Results 121 to 130 of about 247 (176)

Rake-MMSE-equalizer performance for UWB

IEEE Communications Letters, 2005
The performance of a joint rake and minimum mean square error (MMSE) equalizer receiver for high data rate ultra-wideband communications is studied in this paper. The proposed receiver combats inter-symbol interference by taking advantage of the rake and equalizer structure.
Mohsen Eslami, Xiaodai Dong
openaire   +1 more source

Spread OFDM performance with MMSE equalization

2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221), 2002
Upper-bounds on the bit error probability of an OFDM/CDMA system in a single user context are derived for a linear minimum mean-square-error (MMSE) receiver structure. All the calculus are performed in presence of a frequency-selective Rayleigh fading channel both in a coded (convolutive forward error correcting scheme) and uncoded scenario ...
Debbah, M., Loubaton, Philippe, Courville, M. De   +2 more
openaire   +2 more sources

MMSE equalization for UMTS HSDPA

2003 IEEE 58th Vehicular Technology Conference. VTC 2003-Fall (IEEE Cat. No.03CH37484), 2003
The impact of 'advanced' mobile receivers incorporating dual-port antenna diversity and chip-rate equalization is assessed in terms of UMTS Release-5 high speed downlink packet access (HSDPA) link and system throughput. The addition of a second antenna port to the RAKE receiver increased the link-level throughput under 3GPP RAN WG4 test conditions by ...
R. Love, K. Stewart, R. Bachu, A. Ghosh
openaire   +1 more source

MMSE decision-feedback equalizers and coding. I. Equalization results

IEEE Transactions on Communications, 1995
The minimum mean-squared-error decision-feedback equalizer (MMSE-DFE) has properties that suggest that it is a canonical equalization structure for systems that combine equalization with coded modulation. The structure and performance of the MMSE-DFE are succinctly derived using linear-estimation-theoretic principles in this first part of this two-part
John M. Cioffi, Glen P. Dudevoir, M. Vedat Eyuboglu, G. David Forney Jr.   +3 more
openaire   +1 more source

Performance of rake-MMSE-equalizer for UWB communications

IEEE Wireless Communications and Networking Conference, 2005, 2005
The performance of a joint Rake and minimum mean square error (MMSE) equalizer receiver for high data rate ultra-wideband communications is studied in this paper. The proposed receiver combats intersymbol interference by taking advantage of the Rake and equalizer structure.
Mohsen Eslami, Xiaodai Dong
openaire   +1 more source

MMSE Equalizer Design Optimization for Wireline SerDes Applications

IEEE Transactions on Circuits and Systems I: Regular Papers
David Johns, Mohammad Hossein Shakiba, Alireza Akbarpour Bazargani   +2 more
exaly   +2 more sources

Direct semi-blind MMSE equalization for STBC

IEEE Signal Processing Letters, 2005
A semi-blind method for minimum mean square square error (MMSE) equalization of space-time block coding (STBC) systems is proposed. By exploiting information from the redundancy in the structure of STBC as well as from the training symbols, MMSE equalization can be achieved without channel estimation.
Ding, Z., Ward, D.
openaire   +1 more source

Innovations approach to MMSE waterfilling based equalizers

2006 IEEE International Symposium on Circuits and Systems, 2006
Block equalizer structures formulated under minimum-mean-square-error (MMSE) criteria are known results which perform MMSE power allocation via eigenvector decomposition of certain defining channel dependent matrices. In a practical channel-estimate based scenario, however, performing such eigenvector decomposition is a formidable task.
Ricardo Merched, Are Hjørungnes
openaire   +1 more source

An ML/MMSE estimation approach to blind equalization

Proceedings of ICASSP '94. IEEE International Conference on Acoustics, Speech and Signal Processing, 2002
Blind equalization of a communication channel is achieved by jointly estimating the deterministic channel coefficients and the random data sequence. The EM algorithm is used to determine the ML estimate of the channel. To implement the EM algorithm, one needs the MMSE estimate of the data sequence for the given estimate of the channel at each step.
Min Shao, Chrysostomos L. Nikias
openaire   +1 more source

MMSE Equalization for Bandwidth-Efficient Multicarrier Systems

2006 IEEE International Symposium on Circuits and Systems, 2006
Multicarrier systems, used in many of today's communications standards like 802.11b, are very prominent candidates for future mobile communication systems. Complex modulated transmultiplexer filter banks (Tzannes et al., 1994) providing improved frequency responses in comparison to orthogonal frequency division multiplex (OFDM) are proposed without a ...
Dirk S. Waldhauser, Josef A. Nossek
openaire   +1 more source