Blind Signature Waveform Estimation and Linear Multiuser Detection in Direct Sequence Code Division Multiple Access Systems.
Technische Universität, Darmstadt
[Ph.D. Thesis], (2007)
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|Item Type:||Ph.D. Thesis|
|Title:||Blind Signature Waveform Estimation and Linear Multiuser Detection in Direct Sequence Code Division Multiple Access Systems|
Direct-sequence code-division multiple-access (DS-CDMA) technology is a popular communication scheme adopted for the third generation (3G) wireless communication systems and beyond. Computationally efficient linear multiuser detection techniques can significantly improve the capacity of DS-CDMA systems by taking into account not only the signature of the user-of-interest but also those of the interfering users. However, as the spread spectrum DS-CDMA signals are usually subject to frequency-selective fading, a mismatch between the presumed and the actual user signatures is a typical challenge at the receiver side. As such signature mismatch may have a substantially detrimental effect on the performance of multiuser receivers, it is required to use an accurate signature estimation technique prior to the subsequent multiuser detection procedure. Among various signature estimation approaches, the bandwidth efficient blind algorithms that do not require transmission of any training symbols are of significant interest. This fact have motivated the topic of this thesis where advanced blind signature estimation and multiuser detection techniques for DS-CDMA systems are developed and studied. The first part of the thesis is devoted to blind signature estimation. We first develop a novel subspace-based signature estimation technique for binary phase shift keying (BPSK) transmitted signals in a white noise scenario. Unlike the earlier conventional signature estimation techniques, our method exploits the received signal jointly with its complex conjugate to substantially improve the estimation performance. We then analyze the performance of two well-known subspace-based estimation techniques developed for the case of unknown correlated noise. Finally, we propose a new signature estimation technique for this case that, unlike the latter two estimation algorithms, can be applied to an arbitrary signal constellation and enjoys much simpler implementation. The second part of the thesis is devoted to blind linear multiuser receivers. In this part of our work, we first develop a robust blind minimum mean-square error (MMSE) receiver that explicitly accounts for both the errors in the estimated signature and the sample data covariance matrix. Next, we analyze the signal-to-interference-plus-noise ratio (SINR) performance of the popular blind minimum output energy (MOE) receiver in large random DS-CDMA communication systems. The asymptotic properties of the Capon receiver and the blind Capon channel estimate are also studied in detail for both uplink and downlink scenarios. Our study of existing blind signature estimation and multiuser detection algorithms reveal some important properties of these techniques that have been missing in the literature. Moreover, our novel algorithms meet the requirements of the evolving communication network standards for highly reliable yet simple detection strategies. As such, we expect that our results will facilitate the application of blind multiuser detection to the future generations of DS-CDMA communication systems.
|Place of Publication:||Darmstadt|
|Classification DDC:||600 Technik, Medizin, angewandte Wissenschaften > 620 Ingenieurwissenschaften|
|Divisions:||18 Department of Electrical Engineering and Information Technology|
|Date Deposited:||17 Oct 2008 09:22|
|Last Modified:||07 Dec 2012 11:53|
|Referees:||Sidiropoulos, Prof. Dr. Nikos D.|
|Advisors:||Gershman, Prof. Dr. Alex B.|
|Refereed:||15 May 2007|