Reduced-complexity semi-blind channel estimation for LTE Downlink

Niccolo Franceschi

AbstractThe advance of MIMO techniques as a means of boosting data rate and reliability in wireless communications has challenged researchers to investigate new channel estimation methods. As MIMO multiplies the number of channel parameters, longer pilotsequences need to be sent to attain the same accuracy as SISO. Of course, this increases the overhead resulting in a waste of channel capacity. Semi-blind channel estimators address this problem making use of both pilot-sequence and user data to enhance the quality of the estimate. Even though these methods are appealing in terms of mean squared error, they considerably raise the complexity of the receiver. This issue is even more severe if we consider that MIMO is expected to speed up the bit rate, meaning that an increasing amount of data has to be processed to produce the estimate.
The aim of this thesis is investigating low-complexity semi-blind estimation techniques, capable of improving the mean squared error and still computationally aff ordable. Firstly, the MIMO-LTE channel model is formulated, then we will discuss traditional pilot-only estimation and its limitations. Afterwards, the semi-blind problem is presented and expressed using two di fferent approaches, one relying on the true discrete distribution of the data symbols and the other on a Gaussian approximation. Then, EM-based solutions are derived and compared with numerical techniques that are independent of the size of the data sequence. Finally, all these methods are tested through simulations assessing their accuracy and computational cost.
TypeMaster's thesis [Industrial collaboration]
Year2012
PublisherTechnical University of Denmark, DTU Informatics, E-mail: reception@imm.dtu.dk
AddressAsmussens Alle, Building 305, DK-2800 Kgs. Lyngby, Denmark
SeriesIMM-M.Sc.-2012-123
NoteDTU supervisor, Ole Winther, owi@imm.dtu.dk, DTU Informatics
Electronic version(s)[pdf]
Publication linkhttp://www.imm.dtu.dk/English.aspx
BibTeX data [bibtex]
IMM Group(s)Intelligent Signal Processing


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