Robert Santucci

Energy-Efficient Distributed Estimation by Utilizing a Nonlinear Amplifier

This paper describes the development of an energy-efficient amplify-and-forward distributed estimation scheme using realistic amplifier models. Specifically, a novel algorithm is presented that enables distributed estimation in the presence of amplifier compression resulting from the energy-efficient but non-linear class AB operation. In this system, a digital predistortion scheme is utilized to fit the amplifier at each sensor to a mathematically tractable, soft compression function that roughly mimics the compression region of the amplifier. It is shown both analytically and via simulation that using this scheme has two benefits over linear amplifier operation: improved transmitter efficiency by operating the amplifier in compression, and reduced sensitivity to heavy-tailed distributions due to the soft saturation.

A block adaptive predistortion algorithm for transceivers with long transmit-receive latency

The purpose of this paper is to introduce digital predistortion and propose a new digital predistortion scheme for use in systems with lengthy transmit-receive delays. The introduction discusses the motivation to implement digital predistortion within a wireless transceiver system. Then, we introduce techniques commonly found in the literature and the assumptions made in their operation. Finally, a new scheme is proposed which allows consideration of multiple measurements of actual data between predistorter updates. This is beneficial when there is a significant latency after each update before new results can be measured. This new scheme utilizes a block least-mean-squares algorithm, running within a gain-based look-up-table predistorter. The proposed scheme demonstrates a reduction in the time required for power amplifier linearization.

Design of limiting amplifier models for nonlinear amplify-and-forward distributed estimation

This paper describes the design of limiting amplifier models to be used in the implementation of non-linear amplify-and-forward distributed estimation systems. The use of nonlinear amplifiers in amplify-and-forward distributed estimation can yield significant gains in sensor power efficiency compared to the more conventional linear amplifiers. To ensure similar compression characteristics across all individual sensors and thus allow the receiver to perform estimation, predistortion is utilized to fit all amplifiers to a common shaping function similar to their inherent compression characteristics. When designing this shaping function, knowledge of the receiver noise and the accuracy of the amplifier predistortion is critical to estimating system performance. Analytical expressions for the asymptotic variance are derived for two non-linear amplifier models. The two models analyzed are the scaled hyperbolic tangent and the Cann model. It is found the Cann model with low sharpness can improve power added efficiency in a distributed estimation system. A set of Java-DSP functions is introduced to aid in teaching predistortion design tradeoffs.

Enhanced direction of arrival estimation via reassigned space-time-frequency methods

Two new space-time-frequency direction of arrival estimation algorithms are presented that decrease the estimation variance under specific conditions of narrow differential direction of arrival when multiple signals impinge upon the sensor array. The first algorithm, called Wide-Lane, provides a modest extension of existing space-time-frequency (STF) techniques by integrating a wide path along the signals instantaneous frequency track through the time-frequency (TF) plane. The second algorithm, called Reassigned STF, utilizes the TF reassignment method to increase the signals localization within the TF plane prior to estimating the direction of arrival with MUSIC. The performance variation of space-time MUSIC to a variety of signal structures is also presented.

Nonlinear Amplify-and-Forward Distributed Estimation Over Nonidentical Channels

This paper presents the use of nonlinear distributed estimation in a wireless system transmitting over channels with random gains. Specifically, we discuss the development of estimators and analytically determine their attainable variance for two conditions: 1) when full channel state information (CSI) is available at the transmitter and receiver; and 2) when only channel gain statistics and phase information are available. For the case where full CSI is available, we formulate an optimization problem to allocate power among each of the transmitting sensors while minimizing the estimate variance. We show that minimizing the estimate variance when the transmitter is operating in its most nonlinear region can be formulated in a manner very similar to optimizing sensor gains with full CSI and linear transmitters. Furthermore, we show that the solution to this optimization problem in most scenarios is approximately equivalent to one of two low-complexity power allocation systems.

OFDM-based distributed estimation for rich scattering environments

A preliminary investigation has been conducted into the use of orthogonal frequency-division multiple-access for distributed estimation. The key difference from previous work in the literature is that the channels between the sensors and the fusion center contain multiple paths with time lags, amplitudes, and phase rotations due to fading. Orthogonal frequency-division multiplexing has been proven to be an effective modulation scheme in the presence of multipath channels, and thus has been utilized in these experiments. This estimation system was designed to operate in a heavily scattered environment where synchronizing the transmitters and developing channel statistics has proven difficult to achieve. Sensors measure a signal in noise, modulate the measured data over an OFDM subcarrier, and transmit this to a fusion center over a Gaussian multiple-access channel. The transmissions are received at the fusion center using an OFDM receiver, and the estimation process is completed. Simulations demonstrate the effectiveness of the technique.