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Channel estimation in mobile wireless systems
KTH, School of Electrical Engineering (EES), Signal Processing.
2012 (English)Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

The demands of multimedia services from mobile user equipment (UE) for achieving high data rate, high capacity and reliable communication in modern mobile wireless systems are continually ever-growing. As a consequence, several technologies, such as the Universal Mobile Telecommunications System (UMTS) and the 3rd Generation Partnership Project (3GPP), have been used to meet these challenges. However, due to the channel fading and the Doppler shifts caused by user mobility, a common problem in wireless systems, additional technologies are needed to combat multipath propagation fading and Doppler shifts. Time-variant channel estimation is one such crucial technique used to improve the performance of the modern wireless systems with Doppler spread and multipath spread.

One of vital parts of the mobile wireless channel is channel estimation, which is a method used to significantly improve the performance of the system, especially for 4G and Long Term Evolution (LTE) systems. Channel estimation is done by estimating the time-varying channel frequency response for the OFDM symbols. Time-variant channel estimation using Discrete Prolate Spheroidal Sequences (DPSS) technique is a useful channel estimation technique in mobile wireless communication for accurately estimating transmitted information. The main advantage of DPSS or Slepian basis expansion is allowing more accurate representation of high mobility mobile wireless channels with low complexity. Systems such as the fourth generation cellular wireless standards (4G), which was recently introduced in Sweden and other countries together with the Long Term Evolution, can use channel estimation techniques for providing the high data rate in modern mobile wireless communication systems.

The main goal of this thesis is to test the recently proposed method, time-variant channel estimation using Discrete Prolate Spheroidal Sequences (DPSS) to model the WINNER phase II channel model. The time-variant sub-carrier coefficients are expanded in terms of orthogonal DPS sequences, referred to as Slepian basis expansions. Both Slepian basis expansions and DPS sequences span the low-dimensional subspace of time-limited and band-limited sequences as Slepian showed. Testing is done by using just two system parameters, the maximum Doppler frequency Dmax v and K, the number of basis functions of length N = 256.

The main focus of this thesis is to investigate the Power spectrum and channel gain caused by Doppler spread of the WINNER II channel model together with linear fitting of curves for both the Slepian and Fourier basis expansion models. In addition, it investigates the Mean Square Error (MSE) using the Least Squares (LS) method. The investigation was carried out by simulation in Matlab, which shows that the spectrum of the maximum velocity of the user in mobile wireless channel is upper bounded by the maximum normalized one-sided Doppler frequency. Matlab simulations support the values of the results. The value of maximum Doppler bandwidth vDmax  of the WINNER model is exactly the same value as DPS sequences. In addition to the Power spectrum of the WINNER model, the fitting of Slepian basis expansion performs better in the WINNER model than that of the Fourier basis expansion.

Place, publisher, year, edition, pages
EES Examensarbete / Master Thesis, XR-EE-SB 2012:005
Keyword [en]
Time-variant channel, Discrete Prolate Spheroidal Sequences (DPSS)
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
URN: urn:nbn:se:kth:diva-98754OAI: diva2:538857
Educational program
Master of Science in Engineering - Electrical Engineering
Available from: 2012-07-02 Created: 2012-07-02 Last updated: 2012-07-02Bibliographically approved

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