Samir Kapoor

BEACON: an adaptive set-membership filtering technique with sparse updates

This paper deals with adaptive solutions to the so-called set-membership filtering (SMF) problem. The SMF methodology involves designing filters by imposing a deterministic constraint on the output error sequence. A set-membership decision feedback equalizer (SM-DFE) for equalization of a communications channel is derived, and connections with the minimum mean square error (MMSE) DFE are established. Further, an adaptive solution to the general SMF problem via a novel optimal bounding ellipsoid (OBE) algorithm called BEACON is presented. This algorithm features sparse updating, wherein it uses about 5-10% of the data to update the parameter estimates without any loss in mean-squared error performance, in comparison with the conventional recursive least-squares (RLS) algorithm. It is shown that the BEACON algorithm can also be derived as a solution to a certain constrained least-squares problem. Simulation results are presented for various adaptive signal processing examples, including estimation of a real communication channel. Further, it is shown that the algorithm can accurately track fast time variations in a nonstationary environment. This improvement is a result of incorporating an explicit test to check if an update is needed at every time instant as well as an optimal data-dependent assignment to the updating weights whenever an update is required.

Set-membership adaptive equalization and an updator-shared implementation for multiple channel communications systems

This paper considers the problems of channel estimation and adaptive equalization in the novel framework of set-membership parameter estimation. Channel estimation using a class of set-membership identification algorithms known as optimal bounding ellipsoid (OBE) algorithms and their extension to tracking time-varying channels are described. Simulation results show that the OBE channel estimators outperform the least-mean-square (LMS) algorithm and perform comparably with the RLS and the Kalman filter. The concept of set-membership equalization is introduced along with the notion of a feasible equalizer. Necessary and sufficient conditions are derived for the existence of feasible equalizers in the case of linear equalization for a linear FIR additive noise channel. An adaptive OBE algorithm is shown to provide a set of estimated feasible equalizers. The selective update feature of the OBE algorithms is exploited to devise an updator-shared scheme in a multiple channel environment, referred to as updator-shared parallel adaptive equalization (USHAPE). U-SHAPE is shown to reduce the hardware complexity significantly. Procedures to compute the minimum number of updating processors required for a specified quality of service are presented.

Adaptive multiuser detection and beamforming for interference suppression in CDMA mobile radio systems

This paper considers the problem of interference suppression in direct-sequence code-division multiple-access (DS-CDMA) systems over fading channels. An adaptive array receiver is presented which integrates multiuser detection, beamforming, and RAKE reception to mitigate cochannel interference and fading. The adaptive multiuser detector is formulated using a blind constrained energy minimization criterion and adaptation is carried out using a novel algorithm based on set-membership parameter estimation theory. The proposed detector overcomes the shortcomings of conventional LMS- and RLS-type algorithms, namely, that of slow convergence and large computational load, respectively. This is especially the case when strong interferers are present or when the number of adaptive weights is relatively large. DS-CDMA systems can have a relatively large number of spatially distributed interferers. Thus beamforming is based on direction-of-arrival (DOA) estimates provided by an approximate maximum-likelihood estimator (DOA-MLE). Unlike previous approaches, the DOA-MLE exploits the structure of the DS-CDMA signaling scheme resulting in robust performance and simple implementation in the presence of angle spreading. The overall method is suitable for real-time implementation and can substantially improve the interference suppression capabilities of a CDMA system.

Adaptive interference suppression for CDMA systems with a worst-case error criterion

This correspondence proposes a novel design strategy for linear multiuser detection in CDMA systems to satisfy a deterministic worst-case error performance measure. Formulations with and without the use of training signals are considered, and a near-far resistant solution for each is presented. Further, computationally efficient adaptive algorithms are derived in this framework that allow for sharing of detectors among different users.

Low complexity adaptive receiver for CDMA with multipath fading

A new receiver scheme for a DS-CDMA system similar to the IS-95 uplink is proposed in this paper that is of lower complexity and superior bit error rate performance in comparison to the conventional non-coherent RAKE receiver. The proposed receiver consists of a coherent RAKE receiver in the form of a transversal filter, and uses channel estimates obtained by an adaptive channel identification algorithm. Adaptation follows the set-membership filtering methodology, that features fast convergence and lower computational complexity compared to least-squares techniques.

Multiuser detection based on a deterministic error specification: theory and low-complexity adaptive solutions

This paper proposes a new strategy for multiuser detection in DS/CDMA systems. The detectors are designed to meet a deterministic worst-case error performance measure. Formulations with and without the use of training signals are considered and a solution for each is presented. Further, they are shown to be near-far resistant. An advantage in posing the multiuser detection problem this way is that computationally efficient adaptive algorithms can be derived for both the blind and non-blind cases, whose performance is very comparable to that of traditional RLS-like algorithms. It is also shown that sharing of detectors across users is possible, leading to significant reduction in hardware requirements.