed on demand and is non-refundable after purchase

Available Formats :

Printed Book

It will be sent to your address

SR293
Incl. VAT

Choose your delivery preference

Or

About this Product

Thesis (M.A.) from the year 2016 in the subject Engineering - Communication Technology, grade: 75%, Mekelle University, course: Communication engineering, language: English, abstract: In this thesis channel estimation techniques for LTE downlink named Least Square, Minimum Mean Square error and Maximum Likelihood estimation techniques are studied for the pilot symbol based channel estimation. In addition to this the performances of these three channel estimation techniques were also studied by introducing averaging, interpolation and hybrid methods. This work also investigates the complexity of the channel estimation techniques in terms of the number of complex multiplications and by varying the FFT size and number of CP. furthermore, the effect of varying the number of antennas at the transmitter and receiver ends, where 2 x 2 and 4 x 4 antenna arrangements are considered as a case studies. The performance of these channel estimation techniques is also studied for EVA standard channel model in LTE. The considered channel model is EVA standard channel model with Doppler shift of 300HZ. Simulation results in this thesis show that the ML channel estimation technique has the best performance. In terms of number of complex multiplications it is proved the ML has lower complexity. From the interpolating techniques it is shown the performance of the algorithm integrated with hybrid technique has the best performance. In addition to this it is shown that as the number of transmit and receive antennas increase from 2 x 2 to 4 x 4 the performance of the estimator increases.
Show more

Specifications

SKU9783668365711
Manufacturer Number9783668365711
year published2017
Show more

Report an issue with this product.

Customer Reviews