Upamanyu Madhow

Upamanyu Madhow
University of California, Santa Barbara | UCSB · Department of Electrical and Computer Engineering

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388
Publications
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Publications

Publications (388)
Article
Conventional deep neural network (DNN) training with an end-to-end cost function is unable to exert control on, or to provide guarantees regarding the features extracted by the layers of a DNN. Thus, despite the pervasive impact of DNNs, there remain significant concerns regarding their (lack of) interpretability and robustness. In this work, we de...
Article
Full-text available
Utilizing mmWave massive MIMO frontends for base station to mobile communication promises unprecedented throughput gains in cellular networks. Power efficiency is a significant bottleneck in scaling to the large array sizes required for closing the link at high frequencies, particularly in the battery-powered handset. Conventional phased array arch...
Article
Full-text available
This paper presents an algorithm-adaptable, scalable, and platform-portable generator for massive multiple-input multiple-output (MIMO) baseband processing systems. This generator is written in Chisel hardware construction language, and produces instances that implement distributed massive MIMO base station (BS) processing, including channel estima...
Preprint
While end-to-end training of Deep Neural Networks (DNNs) yields state of the art performance in an increasing array of applications, it does not provide insight into, or control over, the features being extracted. We report here on a promising neuro-inspired approach to DNNs with sparser and stronger activations. We use standard stochastic gradient...
Preprint
Speaker recognition, recognizing speaker identities based on voice alone, enables important downstream applications, such as personalization and authentication. Learning speaker representations, in the context of supervised learning, heavily depends on both clean and sufficient labeled data, which is always difficult to acquire. Noisy unlabeled dat...
Preprint
Machine learning models are known to be susceptible to adversarial attacks which can cause misclassification by introducing small but well designed perturbations. In this paper, we consider a classical hypothesis testing problem in order to develop fundamental insight into defending against such adversarial perturbations. We interpret an adversaria...
Article
We investigate the problem of localizing multiple targets using a single set of measurements from a network of radar sensors. Such "single snapshot imaging" provides timely situational awareness, but can utilize neither platform motion, as in synthetic aperture radar, nor track targets across time, as in Kalman filtering and its variants. Associati...
Preprint
Line-of-sight (LoS) multi-input multi-output (MIMO) systems exhibit attractive scaling properties with increase in carrier frequency: for a fixed form factor and range, the spatial degrees of freedom increase quadratically for 2D arrays, in addition to the typically linear increase in available bandwidth. In this paper, we investigate whether moder...
Article
This paper investigates the effect of oscillator phase noise on a multiuser millimeter wave (mmWave) massive MIMO uplink as we scale up the number of base station antennas, fixing the load factor, defined as the ratio of the number of simultaneous users to the number of base station antennas. We consider a modular approach in which the base station...
Preprint
Full-text available
Deep Neural Networks are known to be vulnerable to small, adversarially crafted, perturbations. The current most effective defense methods against these adversarial attacks are variants of adversarial training. In this paper, we introduce a radically different defense trained only on clean images: a sparse coding based frontend which significantly...
Article
Millimeter wave MIMO combines the benefits of compact antenna arrays with a large number of elements and massive bandwidths, so that fully digital beamforming has the potential of supporting a large number of simultaneous users with per user data rates of multiple gigabits/sec (Gbps). In this paper, we develop an analytical model for the impact of...
Preprint
Full-text available
Deep Neural Networks (DNNs) are vulnerable to adversarial attacks: carefully constructed perturbations to an image can seriously impair classification accuracy, while being imperceptible to humans. While there has been a significant amount of research on defending against such attacks, most defenses based on systematic design principles have been d...
Preprint
Machine learning models are vulnerable to adversarial attacks that can often cause misclassification by introducing small but well designed perturbations. In this paper, we explore, in the setting of classical composite hypothesis testing, a defense strategy based on the generalized likelihood ratio test (GLRT), which jointly estimates the class of...
Preprint
We investigate the problem of localizing multiple targets using a single set of measurements from a network of radar sensors. Such "single snapshot imaging" provides timely situational awareness, but can utilize neither platform motion, as in synthetic aperture radar, nor track targets across time, as in Kalman filtering and its variants. Associati...
Preprint
Can we distinguish between two wireless transmitters sending exactly the same message, using the same protocol? The opportunity for doing so arises due to subtle nonlinear variations across transmitters, even those made by the same manufacturer. Since these effects are difficult to model explicitly, we investigate learning device fingerprints using...
Preprint
The vulnerability of deep neural networks to small, adversarially designed perturbations can be attributed to their "excessive linearity." In this paper, we propose a bottom-up strategy for attenuating adversarial perturbations using a nonlinear front end which polarizes and quantizes the data. We observe that ideal polarization can be utilized to...
Preprint
Millimeter wave MIMO combines the benefits of compact antenna arrays with a large number of elements and massive bandwidths, so that fully digital beamforming has the potential of supporting a large number of simultaneous users with {\it per user} data rates of multiple gigabits/sec (Gbps). In this paper, we develop an analytical model for the impa...
Article
We investigate synthesis of a large effective aperture using a sparse array of subarrays. We employ a multi-objective optimization framework for placement of subarrays within a prescribed area dictated by form factor constraints, trading off the smaller beam width obtained by spacing out the subarrays against the grating and side lobes created by s...
Article
Picocellular architectures are essential for providing the spatial reuse required to satisfy the everincreasing demand for mobile data. A key deployment challenge is to provide backhaul connections with sufficiently high data rate. Providing wired support (e.g., using optical fiber) to pico base stations deployed opportunistically on lampposts and...
Preprint
This paper investigates the effect of oscillator phase noise on a multiuser millimeter wave (mmWave) massive MIMO uplink as we scale up the number of base station antennas, fixing the load factor, defined as the ratio of the number of simultaneous users to the number of base station antennas. We consider a modular approach in which the base station...
Article
Millimeter (mm) wave picocellular networks are a promising approach for delivering the 1000-fold capacity increase required to keep up with projected demand for wireless data: the available bandwidth is orders of magnitude larger than that in existing cellular systems, and the small carrier wavelength enables the realization of highly directive ant...
Preprint
We investigate synthesis of a large effective aperture using a sparse array of subarrays. We employ a multi-objective optimization framework for placement of subarrays within a prescribed area dictated by form factor constraints, trading off the smaller beam width obtained by spacing out the subarrays against the grating and side lobes created by s...
Article
In this paper, we develop a theoretical framework for short-range millimeter (mm) wave radar imaging using a sparse array of monostatic elements, and validate it via experiments. The framework is a significant departure from classical radar, which largely focuses on long-range settings in which targets are well modeled as point scatterers. For spar...
Preprint
A "wireless fingerprint" which exploits hardware imperfections unique to each device is a potentially powerful tool for wireless security. Such a fingerprint should be able to distinguish between devices sending the same message, and should be robust against standard spoofing techniques. Since the information in wireless signals resides in complex...
Preprint
Millimeter (mm) wave picocellular networks are a promising approach for delivering the 1000-fold capacity increase required to keep up with projected demand for wireless data: the available bandwidth is orders of magnitude larger than that in existing cellular systems, and the small carrier wavelength enables the realization of highly directive ant...
Preprint
It is by now well-known that small adversarial perturbations can induce classification errors in deep neural networks. In this paper, we make the case that a systematic exploitation of sparsity is key to defending against such attacks, and that a "locally linear" model for neural networks can be used to develop a theoretical foundation for crafting...
Article
We consider the problem of optimal precoder design for a multi-input single-output wideband wireless system to maximize two different figures of merit: the total communication capacity and the total received power, subject to individual power constraints on each transmit element. We show that the two optimal precoders satisfy a Separation Principle...
Preprint
Picocellular architectures are essential for providing the spatial reuse required to satisfy the ever-increasing demand for mobile data. A key deployment challenge is to provide backhaul connections with sufficiently high data rate. Providing wired support (e.g., using optical fiber) to pico base stations deployed opportunistically on lampposts and...
Chapter
Introduction to Communication Systems - by Upamanyu Madhow November 2014
Chapter
Introduction to Communication Systems - by Upamanyu Madhow November 2014
Article
It is by now well-known that small adversarial perturbations can induce classification errors in deep neural networks (DNNs). In this paper, we make the case that sparse representations of the input data are a crucial tool for combating such attacks. For linear classifiers, we show that a sparsifying front end is provably effective against $\ell_{\...
Article
There is growing evidence regarding the importance of spike timing in neural information processing, with even a small number of spikes carrying information, but computational models lag significantly behind those for rate coding. Experimental evidence on neuronal behavior is consistent with the dynamical and state dependent behavior provided by re...
Article
Full-text available
We propose a concept system termed distributed base station (DBS), which enables distributed transmit beamforming at large carrier wavelengths to achieve significant range extension and/or increased downlink data rate, providing a low-cost infrastructure for applications such as rural broadband. We consider a frequency division duplexed (FDD) syste...
Article
Millimeter (mm) wave massive MIMO has the potential for delivering orders of magnitude increases in mobile data rates, with compact antenna arrays providing narrow steerable beams for unprecedented levels of spatial reuse. A fundamental technical bottleneck, however, is rapid spatial channel estimation and beam adaptation in the face of mobility an...
Article
Deep neural networks represent the state of the art in machine learning in a growing number of fields, including vision, speech and natural language processing. However, recent work raises important questions about the robustness of such architectures, by showing that it is possible to induce classification errors through tiny, almost imperceptible...
Article
Full-text available
In this paper, we develop a theoretical framework for analyzing the measurable information content of an unknown scene through an active electromagnetic imaging array. We consider monostatic and multistatic array architectures in a one-dimensional setting. Our main results include the following: (a) we introduce the space-bandwidth product (SBP), a...
Conference Paper
Millimeter (mm) wave picocellular networks have the potential for providing the 1000X capacity increase required to keep up with the explosive growth of mobile data. However, maintaining beams towards mobile users and adapting to frequent blockage, requires efficient, dynamic path tracking algorithms. In this paper, we develop and experimentally de...
Article
The scaling of analog-to-digital converter (ADC) power consumption with communication bandwidth imposes severe limits on its precision which significantly impacts receiver performance. In this paper, we consider a “space-time” generalization of the flash architecture by allowing a fixed number of slicers to be dispersed in time (i.e., sampling offs...
Article
The "fire together, wire together" Hebbian model is a central principle for learning in neuroscience, but surprisingly, it has found limited applicability in modern machine learning. In this paper, we take a first step towards bridging this gap, by developing flavors of competitive Hebbian learning which produce sparse, distributed neural codes usi...
Article
We consider the problem of multicasting a common message signal from a distributed array of wireless transceivers by beamforming to a set of beam targets, while simultaneously protecting a set of null targets by nullforming to them. We describe a distributed algorithm in which each transmitter iteratively adapts its complex transmit weight using co...
Article
As communication systems scale up in bandwidth, the limited resolution in high-speed analog-to-digital converters (ADCs) is a key challenge in realizing low-cost 'mostly digital' transceiver architectures. This motivates a systematic effort to understand the limits of such architectures under the severe quantization constraints imposed by the use o...
Article
We investigate analog multiband as a means of scaling communication bandwidths over dispersive channels: the available band is channelized into contiguous subbands in the analog domain and digitized in parallel at the receiver. The subband width is chosen such that existing analog-to-digital converter (ADC) technology provides dynamic range suffici...
Article
We propose, analyze and demonstrate an architecture for scalable cooperative reception. In a cluster of N + 1 receive nodes, one node is designated as the final receiver, and the N other nodes act as amplify-and-forward relays which adapt their phases such that the relayed signals add up constructively at the designated receiver. This yields receiv...
Conference Paper
We propose a fast sequential algorithm for the fundamental problem of estimating continuous-valued frequencies and amplitudes using samples of a noisy mixture of sinusoids. Each step consists of two phases: detection of a new sinusoid, and refining the parameters of already detected sinusoids. The detection phase is performed on an oversampled DFT...
Conference Paper
We consider distributed transmit beamforming from a cluster of cooperating nodes towards a distant destination, over a wideband dispersive channel. We consider explicit aggregate feedback, with the destination broadcasting its feedback to all nodes in the transmit cluster. Explicit feedback allows for frequency division duplex (FDD) operation, sinc...
Conference Paper
At high carrier frequencies, spatial multiplexing gains can be obtained even in line of sight (LoS) environments with reasonable node form factors. We investigate design of a LoS MIMO link operating at millimeter (mm) wave frequencies beyond 100 GHz, with 4-fold spatial multiplexing, and bandwidth of 10–20 GHz, with data rates even with relatively...
Article
Full-text available
Spectral embedding based on the Singular Value Decomposition (SVD) is a widely used "preprocessing" step in many learning tasks, typically leading to dimensionality reduction by projecting onto a number of dominant singular vectors and rescaling the coordinate axes (by a predefined function of the singular value). However, the number of such vector...
Article
Full-text available
We propose a fast sequential algorithm for the fundamental problem of estimating continuous-valued frequencies and amplitudes using samples of a noisy mixture of sinusoids. The algorithm is a natural generalization of Orthogonal Matching Pursuit (OMP) to the continuum using Newton refinements, and hence is termed Newtonized OMP (NOMP). Each iterati...
Conference Paper
The exponential growth in demand for mobile data requires significant increases in spatial reuse, motivating an evolution towards picocellular architectures with densely deployed base stations. Providing backhaul for such a network is a key challenge, because of the high access link rates, and the cost and difficulty of running optical fiber to bas...
Article
We propose and investigate a compressive architecture for estimation and tracking of sparse spatial channels in millimeter (mm) wave picocellular networks. The base stations are equipped with antenna arrays with a large number of elements (which can fit within compact form factors because of the small carrier wavelength) and employ radio frequency...
Article
In this paper, we consider the problem of frequency and phase tracking with intermittent measurements. While this problem is of fundamental interest, we are primarily motivated by the coherence requirements of distributed MIMO (DMIMO) applications in which cooperating nodes emulate a virtual antenna array and frequency synchronization among transmi...
Article
We report on experimental results, and associated theory, for a 60 GHz synthetic aperture radar (SAR) testbed for short-range (sub-meter) imaging. Our testbed consists of a monostatic radar with synchronized transmitter and receiver, with lateral motion (over 10-30 cm) providing the SAR geometry, and range resolution provided by stepped frequency c...
Article
This paper considers a problem of distributed nullforming, in which multiple wireless transmitters steer a null toward a designated receiver by only adjusting their carrier phases. Since each transmitter transmits at full power, the system maximizes “power pooling” gains for cooperative communication or jamming, while simultaneously protecting a de...