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Channel Estimation And Tracking In MIMO Communication Systems

Posted on:2007-12-09Degree:DoctorType:Dissertation
Country:ChinaCandidate:Y J LiFull Text:PDF
GTID:1118360212965418Subject:Signal and Information Processing
Abstract/Summary:PDF Full Text Request
The increasing demand for high data rate and the limited available bandwidth motivates the investigation of wireless systems that efficiently exploit the spatial domain. It has been recently shown that the use of spatial diversity can improve throughput and coverage in addition to allowing a high degree of spatial reuse and thereby increase the system capacity. In this dissertation, we mainly focus on the topics of channel estimation and tracking in MIMO communication systems. The main contents are as follows:1. Propose an error-adjustment scheme for semiblind channel estimation. The algorithm consists of a two-step iteration to achieve even better performance. The initial channel estimate is computed using a variant of cyclic prefix. Then the estimate error of the received symbol is used to adjust the initial channel estimation. Computer simulations show that the proposed algorithm offers good estimation behavior for MIMO systems.2. A low-complexity blind channel estimation technique is proposed for long-code MIMO CDMA systems. Simply based on the first-order statistic of the decorrelating matched filter output, the channel parameters can be estimated effectively without training sequences. Computer simulations show that the proposed algorithm offers good estimation behavior for MIMO CDMA systems.3. A blind channel estimation method is presented for the multiple-input-multiple-output (MIMO) CDMA system employing long spreading codes. To estimate channel parameters, we apply a decorrelating matched filter as front-end at the receiver. The matched filter outputs consist of the signal space spanned by the users channel vector and we can find the centers of the sets by clustering procedure. Then the channel parameters are estimated via the first-order statistics of the filter outputs. We also improve the K-mean clustering algorithm in class centers initialization for fast convergence. The proposed method has low computational complexity and estimates the channel in an effective way.4. A blind channel estimation method is presented for the multiple-input-multiple-output (MIMO) CDMA system employing long spreading codes. By exploiting the finite alphabet p.d.f. of the transmit symbols, the matched filter outputs can be modeled as a Gaussian Mixture Model. Then the channel parameters are estimated using expectation-maximum (EM) algorithm that fully exploits the statistical features of the transmitted signal.5. A new estimation method based on the superimposed (implicit) training is proposed for...
Keywords/Search Tags:MIMO system, channel estimation, blind estimation, semiblind estimation, CDMA, clustering algorithm, implicit training, adaptive algorithm
PDF Full Text Request
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