Tracking of time-varying mobile radio channels. II. A case study

Lindbom, Lars; Åhlén, Anders; Sternad, Mikael; Falkenstrom, M.

doi:10.1109/26.975781

Cited by 66 publications

(90 citation statements)

References 18 publications

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“…Those conditions coincide with the channel properties in the North American Digital Cellular system IS-136 [31]. 2 They also hold when tracking each RAKE finger separately in, e.g., the WCDMA system, with 4-QAM modulated data.…”

Section: B Fir Systems With White Inputsmentioning

confidence: 93%

“…Lemma 1: Under Assumption 2 and assuming a nonsingular , the MSE-optimal learning filter (10) is asymptotically stable and is given by (31) Here, is the stably and causally invertible solution to the left polynomial matrix spectral factorization (32) whereas , together with a polynomial matrix , is the unique solution to the Diophantine equation (33) Proof: The proof is obtained by Theorem 1 in [7] and modified to an ARMA model structure for with common scalar denominator polynomial.…”

Section: Wiener Designmentioning

confidence: 99%

“…The contribution of the feedback noise to the gradient noise variance can be computed analytically; therefore, an estimation by Monte Carlo simulation can be avoided. Performance and robustness for various mismatched designs can also be investigated by Theorem 3; see [31] and [32].…”

Section: B Fir Systems With White Inputsmentioning

confidence: 99%

See 2 more Smart Citations

Analysis of Stability and Performance of Adaptation Algorithms With Time-Invariant Gains

Åhlén

Lindbom

Sternad

2004

IEEE Trans. Signal Process.

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Section: B Fir Systems With White Inputsmentioning

confidence: 93%

Section: Wiener Designmentioning

confidence: 99%

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Analysis of Stability and Performance of Adaptation Algorithms With Time-Invariant Gains

Åhlén

Lindbom

Sternad

2004

IEEE Trans. Signal Process.

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“…Therefore, the forward recursion of is given by (36) Finally, can also be expressed in a backward recursion form (37) as in [30], where (38) due to the fact that , and that is independent of and , according to the memory length assumption. In addition, we also have (39) Thus, the backward recursion of is given by (40) Now, substituting (30), (36) and (40) The signal processing procedure for calculating the noncoherent posterior probability is illustrated in Fig.…”

Section: A Noncoherent Detection Over Multipath Fading Channelsmentioning

confidence: 99%

Iterative Joint Channel Estimation and Multiuser Detection for DS-CDMA in Frequency-Selective Fading Channels

Mitra

Kuo

2008

IEEE Trans. Signal Process.

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Abstract-An iterative joint channel estimation, symbol detection, phase recovery and interference cancellation structure is proposed for asynchronous code-division multiple-access systems over frequency-selective fading channels. Based on the expectation maximization (EM) algorithm, a recursive channel estimator is developed for blind channel tracking, using a novel stochastic signal processing technique. To perform symbol detection given the phase ambiguities of the resultant EM channel estimates, a noncoherent scheme is developed to compute the a posteriori probabilities (APPs) of data symbols. Moreover, by incorporating the APPs into the proposed recursive channel estimator, phase ambiguity due to the EM channel estimation can be resolved, which enables soft multiple access interference cancellation for multiuser detection. Based on these new signal processing schemes, an iterative structure is proposed for joint channel estimation and multiuser detection over fast fading channels.

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“…The adaptation law may be designed for a set of possible situations, and its performance is optimized on average over this set, or for the worst case [1,2]. A robust design may be unsatisfactory if one single estimator is to be adjusted to a very wide variety of situations.…”

Section: Introductionmentioning

confidence: 99%