Energy efficiency of mmWave massive MIMO precoding with low-resolution DACs

With the congestion of the sub-6 GHz spectrum, the interest in massive multiple-input multiple-output (MIMO) systems operating on millimeter wave spectrum grows. In order to reduce the power consumption of such massive MIMO systems, hybrid analog/digital transceivers and application of low-resolution digital-to-analog/analog-to-digital converters have been recently proposed. In this work, we investigate the energy efficiency of quantized hybrid transmitters equipped with a fully/partially-connected phase-shifting network composed of active/passive phase-shifters and compare it to that of quantized digital precoders. We introduce a quantized single-user MIMO system model based on an additive quantization noise approximation considering realistic power consumption and loss models to evaluate the spectral and energy efficiencies of the transmit precoding methods. Simulation results show that partially-connected hybrid precoders can be more energy-efficient compared to digital precoders, while fully-connected hybrid precoders exhibit poor energy efficiency in general. Also, the topology of phase-shifting components offers an energy-spectral efficiency trade-off: active phase-shifters provide higher data rates, while passive phase-shifters maintain better energy efficiency.Comment: Published in IEEE Journal of Selected Topics in Signal Processin

Model for Estimation of Bounds in Digital Coding of Seabed Images

This paper proposes the novel model for estimation of bounds in digital coding of images. Entropy coding of images is exploited to measure the useful information content of the data. The bit rate achieved by reversible compression using the rate-distortion theory approach takes into account the contribution of the observation noise and the intrinsic information of hypothetical noise-free image. Assuming the Laplacian probability density function of the quantizer input signal, SQNR gains are calculated for image predictive coding system with non-adaptive quantizer for white and correlated noise, respectively. The proposed model is evaluated on seabed images. However, model presented in this paper can be applied to any signal with Laplacian distribution

Sampling and Reconstruction of Spatial Fields using Mobile Sensors

Spatial sampling is traditionally studied in a static setting where static sensors scattered around space take measurements of the spatial field at their locations. In this paper we study the emerging paradigm of sampling and reconstructing spatial fields using sensors that move through space. We show that mobile sensing offers some unique advantages over static sensing in sensing time-invariant bandlimited spatial fields. Since a moving sensor encounters such a spatial field along its path as a time-domain signal, a time-domain anti-aliasing filter can be employed prior to sampling the signal received at the sensor. Such a filtering procedure, when used by a configuration of sensors moving at constant speeds along equispaced parallel lines, leads to a complete suppression of spatial aliasing in the direction of motion of the sensors. We analytically quantify the advantage of using such a sampling scheme over a static sampling scheme by computing the reduction in sampling noise due to the filter. We also analyze the effects of non-uniform sensor speeds on the reconstruction accuracy. Using simulation examples we demonstrate the advantages of mobile sampling over static sampling in practical problems. We extend our analysis to sampling and reconstruction schemes for monitoring time-varying bandlimited fields using mobile sensors. We demonstrate that in some situations we require a lower density of sensors when using a mobile sensing scheme instead of the conventional static sensing scheme. The exact advantage is quantified for a problem of sampling and reconstructing an audio field.Comment: Submitted to IEEE Transactions on Signal Processing May 2012; revised Oct 201

Data compression techniques applied to high resolution high frame rate video technology

An investigation is presented of video data compression applied to microgravity space experiments using High Resolution High Frame Rate Video Technology (HHVT). An extensive survey of methods of video data compression, described in the open literature, was conducted. The survey examines compression methods employing digital computing. The results of the survey are presented. They include a description of each method and assessment of image degradation and video data parameters. An assessment is made of present and near term future technology for implementation of video data compression in high speed imaging system. Results of the assessment are discussed and summarized. The results of a study of a baseline HHVT video system, and approaches for implementation of video data compression, are presented. Case studies of three microgravity experiments are presented and specific compression techniques and implementations are recommended

Vision Science and Technology at NASA: Results of a Workshop

A broad review is given of vision science and technology within NASA. The subject is defined and its applications in both NASA and the nation at large are noted. A survey of current NASA efforts is given, noting strengths and weaknesses of the NASA program

Millimeter wave MIMO communications : high-resolution angle acquisition and low-resolution time-frequency synchronization

Knowledge of the propagation channel is critical to exploit the full benefit of multiple-input multiple-output (MIMO) techniques in millimeter wave (mmWave) cellular systems. Obtaining accurate channel state information in mmWave systems, however, is challenging due to high estimation overhead, high computational complexity and on-grid setting. It is also desirable to reduce the analog-to-digital converters (ADCs) resolution at mmWave frequencies to reduce power consumption and implementation costs. The use of low-precision ADCs, though, brings new design challenges to practical cellular networks. In the first part of this dissertation, we develop several new methods to estimate and track the mmWave channel's angle-of-departure and angle-of-arrival with high accuracy and low overhead. The key ingredient of the proposed strategies is custom designed beam pairs, from which there exists an invertible function of the angle to be estimated. We further extend the proposed algorithms to dual-polarized MIMO in wideband channels, and angle tracking design for fast-varying environments. We derive analytical angle estimation error performance of the proposed methods in single-path channels. We also use numerical examples to characterize the robustness of the proposed approaches to various transceiver settings and channel conditions. In the second part of this dissertation, we focus on improving the low-resolution time-frequency synchronization performance for mmWave cellular systems. In our system model, the base station uses analog beams to send the synchronization signal with infinite-resolution digital-to-analog converters (DACs). The user equipment employs a fully digital front end to detect the synchronization signal with low-resolution ADCs. For low-resolution timing synchronization, we propose a new multi-beam probing based strategy, targeting at maximizing the minimum received synchronization signal-to-quantization-plus-noise ratio among all serving users. Regarding low-resolution frequency synchronization, we construct new sequences for carrier frequency offset (CFO) estimation and compensation. We use both analytical and numerical examples to show that the proposed sequences and the corresponding metrics used for retrieving the CFOs are robust to the quantization distortion.Electrical and Computer Engineerin