Jens Baltersee

Channel tracking for RAKE receivers in closely spaced multipath environments

This paper deals with the problem of channel tracking for RAKE receivers in propagation environments characterized by closely spaced multipath components. After outlining why conventional single-path channel tracking algorithms fail in such scenarios, several new estimation algorithms are developed that are tailored to channels with closely spaced multipaths. This is achieved by removing or minimizing self-interference caused by multipath components. Other interfering users are treated as noise. Both timing tracking and phasor tracking and their interaction are covered in this paper. The derived algorithms are benchmarked against perfect channel knowledge on one hand and conventional tracking algorithms on the other hand, both in a UMTS test scenario. In moderate scenarios, the use of these new algorithms leads to performance improvements of up to 2 dB, in terms of signal-to-noise ratio (SNR) at moderate bit error rates, and even manages to track the channel in conditions where conventional tracking algorithms fail completely.

Nonlinear adaptive prediction of speech with a pipelined recurrent neural network

New learning algorithms for an adaptive nonlinear forward predictor that is based on a pipelined recurrent neural network (PRNN) are presented. A computationally efficient gradient descent (GD) learning algorithm, together with a novel extended recursive least squares (ERLS) learning algorithm, are proposed. Simulation studies based on three speech signals that have been made public and are available on the World Wide Web (WWW) are used to test the nonlinear predictor. The gradient descent algorithm is shown to yield poor performance in terms of prediction error gain, whereas consistently improved results are achieved with the ERLS algorithm. The merit of the nonlinear predictor structure is confirmed by yielding approximately 2 dB higher prediction gain than a linear structure predictor that employs the conventional recursive least squares (RLS) algorithm.

Performance analysis of phasor estimation algorithms for a FDD-UMTS RAKE receiver

The performance of phasor estimation algorithms for the UMTS RAKE receiver are analysed. Due to the need of covering a wide range of possible mobile speeds and spreading factors, two different algorithms are considered, namely a LMS-Kalman type algorithm, and a Wiener filter. The Wiener filter is considered both, as a predictor and a smother. It is shown that the simpler LMS-Kalman predictor is particularly suited for low mobile speeds and low spreading factors, whereas higher speeds and/or higher spreading factors require the usage of the more complex Wiener filter. Furthermore, the very high spreading factors (128-512) require the usage of the common pilot channel in order to facilitate smoothing instead of prediction.

Low complexity adaptive code tracking with improved multipath resolution for DS-CDMA communications over fading channels

A new adaptive timing error detector (TED) embedded in a code-tracking loop for RAKE reception of direct sequence-CDMA signals is presented. The loop consists of a digital coherent TED and a loop filter with lowpass characteristic. In a multipath fading environment, one such loop can be allocated for each finger in a RAKE receiver and the interference from adjacent paths can be mitigated by adaptively prefiltering the signal prior to the correlation process. The filter coefficients are computed online in order to minimize an interference cost function. Multipaths whose delays differ by as little as one chip duration become resolvable and can be tracked, resulting in significant performance gains of the overall system, especially if the channel delay spread is small. The tracking performance of the proposed loop is assessed by computer simulation.

Multipath resistant coherent timing error detector for DS-CDMA applications

A new coherent timing error detector (TED) for timing/code tracking loops used inside RAKE receivers in CDMA systems is presented. In contrast to the conventional TED it is well suited for the case of multipath propagation channels. In order to accomplish this task a compensation term is introduced inside the tracking loop directly behind the conventional TED. This compensation term is calculated using the knowledge on the relative delays of all paths and their respective channel coefficients. A compensation scheme like the one described here becomes necessary whenever closely spaced paths have to be tracked. This fact makes this algorithm a favorable candidate for indoor scenarios where individual paths can be spaced even more closely than one chip. The performance of the presented scheme is assessed by means of simulation.

Channel estimation for DS-CDMA with transmit diversity over frequency selective fading channels

RAKE receivers for DS-CDMA communications over fading channels require the knowledge of instantaneous complex channel phasors for each of the multipath diversity branches (or RAKE fingers). If transmit diversity is employed by using N transmit antennas in the basestation, N such fading channels need to be estimated in the mobile receiver. A channel estimation algorithm which estimates two fading channels in the case of dual TX diversity is presented, making use of known pilot symbols. The proposed scheme performs remarkably well in Rayleigh fading multipath environments with little additional complexity if compared to a scheme where only one channel needs to be estimated (i.e. no TX or RX diversity). The performance of the algorithm is assessed by means of computer simulations.

A novel multipath interference cancellation scheme for RAKE channel estimation

A novel channel estimation scheme is proposed for a RAKE receiver operating in the downlink of a mobile communication scenario. The approach is an extension of the well known Wiener channel estimator and partly cancels multipath interference, with the additional advantage of being able to cope with physically closely spaced multipaths which arise, for example, in an indoor scenario. It is demonstrated by means of simulation that the algorithm improves the quality of the channel estimates significantly. Little additional computational effort is necessary to implement the algorithm, making it an ideal candidate for improving reception capabilities of the mobile user equipment.

Non-Linear Adaptive Prediction of Speech with a Pipelined Recurrent Neural Network and Advanced Learning Algorithms

New learning algorithms for an adaptive non-linear forward predictor which is based on a Pipelined Recurrent Neural Network (PRNN) are presented. A computationally efficient Gradient Descent (GD) algorithm, as well as a novel Extended Recursive Least Squares (ERLS) algorithm are tested on the predictor. Simulation studies, based on three speech signals, which have been made public and are available on the World Wide Web (WWW), show that the non-linear predictor does not perform satisfactorily when the previously proposed gradient descent algorithm was used. The steepest descent algorithm is shown to yield a poor performance in terms of the prediction error gain, whereas consistently improved results are obtained using the ERLS algorithm. The merit of the non-linear predictor structure is confirmed by yielding approximately 2 dB higher prediction gain than only a linear structure predictor, which uses the conventional Recursive Least Squares (RLS) algorithm.

Performance bounds for a UMTS RAKE receiver with imperfect timing synchronisation

Performance bounds for a UMTS RAKE receiver with imperfect timing synchronisation are presented. Firstly, an analytical expression for the bit error probability (P/sub e/) performance of the RAKE receiver is derived. This analysis establishes that the bit error probability performance of the RAKE receiver is less sensitive to timing errors for higher spreading factors. However, significant performance degradations for all spreading factors confirm the need for timing synchronisation in the RAKE receiver. An extension of the analysis is presented for a multipath environment, allowing the derivation of an upper and a lower performance bound. The results indicate that a very simple interpolator providing 4 samples within a chip period results in a performance loss smaller than 0.15 dB.

Linear MMSE channel estimation for GSM

A new channel estimation algorithm capable of exploiting a-priori knowledge about modulation and receive filters and the power delay profile of the physical channel is presented. In order to incorporate the a-priori knowledge into the linear minimum mean square error (LMMSE) channel estimator, a Bayesian approach is applied to an appropriate GSM system model. The performance of the new algorithm is compared to a conventional least squares (LS) channel estimator by means of analysis and simulations. Simulations are carried out for the standard GSM channel profiles (TU50, HT100, RA250). Information about the shape of the power delay profile is assumed to be unavailable to the receiver. The merit of the new channel estimator is confirmed by yielding an MSE approximately 1-2 dB lower than the LS estimator. The lower MSE translates into a BER advantage of approximately 0.25 dB. Exploiting additional knowledge about the shape of the power delay profile results in further BER performance improvements of up to 0.3 dB.