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Study on channel estimation of MIMO-OFDM systems

Multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) technology has been used widely in many wireless communication systems. Signals will be distorted when they are transmitted in wireless channels. For the reason that wireless channel is time or location variant, we have to estimate the channel impulse response and use the channel state information to compensate the channel distortion. Pilot signals can be spaced separated in the transmitted symbols. In the receiver, the channel impulse response can be estimated at the positions of pilot signals. The other channel information at the data signals can be obtained by interpolating the estimated channel impulse response. However, error caused by channel interpolation can not be avoided. In this paper we propose a pilot-aided iterative maximum likelihood (ML) channel estimation algorithm for MIMO OFDM systems. At first, an ML channel estimate is obtained by using pilot tones. The receiver uses the estimated channel to help the detection/decision of data signals. And then the channel estimation treats the detected signals as known data to perform a next stage channel estimation iteratively. By utilizing the iterative channel estimation and signal detection process we can reduce the estimation error caused by channel interpolation between pilots. The accuracy of the channel estimation can be improved by increasing the number of iteration process.
Simulation results demonstrate the iterative ML channel estimation algorithm can provide better mean-square-error and bit-error-rate performance than conventional methods. By changing the system parameters we can see that the improvement provided by this algorithm is different. Systems with fewer pilots have more improvement from the iterative ML algorithm. On the other hand, systems with more pilots have less improvement from the iterative algorithm. Finally, several channel environments are also considered in this thesis to compare the performance improvement introduced by the iterative algorithm.

Identiferoai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0508106-164152
Date08 May 2006
CreatorsChiang, Cheng-chih
ContributorsKen-huang Lin, Ju-ya Chen, Ching-piao Hung, Jie-chia Wu, Jih-ching Chiu
PublisherNSYSU
Source SetsNSYSU Electronic Thesis and Dissertation Archive
LanguageCholon
Detected LanguageEnglish
Typetext
Formatapplication/pdf
Sourcehttp://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0508106-164152
Rightsnot_available, Copyright information available at source archive

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