The M.Sc. student Mrs. Sara Salih Idan was examined in the contents of the thesis entitled:

“Channel Equalization Techniques in MIMO_OFDM Systems”

Which she prepared in the department of Electronics and Communication engineering in partial fulfillment of the requirements for the degree of M.Sc on Sunday 29th October, 2023. The examining committee consisted of:

  1. Prof. D. Rajaa Aldeen Abd Kalid, Chairerson of the examining committee.
  2. Prof. D. Firas Ali Sabir, Member of the examining committee.
  3. Prof. D. Aqiel Al Mamori, Member of the examining committee.
  4. Prof. D. Mohammed Kasim Mohammed, Supervisor.

 

The abstract of the thesis is as follows:

In this thesis the channel estimation and equalization for Space-Time Block Coding (STBC) based Multiple Input Multiple Output-Orthogonal Division Multiplexing (MIMO-OFDM) communication system is investigated for a multipath time-varying wireless channel model. STBC is an efficient technique to increase wireless performance by coding of data symbols and transmit diversity via multiple antennas and it is adopted by many applications. However, the biggest challenge is to achieve an accurate channel estimation in order to recovering the transmitted signal across a time-varying multipath fading channel. In this study, pilot-based channel estimation and equalization technique is considered for MIMO-OFDM systems. The performance of the two main estimation techniques, Least Square (LS) and Minimum Mean Square Error (MMSE) is evaluated for 2×2 and 4×4 MIMO system configurations with different number of OFDM subcarriers under different channel models. Simulation results showed that is MMSE just slightly better than LS. In addition, a technique for OFDM based time varying channels LS channel estimation improvement is proposed since it is a widely used channel estimation technique due to its simplicity. The technique is based on Linear Predictive Coding (LPC) to reduce the noise component in LS channel estimate. The simulation results indicate that LPC shows better performance over the LS method for reasonable amount of additional complexity. The channel’s LPC filter coefficients can be used to estimate power spectrum of the channel with continuous frequency variable offer high resolution compared to other spectral estimation methods.

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