No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
Joint Detection and Joint Pre-Distortion Techniques for SD/TD/CDMA Systems
... The works by Walke et.al. [WR01b], [WR01a], [Wal03] compare the spectral efficiency of linear MUD and MUT methods and propose low-complexity frequency-domain implementations. Furthermore, the application of multiple antennas is considered. ...
... Several complexity reduction proposals [VHG01], [BS01] exist for Multiuser Detection / Joint Detection. Algorithms for the TxZF are proposed in [KM00], [WR01b], [Wal03]. In [GC02] and [Geo03], the complexity for the block-based TxZF is compared to inverse filters. ...
... If a matrix is block-circulant, its inverse can be calculated efficiently in the frequency domain [VHG01], [BS01], [WR01b]. The system matrix and the data matrix will be transformed into the frequency domain and then the solution will be computed. ...
Der codegeteilte Mehrfachzugriff (CDMA) wird bei allen zellularen Mobilfunksystemen der dritten Generation verwendet und ist ein aussichtsreicher Kandidat für zukünftige Technologien. Die Netzkapazität, also die Anzahl der Nutzer je Funkzelle, ist durch auftretende Interferenzen zwischen den Nutzern begrenzt. Für die Aufwärtsstrecke von den mobilen Endgeräten zur Basisstation können die Interferenzen durch Verfahren der Mehrnutzerdetektion im Empfänger verringert werden. Für die Abwärtsstrecke, die höhere Datenraten bei Multimedia-Anwendungen transportiert, kann das Sendesignal im Sender so vorverzerrt werden, dass der Einfluß der Interferenzen minimiert wird. Die informationstheoretische Motivation liefert dazu das Writing-on-Dirty-Paper Theorem. Das Signal-zu-Rausch-Verhältnis ist ein geeignetes Kriterium für die Performanz in rauschdominierten Szenarien. Mit Sende- und Empfangsfiltern kann das SNR durch den vorgeschlagenen Eigenprecoder maximiert werden. Durch den Einsatz von Mehrfachantennen im Sender und Empfänger kann die Performanz signifikant erhöht werden. Mit dem Generalized Selection MIMO Eigenprecoder können Transceiver mit reduzierter Komplexität ermöglicht werden. Sowohl für den Empfänger als auch für den Sender existieren Methoden, die Interferenzen vollständig zu eliminieren, oder den mittleren quadratischen Fehler zu minimieren. Der Maximum-Likelihood-Empfänger minimiert die Bitfehlerwahrscheinlichkeit (BER), hat jedoch kein entsprechendes Gegenstück im Sender. Die in dieser Arbeit vorgeschlagene Minimum Bit Error Rate Multiuser Transmission (TxMinBer) minimiert die BER am Detektor durch Sendesignalverarbeitung. Dieses nichtlineare Verfahren nutzt die Kenntnis der Datensymbole und des Mobilfunkkanals, um ein Sendesignal zu generieren, dass die BER unter Berücksichtigung einer Sendeleistungsnebenbedingung minimiert. Dabei werden nichtlineare Optimierungsverfahren wie Sequentielle Quadratische Programmierung (SQP) verwendet. Die Performanz linearer und nichtlinearer MUT-Verfahren MUT-Algorithmen mit linearen Empfängern wird am Beispiel des TD-SCDMA-Standards verglichen. Das Problem der Interferenzen kann mit allen untersuchten Verfahren gelöst werden, die TxMinBer-Methode benötigt jedoch die geringste Sendeleistung, um eine bestimmt Anzahl von Nutzern zu unterstützen. Die hohe Rechenkomplexität der MUT-Algorithmen ist ein wichtiges Problem bei der Implementierung in Real-Zeit-Systemen. Durch die Ausnutzung von Struktureigenschaften der Systemmatrizen kann die Komplexität der linearen MUT-Verfahren signifikant reduziert werden. Verschiedene Verfahren zur Invertierung der Systemmatrizen werden aufgezeigt und verglichen. Es werden Vorschläge gemacht, die Komplexität der Minimum Bit Error Rate Multiuser Transmission zu reduzieren, u.a. durch Vermeidung der Sendeleistungsnebenbedingung durch eine Beschränkung der Optimierung auf die Phasen des Sendesignalvektors. Die Komplexität der nichtlinearen Methoden ist um einige Größenordungen höher als die der linearen Verfahren. Weitere Forschungsanstrengungen an diesem Thema sowie die wachsende Rechenleistung von integrierten Halbleitern werden künftig die Ausnutzung der besseren Leistungsfähigkeit der nichtlinearen MUT-Verfahren erlauben.
... This can be provided by feedback, or by exploiting the channel reciprocity in TDD (time division duplex) systems, where the same channel is used for uplink and downlink. Linear zero-forcing MUT (TxZF) was proposed as Transmitter Precoding [1] , Joint Transmission (JT) [2], [3], Joint Precoding [4] or Joint Predistortion [5], [6], [7]. An MMSE criterion is used for the transmit Wiener filter (TxWF) [8], which outperforms the TxZF. ...
... Thus, the complexity was shown to be nearly independent from the number of transmit antennas. In [7], frequency-domain linear MUT was proposed to reduce the complexity of the inversion process. For linear Multiuser Detection, known as Joint Detection (JD,RxZF) or the Wiener Filter (RxWF) exist several complexity reduction proposals like [13], [14]. ...
... If a matrix is block circulant, its inverse can be calculated efficiently in frequency domain [14], [13], [7]. The system matrix and the data matrix will be transformed into the frequency domain and then the solution will be computed. ...
CDMA system capacity is interference limited. Whereas for the uplink multiuser detection can be applied, for the downlink multiuser transmission (MUT) is required. Using channel knowledge, the transmit signal is jointly preprocessed in such a way that the performance in the receivers is optimized. Linear MUT methods like joint transmission (JT) or the transmit Wiener filter are computational intensive due to the inversion of the system matrix. Efficient algorithms are proposed and compared, such as the block tridiagonal algorithm or the band Cholesky algorithm. Approximations of the former and frequency-domain processing are also considered. The MUT complexity and performance is compared for TD-SCDMA.
... The pre-RAKE [1] moves the conventional RAKE processing from Rx to Tx, but suffers from multiple-access interference (MAI). The linear methods which cancel interference [2][3][4][5][6][7][8], but do not regard noise, are known as Joint Transmission, Transmitter Precoding, Joint Predistortion and Joint Signal Precoding. An overview can be found in [10]. ...
... Using multiple antennas in Tx and Rx, their performance can be further increased. However, the computational complexity is dramatically increased at Tx. Attempts to minimize the complexity are made in [7], [8]and in [9] for the somewhat similar Joint Detection (JD). Here, further complexity reduction methods are proposed. ...
... The interference can be mitigated by linearly preprocessing the data symbols using the precoding matrix T. There exist several proposals to optimize T [2][3][4][5][6][7][8] either zero-forcing (ZF) or fulfilling minimum mean square error (MMSE) criterion. For fairness comparison, the transmitted power has always to be normalized. ...
The capacity of CDMA-based systems, for instance UMTS, is interference limited. The downlink (DL) is expected to carry much more traffic than in the uplink (UL) for multimedia applications services. If the characteristic of the DL channel is a priori known at the base station (BS), preprocessing data before transmission at BS reduces interference at mobile terminals Ts). This paper investigates several transmitterbased interference mitigation (TBIM) algorithms, for instance Joint Transmission (JT), in frequency selective fading channel. These algorithms are extended to multiple antennas in the transmitter or/and receiver IMO). Their performance is investigated and compared to conventional concepts. The computational load, which appears to be one of the largest obstacles in applying these algorithms, is analyzed and a complexity reduction method is proposed.
... In Category II the most important publications related to receiver oriented multiuser algorithms are listed. [Ver98], [Ver86a], [Ver86b] optimum multiuser detection Ib [LV89], [XSR90], [LV90], linear multiuser estimation [KB92], [KB93], [Kle96], -RxZF JD [Mil88], [BFKM93], [FKB94], [KKKB94], -MMSE [KKKB96], [MH94], [Gra81] [VA90], [PH94], [VA91], iterative multiuser detection [Var95], [Lam00b], [Lam00a], -multistage detection [YKI93], [KIHP90], [HL98], -parallel interference cancellation [DSR98] [Hag97], [BG96], [BM96], turbo multiuser detection [HOP96], [BDMP98], [BGT93], [ARAS99], [Moh98], [RSAA98], [Hag96], [AGR98], [VW98] II [Fis02], [WR01], [Bar02], receiver oriented algorithms [VJ98], [ Concerning transmitter oriented multiuser algorithms, it can be discerned among two main groups of algorithms: ...
... The TxZF was applied to TD-CDMA multiuser systems by Baier et al. [56] and Joham et al. [57], and to TDD-CDMA by Noll Barreto et al. [58]. Kowalewski et al. [59] examined the influence of channel estimation and change of the channel impulse responses due to the time separation of uplink and downlink (see also [60]), whereas Walke et al. [61] compared the TxZF to the RxZF for TD-CDMA systems. Morgado et al. [62] developed the TxZF in frequency domain by utilizing the redundancy of nonoverlapping band of a direct sequence CDMA (DS-CDMA) signal. ...
We examine and compare the different types of linear transmit processing for multiple input, multiple output systems, where we assume that the receive filter is independent of the transmit filter contrary to the joint optimization of transmit and receive filters. We can identify three filter types similar to receive processing: the transmit matched filter, the transmit zero-forcing filter, and the transmit Wiener filter. We show that the transmit filters are based on similar optimizations as the respective receive filters with an additional constraint for the transmit power. Moreover, the transmit Wiener filter has similar convergence properties as the receive Wiener filter, i.e., it converges to the matched filter and the zero-forcing filter for low and high signal-to-noise ratio, respectively. We give closed-form solutions for all transmit filters and present the fundamental result that their mean-square errors are equal to the errors of the respective receive filters, if the information symbols and the additive noise are uncorrelated. However, our simulations reveal that the bit-error ratio results of the transmit filters differ from the results for the respective receive filters.
ResearchGate has not been able to resolve any references for this publication.