Alexandra Duel-Hallen

Decorrelating decision-feedback multiuser detector for synchronous code-division multiple-access channel

A decorrelating decision-feedback detector (DF) for synchronous code-division multiple-access (CDMA) that uses decisions of the stronger users when forming decisions for the weaker ones is described. The complexity of the DF is linear in the number of users, and it requires only one decision per user. It is shown that performance gains with respect to the linear decorrelating detector are more significant for relatively weak users and that the error probability of the weakest user approaches the single-user bound as interferers grow stronger. The error rate of the DF is compared to those of the decorrelator and the two-stage detector. >

Long-range prediction of fading signals

It was previously proposed to adapt several transmission methods, including modulation, power control, channel coding, and antenna diversity to rapidly time variant fading channel conditions. Prediction of the channel coefficients several tens-to-hundreds of symbols ahead is essential to realize these methods in practice. We describe a novel adaptive long-range fading channel prediction algorithm (LRP) and its utilization with adaptive transmission methods. The LRP is validated for standard stationary fading models and tested with measured data and with data produced by our novel realistic physical channel model. Both numerical and simulation results show that long-range prediction makes adaptive transmission techniques feasible for mobile radio channels.

A family of multiuser decision-feedback detectors for asynchronous code-division multiple-access channels

It is important to identify simple and reliable interference rejection methods for code-division multiple-access (CDMA) channels, since the conventional matched filter receiver has high error rates, and the optimal detector is too complex. We introduce decision-feedback and partial feedback detectors for asynchronous CDMA channels. Two-stage detectors with decision-feedback in the second stage are also studied. The derivation of the decision-feedback detector is based on spectral factorization which leads to a white-noise channel model. We also describe two implementations of the maximum-likelihood detector for this model. Comparisons among the proposed detectors, the conventional detector, and the linear decorrelating detector are undertaken for several asynchronous CDMA channels. In these examples, high bandwidth efficiency systems are explored, and user energies are varied form being similar to being very different. We find that decision-feedback detectors compare favorably with more complex two-stage methods and maintain good performance under diverse channel conditions. >

Fading Channel Prediction for Mobile Radio Adaptive Transmission Systems

Adaptive transmission methods can potentially aid the achievement of high data rates required for mobile radio multimedia services. To realize this potential, the transmitter needs accurate channel state information (CSI) for the upcoming transmission frame. In most mobile radio systems, the CSI is estimated at the receiver and fed back to the transmitter. However, unless the mobile speed is very low, the estimated CSI cannot be used directly to select the parameters of adaptive transmission systems, since it quickly becomes outdated due to the rapid channel variation caused by multipath fading. To enable adaptive transmission for mobile radio systems, prediction of future fading channel samples is required. Several fundamental issues arise in the design and testing of fading prediction algorithms for adaptive transmission systems. These include complexity, robustness, choice of an appropriate channel model for algorithm validation, channel estimation and noise reduction required for reliable prediction, and design and analysis of adaptive transmission methods aided by fading prediction algorithms. We use these criteria in the review of recent advances in the area of fading channel prediction. We also demonstrate that reliable fading prediction makes adaptive transmission feasible in diverse wireless communication systems.

Multiuser detectors with disjoint Kalman channel estimators for synchronous CDMA mobile radio channels

We compare performance of several multiuser detectors for differentially encoded data combined with simple, disjoint, decision-directed Kalman channel estimators over flat Rayleigh fading channels. Simpler detectors with noncoherent differential detection are also compared. Different performance trends relative to the case of perfect channel estimation are observed. We find that in the presence of channel mismatch, the linear decorrelator is the most robust detector in terms of the bit-error rate and the near-far resistance. Parameter adjustment for fading channel modeling and estimation in the decision-directed mode are also discussed.

The Jakes fading model for antenna arrays incorporating azimuth spread

A new method for simulating the multiplicative fading of the narrow-band, flat wireless channel for antenna array receivers is presented. The new approach produces a set of fading waveforms, one waveform associated with each receiver element, in which the waveforms are appropriately correlated to take into account the spread, or dispersion, in the azimuth (arrival angle) of the received signal. The new method is an extension of the Jakes (1974) method of simulating fading in which the appropriate correlation of the set of waveforms is accomplished by directly considering the azimuth of scatterers in a particular distribution about the mobile transmitter. The models used for this cluster of scatterers are a ring and a disk of scatterers. Further modifications of the disk model permit the generation of fading waveforms which are correlated in a manner which reflect actual field measurements of azimuth dispersion. Analytical correlation of these models is reviewed for purposes of verification with the waveforms generated by the method.

Long range prediction and reduced feedback for mobile radio adaptive OFDM systems

Adaptive orthogonal frequency division multiplexing (AOFDM) modulation is a promising technique for achieving high data rates required for wireless multimedia services. To accomplish efficient adaptive channel loading, the channel state information (CSI) needs to be fed back to the transmitter. Since the fading channel varies rapidly for fast vehicle speeds, long range fading prediction (LRP) is required for mobile radio AOFDM to insure reliable adaptation. We use past channel observations to predict future CST and perform adaptive bit and power allocation for the OFDM system. We derive the minimum mean-square-error (MMSE) long-range channel prediction that utilizes the time and frequency domain correlation functions of the Rayleigh fading channel. Since the channel statistics are usually unknown, robust prediction methods that do not require the knowledge of the correlation functions are developed. Statistical model of the prediction error is created and used in the design of reliable adaptive modulation. In addition, several methods that significantly reduce the feedback load for mobile radio AOFDM systems are developed and compared. We use a standard sum-of-sinusoids model and our realistic physical model to validate performance of proposed methods. Simulation results demonstrate reliable performance and robustness of the proposed techniques, thus validating feasibility of AOFDM for rapidly varying mobile radio channels

Reliable adaptive modulation aided by observations of another fading channel

Adaptive transmission techniques, such as adaptive modulation and coding, adaptive power control, adaptive transmitter antenna diversity, etc., generally require precise channel estimation and feedback of channel state information (CSI). For fast vehicle speeds, reliable adaptive transmission also requires long-range prediction of future CSI, since the channel conditions are rapidly time variant. In this paper, we propose using past channel observations of one carrier to predict future CSI and perform adaptive modulation without feedback for another correlated carrier. We derive the minimum mean-square error (MMSE) long-range channel prediction that uses the time- and frequency-domain correlation function of the Rayleigh fading channel. An adaptive MMSE prediction method is also proposed. A statistical model of the prediction error that depends on the frequency and time correlation is developed and is used in the design of reliable adaptive modulation methods. We use a standard stationary fading channel model (Jakes model) and a novel physical channel model to test our algorithm. Significant gains relative to nonadaptive techniques are demonstrated for sufficiently correlated channels and realistic prediction range.

Combined adaptive modulation and transmitter diversity using long range prediction for flat fading mobile radio channels

Development of novel signal processing and communication techniques for 3G wireless systems is motivated by high data rate service requirements. These techniques include adaptive modulation and transmitter antenna diversity. In rapidly time variant channels, these methods need the knowledge of future fading conditions. Thus, they require accurate long range fading prediction. We investigate three combined adaptive modulation and transmitter diversity schemes in conjunction with our previously proposed long range channel prediction (LRP) algorithm. It is demonstrated that the novel combined schemes can achieve higher data rates than the conventional adaptive modulation methods when aided by the LRP.

On the performance of coherent and noncoherent multiuser detectors for mobile radio CDMA channels

We investigate the performance of several suboptimal multiuser detectors for rapidly time varying mobile radio channels. A modified Jakes (1974) model is used to simulate a realistic mobile fading channel. The use of the Kalman filter for this channel model is examined. We also analyze the performance of several noncoherent multiuser detectors. Analysis and simulation results indicate that the decorrelator is more robust than other considered multiuser detectors.