R-3 Repository :: Browsing by Author "Sabharwal, Ashutosh"

Browsing by Author "Sabharwal, Ashutosh"

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1-bit Phase Shifters for Large-Antenna Full-Duplex mmWave Communications
(IEEE, 2020) da Silva, José Mairton Barros Jr.; Sabharwal, Ashutosh; Fodor, Gábor; Fischione, Carlo
Millimeter-wave using large-antenna arrays is a key technological component for the future cellular systems, where it is expected that hybrid beamforming along with quantized phase shifters will be used due to their implementation and cost efficiency. In this paper, we investigate the efficacy of full-duplex mmWave communication with hybrid beamforming using low-resolution phase shifters. We assume that the self-interference can be sufficiently cancelled by a combination of propagation domain and digital self-interference techniques, without any analog self-interference cancellation. We formulate the problem of joint self-interference suppression and downlink beamforming as a mixed-integer nonconvex joint optimization problem. We propose LowRes, a near-to-optimal solution using penalty dual decomposition. Numerical results indicate that LowRes using low-resolution phase shifters perform within 3% of the optimal solution that uses infinite phase shifter resolution. Moreover, even a single quantization bit outperforms half-duplex transmissions, respectively by 29% and 10% for both low and high residual self-interference scenarios, and for a wide range of practical antenna to radio-chain ratios. Thus, we conclude that 1-bit phase shifters suffice for full-duplex millimeter-wave communications, without requiring any additional new analog hardware.
3PointTM: Faster Measurement of High-Dimensional Transmission Matrices
(2020-04-23) Chen, June; Sabharwal, Ashutosh
A transmission matrix (TM) describes the linear relationship between input and output when a coherent wavefront passes through a scattering medium. Measurement of the TM enables numerous applications, such as focusing light and image reconstruction. However, measuring TM continues to be very challenging due to its large dimension. The state-of-the-art methods, including phase-shifting holography and double phase retrieval, require significant amounts of measurements, and the subsequent data processing is often slow and computationally intensive. In this thesis, we propose a solution for transmission matrix recovery, called 3PointTM, that uses a minimal number of measurements per pixel for TM recovery. As a result, 3PointTM reduces the measurement budget by a factor of two, as compared to phase-shifting holography. This enables the acquisition of TMs at high resolutions and with low computational complexity. We validate our approach on both real and simulated data, and in particular demonstrate focusing of light and image reconstruction on dense scattering media in high SNR settings at 4X reduced complexity.
A Computational Analysis of Meal Events Using Food Diaries and Continuous Glucose Monitors
(2023-04-21) Pai, Amruta; Sabharwal, Ashutosh; Allen, Genevera; Patel, Ankit; Beier, Margaret; Kerr, David
Diet self-management, through its effect on weight and glycemic control, is one of the cornerstones of Type 2 Diabetes (T2D) prevention and management. A quantitative understanding of bio-behavioral mechanisms of diet is needed to create effective diet self-management tools. Smartphone diet-tracking applications and continuous glucose monitors (CGMs) are emerging devices that enable dense sampling of an individual's diet. Research in diet analysis of app-based food diaries and CGMs have mainly focused on developing aggregate measures of nutrient intake and glucose responses. However, innovative computational analysis is required to infer actionable insights. In this thesis, we develop computational measures for various bio-behavioral aspects of diet by leveraging meal event data collected with food diaries and CGMs. First, we establish recurrent consumption measures across meal events to characterize habitual behavior in an individual's diet. We leverage a large publicly available MyFitnessPal (MFP) food diary dataset to provide novel insights on differences in habitual behavior across individuals and temporal contexts. Next, we develop calorie compensation measures to characterize self-regulatory behavior. A quantitative analysis of calorie compensation measures on the MFP dataset reveals significant meal compensation patterns and their impact on adherence to self-set calorie goals. Finally, we designed an observational study using the MFP app and CGMs to evaluate the impact of meal events on glycemic control in adults with varying hemoglobin a1c levels. We developed elevated meal event count to characterize mealtime glucose responses by exploiting its association with hemoglobin a1c. Elevated meal event count significantly affected glycemic control, suggesting its value as a novel event-driven glycemic target metric. This thesis highlights the value of using CGMs and food diaries to broaden our understanding of diet. The developed measures augment existing intake measures and could be used as a digital bio-behavioral markers to personalize diet self-management strategies.
A Matter of Perspective: Reliable Communication and Coping with Interference with Only Local Views
(2012-09-05) Kao, David; Sabharwal, Ashutosh; Aazhang, Behnaam; Knightly, Edward W.; Tapia, Richard A.; Chiang, Mung
This dissertation studies interference in wireless networks. Interference results from multiple simultaneous attempts to communicate, often between unassociated sources and receivers, preventing extensive coordination. Moreover, in practical wireless networks, learning network state is inherently expensive, and nodes often have incomplete and mismatched views of the network. The fundamental communication limits of a network with such views is unknown. To address this, we present a local view model which captures asymmetries in node knowledge. Our local view model does not rely on accurate knowledge of an underlying probability distribution governing network state. Therefore, we can make robust statements about the fundamental limits of communication when the channel is quasi-static or the actual distribution of state is unknown: commonly faced scenarios in modern commercial networks. For each local view, channel state parameters are either perfectly known or completely unknown. While we propose no mechanism for network learning, a local view represents the result of some such mechanism. We apply the local view model to study the two-user Gaussian interference channel: the smallest building block of any interference network. All seven possible local views are studied, and we find that for five of the seven, there exists no policy or protocol that universally outperforms time-division multiplexing (TDM), justifying the orthogonalized approach of many deployed systems. For two of the seven views, TDM-beating performance is possible with use of opportunistic schemes where opportunities are revealed by the local view. We then study how message cooperation --- either at transmitters or receivers --- increases capacity in the local view two-user Gaussian interference channel. The cooperative setup is particularly appropriate for modeling next-generation cellular networks, where costs to share message data among base stations is low relative to costs to learn channel coefficients. For the cooperative setting, we find: (1) opportunistic approaches are still needed to outperform TDM, but (2) opportunities are more abundant and revealed by more local views. For all cases studied, we characterize the capacity region to within some known gap, enabling computation of the generalized degrees of freedom region, a visualization of spatial channel resource usage efficiency.
A protocol class for stealing residual bandwidth in uncoordinated distributed wireless networks
(2010) Novich, Scott David; Sabharwal, Ashutosh
The need for finding effective means of recycling spectrum is becoming increasingly apparent as the world becomes more crowded with wireless devices. While finding a policy solution to this problem will require years, "cognitive radio" is an immediately applicable technology-based solution. Our attention is focused on how a distributed uncoordinated cognitive group of "secondary" users (those with lower priority access to the spectrum) can push data through its network on a single band and in the presence of non-cognitive "primary" users (those with priority access to the spectrum). The main contribution is a novel class of cognitive radio protocols that accomplish this through feedback, where secondaries estimate residual bandwidth and adapt a performance-based parameter. This class of solutions is presented, its parameters are explored and a specific implementation is demonstrated with insights gained.
A Robust Algorithm for Identification of Motion Artifacts in Photoplethysmography Signals
(2018-12-03) Maity, Akash Kumar; Sabharwal, Ashutosh; Veeraraghavan, Ashok; Heckel, Reinhard
Photoplethysmography(PPG) is commonly used as a means of continuous health monitoring. Many clinically relevant parameters like heart rate (HR), blood oxygenaton level (SPO2) are derived from the sensor measurements using PPG. Presence of motion artifacts in the signal decreases the accuracy of estimating the parameters and therefore reduces the reliabilty of these sensor devices. Motion artifacts can be both periodic or aperiodic. Existing state-of-the-art methods for motion detection rely on the semi-periodic structure of PPG to distinguish from aperiodic motion artifacts. Periodic motion artifacts that can be introduced by perioidic movements like hand tapping, jogging, cannot be detected by current methods reliably. In this thesis, we propose a novel technique, PPGMotion, for identifying all motion artifacts in PPG signals. PPGMotion relies on the morphological structure of artifact-free PPG signal, which has a fast systolic phase and a slowly decaying diastolic phase. We note that in the presence of motion artifacts, the recorded PPG signals do not exhibit the characteristic PPG shape. Our approach uses this prior information about the PPG morphology to reliable detect periodic motion artifacts, without the need of any additional hardware components like an accelerometer. To evaluate the proposed method, we adopt both a simulation and real data collection. For simulation-based iii analysis, we use a generative model for motion artifacts to simulate different cases of motion artifacts. For real data, we have compared our approach against recent works on motion identification using 3 datasets, where we record the PPG from a pulse-oximeter attached to a finger with subjects making (1) random finger movements, (2) periodic movements like periodic finger tapping and (3) PPG recordings from Maxim smartwatch with subjects running on a treadmill. Dataset (2) and (3) are expected to introduce periodic motion artifacts in the measured PPG signals. We demonstrate that while our approach is similar in performance to previous methods when random motion artifacts are introduced, the performance is significantly better in the presence of periodic motion artifacts. We show that for simulated dataset, the performance of PPGMotion is significantly better than existing work as the contaminated PPG tends to become periodic, with an increase in sensitivity of atleast 10% over state-of-the-art method. For real data, PPGMotion is successful in identifying the periodic motion artifacts, with mean sensitivity of 95% and accuracy of 95.8%, compared to the state-of-the-art method with mean sensitivity of 66% and accuracy of 89% for dataset (2). For dataset (1), PPGMotion achieves an accuracy of 96.35% with sensitivity of 95.29%, and for dataset (3), PPGMotion achieves an accuracy of 91.89% and sensitivity of 93.03%, compared to the second best method with accuracy 81.23% and sensitivity 74.99%.
Achievable Diversity and Multiplexing in Multiple Antenna Systems with Quantized Power Control
(2005-05-01) Khoshnevis, Ahmad; Sabharwal, Ashutosh; Center for Multimedia Communications (http://cmc.rice.edu/)
We consider a multiple antenna system with finite rate feedback, in which the quantized channel state information at the transmitter is used solely for temporal power control. We show that similar to systems without feedback, the tradeoff between diversity order and multiplexing gain exists. However, unlike the systems with feedback that apply both rate and power control, systems with only power control are unable of achieving non-zero diversity order at the maximum multiplexing gain. The analysis is based on asymptotic behavior of the distribution of order statistics of the eigenvalues of channel matrix, which is a key step in evaluating the diversity order.
Achievable Rates for Arbitrary Network Topologies with â Cheapâ Nodes
(2003-05-01) Khojastepour, Mohammad; Sabharwal, Ashutosh; Aazhang, Behnaam; Center for Multimedia Communications (http://cmc.rice.edu/)
In this paper, we derive achievable rates for arbitrary network topologies consisting of â cheapâ nodes. A node is labeled â cheapâ if its radio can only operate in TDD mode when transmitting and receiving in the same frequency band. Two main results are shown. The first result provides an achievable rate for the channel with either continuous alphabet or discrete channel. The second result provides the achievable rate for the Gaussian channel with average power constraint. The two results are applied to the case of Gaussian relay channel and concatenated channel with cheap nodes
AmbianceCount: An Objective Social Ambiance Measure from Unconstrained Day-long Audio Recordings
(2020-12-07) Chen, Wenwan; Sabharwal, Ashutosh
Measuring social ambiance in unconstrained environments is of significant importance in mental health due to the association between sociability and psychological outcome. However, it has been challenging to quantify social ambiance since existing objective methods fail to capture the transient ambiance patterns in unconstrained environments. In this thesis, I present AmbianceCount, an automatic and objective method that extracts social ambiance from unconstrained audio recordings by estimating the number of concurrent speakers. AmbianceCount consists of a supervised deep neural network (DNN) embedding extractor to differentiate speech mixtures, and a scoring system for estimation and improving generalization. The performance of Am- bianceCount is compared with baseline and evaluated on several synthesized datasets. Lastly, I utilize AmbianceCount to evaluate data from a sociability pilot, with audio data from depression and psychosis patients as well as age-matched healthy controls. Our analysis shows that extracted social ambiance patterns are significantly different across three groups. Besides, it is observed that captured social ambiance patterns are associated with psychometric and personality scores, which is consistent with clinical diagnosis.
An Objective System for Quantitative Assessment of Television Viewing Among Children (Family Level Assessment of Screen Use in the Home-Television): System Development Study
(JMIR, 2022) Vadathya, Anil Kumar; Musaad, Salma; Beltran, Alicia; Perez, Oriana; Meister, Leo; Baranowski, Tom; Hughes, Sheryl O.; Mendoza, Jason A.; Sabharwal, Ashutosh; Veeraraghavan, Ashok; O'Connor, Teresia
Background: Television viewing among children is associated with developmental and health outcomes, yet measurement techniques for television viewing are prone to errors, biases, or both. Objective: This study aims to develop a system to objectively and passively measure children’s television viewing time. Methods: The Family Level Assessment of Screen Use in the Home-Television (FLASH-TV) system includes three sequential algorithms applied to video data collected in front of a television screen: face detection, face verification, and gaze estimation. A total of 21 families of diverse race and ethnicity were enrolled in 1 of 4 design studies to train the algorithms and provide proof of concept testing for the integrated FLASH-TV system. Video data were collected from each family in a laboratory mimicking a living room or in the child’s home. Staff coded the video data for the target child as the gold standard. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value were calculated for each algorithm, as compared with the gold standard. Prevalence and biased adjusted κ scores and an intraclass correlation using a generalized linear mixed model compared FLASH-TV’s estimation of television viewing duration to the gold standard. Results: FLASH-TV demonstrated high sensitivity for detecting faces (95.5%-97.9%) and performed well on face verification when the child’s gaze was on the television. Each of the metrics for estimating the child’s gaze on the screen was moderate to good (range: 55.1% negative predictive value to 91.2% specificity). When combining the 3 sequential steps, FLASH-TV estimation of the child’s screen viewing was overall good, with an intraclass correlation for an overall time watching television of 0.725 across conditions. Conclusions: FLASH-TV offers a critical step forward in improving the assessment of children’s television viewing.
Analysis of Decision-Feedback Based Broadband OFDM Systems
(2005-11-01) de Baynast, Alexandre; Sabharwal, Ashutosh; Aazhang, Behnaam; Center for Multimedia Communications (http://cmc.rice.edu/)
In wireless communications, about 25% of the bandwidth is dedicated to training symbols for channel estimation. By using a semi-blind approach, the training sequence length can be reduced while improving performance. The principle is as follows: the detected symbols (hard decision) are fed back to the channel estimator in order to re-estimate the channel more accurately. However, semi-blind approach can significantly deteriorate the performance if the bit error rate is high. In this paper, we propose to determine analytically the minimum Signal to Noise Ratio (SNR) from which a semi-blind method starts to outperform a training sequence based only system.
Analysis of scalable channel estimation in FDD massive MIMO
(Springer Nature, 2023) Zhang, Xing; Sabharwal, Ashutosh
One of the key ideas for reducing downlink channel acquisition overhead for FDD massive MIMO systems is to exploit a combination of two assumptions: (i) the dimension of channel models in propagation domain may be much smaller than the next-generation base-station array sizes (e.g., 64 or more antennas), and (ii) uplink and downlink channels may share the same low-dimensional propagation domain. Our channel measurements demonstrate that the two assumptions may not always hold, thereby impacting the predicted performance of methods that rely on the above assumptions. In this paper, we analyze the error in modeling the downlink channel using uplink measurements, caused by the mismatch from the above two assumptions. We investigate how modeling error varies with base-station array size and provide both numerical and experimental results. We observe that modeling error increases with the number of base-station antennas, and channels with larger angular spreads have larger modeling error. Utilizing our modeling error analysis, we then investigate the resulting beamforming performance rate loss. Accordingly, we observe that the rate loss increases with the number of base-station antennas, and channels with larger angular spreads suffer from higher rate loss.
Annealed Langevin Dynamics for MIMO Communications
(2024-01-29) Zilberstein, Nicolas M; Segarra, Santiago; Sabharwal, Ashutosh
Solving the optimal data detection problem in multiple-input multiple-output (MIMO) systems is known to be NP-hard. Moreover, the difficulty is exacerbated when the channel state information is unavailable. In this work we propose a MIMO detector for the two scenarios, namely when the CSI is known and when it is unknown. First, for the case of perfect CSI, we proposed a MIMO detector based on an annealed version of Langevin dynamics. More precisely, we define a stochastic dynamical process whose stationary distribution coincides with the posterior distribution of the data given our observations. This allows us to approximate the maximum a posteriori estimator of the transmitted symbols by sampling from the proposed Langevin dynamic. We carefully craft this stochastic dynamic by gradually adding a sequence of noise with decreasing variance to the trajectories, which ensures that the estimated symbols belong to a pre-specified discrete constellation. Second, for the case of unknown CSI, we propose a joint data detection and channel estimation solution, where we define an annealed Langevin diffusion whose stationary distribution is the joint posterior of the channels and data given noisy observations.
Antenna Packing in Low Power Systems: Communication Limits and Array Design
(2008) Muharemovic, Tarik; Sabharwal, Ashutosh; Aazhang, Behnaam; Center for Multimedia Communications (http://cmc.rice.edu/)
In this paper, we study design of transceiver antenna arrays and its impact on spectral efficiency of low-power systems. Our primary motivation is construction of practical and portable multi-antenna configurations with a very small and a-priori fixed volume for placing antennas. Using spectral efficiency as a target metric for array optimization, we show that any array configuration, transmit or receive, can be characterized via a parameter that we interpret as "effective degrees of freedom." For any array configuration, effective degrees of freedom describes an equivalent uncorrelated array, which results in the same low-power behavior of spectral efficiency. Joint optimization of transmit and receive antenna configurations decouples into maximizing effective degrees of freedom for transmitter and receiver separately. To achieve this goal, we introduce and study a theoretical benchmark of "limiting degrees of freedom," which is the least upper bound on effective degrees of freedom, evaluated over all configurations with finite number of antennas. Limiting degrees of freedom therefore describes the best possible performance for any transceiver array which confines its elements inside a given space. We compute a closed-form expression for limiting degrees of freedom of a circular geometry. Finally, we present numerical procedure and examples for designing linear and square arrays with non-uniform spacing, which typically exhibit significant spectral efficiency gains over uniform arrays.
An Approach to Capacity Analysis of Coarsely Coordinated Low Power Multiple Access Systems
(2004-07-01) Muharemovic, Tarik; Sabharwal, Ashutosh; Aazhang, Behnaam; Center for Multimedia Communications (http://cmc.rice.edu/)
We consider multiaccess problem in low power systems, where we allow each user to select its own data rate and transmit power locally and independently from other users. Here, every user has a set of low power codebooks, labeled a policy, which accomodates a range of small spectral efficiencies, while treating instantaneous data rates of other users as an unknown compound parameter. Even with such coarse user coordination, multiuser detection enables a system which is superior to any classic orthogonal division system. First we fully characterise the set of achievable policies, after which we demonstrate that in multiantenna systems, policies are be viewed as awarding protected receiver spatial dimensions to each user.
Architectures for Cognitive Radio Testbeds and Demonstrators – An Overview
(IEEE, 2010-06-01) Gustafsson, Oscar; Amiri, Kiarash; Andersson, Dennis; Blad, Anton; Bonner, Christian; Cavallaro, Joseph R.; Declerck, Jeroen; Dejonghe, Antoine; Eliardsson, Patrik; Glasse, Miguel; Hayar, Aawatif; Hollevoet, Lieven; Hunter, Chris; Joshi, Madhura; Kaltenberger, Florian; Knopp, Raymond; Le, Khanh; Miljanic, Zoran; Murphy, Patrick; Naessens, Frederik; Nikaein, Navid; Nussbaum, Dominique; Pacalet, Renaud; Raghavan, Praveen; Sabharwal, Ashutosh; Sarode, Onkar; Spasojevic, Predrag; Sun, Yang; Tullberg, Hugo M.; Vander Aa, Tom; Van der Perre, Liesbet; Wetterwald, Michelle; Wu, Michael; Center for Multimedia Communication
Wireless communication standards are developed at an ever-increasing rate of pace, and significant amounts of effort is put into research for new communication methods and concepts. On the physical layer, such topics include MIMO, cooperative communication, and error control coding, whereas research on the medium access layer includes link control, network topology, and cognitive radio. At the same time, implementations are moving from traditional fixed hardware architectures towards software, allowing more efficient development. Today, field-programmable gate arrays (FPGAs) and regular desktop computers are fast enough to handle complete baseband processing chains, and there are several platforms, both open-source and commercial, providing such solutions. The aims of this paper is to give an overview of five of the available platforms and their characteristics, and compare the features and performance measures of the different systems.
Argos: Practical Base Stations for Large-scale Beamforming
(2012-09-05) Shepard, Clayton; Zhong, Lin; Knightly, Edward W.; Sabharwal, Ashutosh
MU-MIMO theory predicts manyfold capacity gains by leveraging many antennas (e.g. M >> 10) on wireless base stations to serve many users simultaneously through multi-user beamforming (MUBF). However, realizing such a large-scale design is nontrivial, and has yet to be achieved in the real world. We present the design, realization, and evaluation of Argos, the first reported large-scale base station that is capable of serving many (e.g., 10s of) terminals simultaneously through MUBF. Designed with extreme flexibility and scalability in mind, Argos exploits hierarchical and modular design principles, properly partitions baseband processing, and holistically considers real-time requirements of MUBF. To achieve unprecedented scalability, we devise a novel, completely distributed, beamforming technique, as well as an internal calibration procedure to enable implicit beamforming across large arrays. We implement a prototype with 64 antennas, and demonstrate that it can achieve up to 6.7 fold capacity gains while using a mere 1/64th the transmission power.
Baseline leptin predicts response to metformin in adolescents with type 1 diabetes and increased body mass index
(Wiley, 2023) Ismail, Heba M.; Barua, Souptik; Wang, Johnny; Sabharwal, Ashutosh; Libman, Ingrid; Bacha, Fida; Nadeau, Kristen J.; Tosur, Mustafa; Redondo, Maria J.
Beamformer Design with Feedback Rate Constraints : Criteria and Constructions
(2003-07-20) Mukkavilli, Krishna Kiran; Sabharwal, Ashutosh; Erkip, Elza; Aazhang, Behnaam; Center for Multimedia Communications (http://cmc.rice.edu/)
In this work, we provide a geometrical framework for the analysis and design of beamformer codebooks with finite number of beamformer vectors. We present a design criterion for good beamfomer codebooks and show the equivalence of the beamformer design problem to two other known problems. First, the beamformer design problem can be directly posed as a problem of packing 2 dimensional subspaces in a 2t dimensional Grassmannian manifold, t being the number of transmit antennas. And second, under certain conditions, the beamformer design problem is equivalent to the construction of unitary space time constellations.
Beamforming in MIMO-OFDM systems: Codebook design for efficient implementation
(2007) Duarte, Melissa; Sabharwal, Ashutosh
Quantized feedback in multiple antenna systems has potential to increase throughput and/or reduce probability of outage. In this work, we present a method to generate quantization codebooks tailored for efficient implementation of beamforming-based Multiple-Input Multiple-Output (MIMO) transmissions. The proposed codebooks can reduce computational requirements significantly, making feasible an efficient architecture for a real-time transmit beamforming and receive combining MIMO orthogonal frequency division multiplexing (OFDM) system. Simulation results validate the proposed codebook construction method and architecture.

Browsing by Author "Sabharwal, Ashutosh"

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