|Title:||DIGITAL IQ IMBALANCE COMPENSATION TECHNIQUES FOR OFDM RECEIVERS|
|???metadata.dc.contributor.*???:||Dr. Eneyew Adugna|
|Abstract:||With increasing demands for higher data rate and better services, more efficient modulation techniques such as orthogonal frequency division multiplexing (OFDM) are being adopted by many broadband wireless standards. However, the implementation of OFDM-based systems suffers from impairments such as in-phase and quadrature-phase (IQ) imbalances in the receiver front-end analog processing. IQ imbalance has been identified as a key front-end effect for OFDM systems. Such imbalances are caused by the analog processing of the radio frequency (RF) signal. The resulting IQ distortion limits the achievable operating SNR at the receiver and the achievable data rates. The IQ imbalances can severely limit the operating SNR and, consequently, the supported constellation sizes. This leads either to heavy front-end specifications and thus expensive front-end systems or large performance degradations. The direct-conversion receiver is a potential solution offering a flexible architecture to cover multiple RF standards while simplifying the system design and reducing overall costs. However, IQ imbalance has been identified as one of the most serious concerns in the practical implementation of the direct conversion receiver architecture. A very promising approach for coping with these analog impairments is to compensate them digitally. In this thesis, OFDM receiver with front-end analog impairments (such as IQ imbalance) is analyzed and descriptions of the physical sources of IQ imbalances are given. Based on the mathematical analysis an IQ imbalance model is developed. The development of model is based on the direct conversion receivers. Using the developed model, compensation algorithms in the digital domain is presented. Two alternative digital techniques are proposed and analyzed. The first one is based on Least Square (LS) method whereas the second method is based on Least Mean Square (LMS) method. Both compensation schemes use training to estimate the distortion parameters that model the IQ imbalances. The performance of both compensation methods is studied using computer simulation. The bit error rate (BER) verses SNR result indicates that the proposed methods can provide sufficient compensation performance with reasonable assumption.|
|Appears in Collections:||Thesis - Electrical Power Engineering|
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