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AuthorHassibi, Babak (5)Kostina, Victoria (2)Alanwar, Amr (1)Anwar, Fatima M. (1)Cai, Jian-Feng (1)View MoreJournal2016 IEEE 55th Conference on Decision and Control (CDC) (2)2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (2)2016 50th Asilomar Conference on Signals, Systems and Computers (1)2016 54th Annual Allerton Conference on Communication, Control, and Computing (Allerton) (1)2017 11th European Conference on Antennas and Propagation (EUCAP) (1)View MoreKAUST Grant NumberKAUST-002 (1)OCRF-2014-CRG-3 (1)OSR-2015-Sensors-2700 (1)Publisher

Institute of Electrical and Electronics Engineers (IEEE) (10)

Subject4G (1)Approximation algorithms (1)Blind equalizers (1)Compressed sensing (1)Convolution (1)View MoreType
Conference Paper (10)

Year (Issue Date)
2017 (10)

Item AvailabilityMetadata Only (10)

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Cyclops: PRU programming framework for precise timing applications

Alanwar, Amr; Anwar, Fatima M.; Zhang, Yi-Fan; Pearson, Justin; Hespanha, Joao; Srivastava, Mani B. (2017 IEEE International Symposium on Precision Clock Synchronization for Measurement, Control, and Communication (ISPCS), Institute of Electrical and Electronics Engineers (IEEE), 2017-10-05) [Conference Paper]

The Beaglebone Black single-board computer is well-suited for real-time embedded applications because its system-on-a-chip contains two

Constrained blind deconvolution using Wirtinger flow methods

Walk, Philipp; Jung, Peter; Hassibi, Babak (2017 International Conference on Sampling Theory and Applications (SampTA), Institute of Electrical and Electronics Engineers (IEEE), 2017-09-04) [Conference Paper]

In this work we consider one-dimensional blind deconvolution with prior knowledge of signal autocorrelations in the classical framework of polynomial factorization. In particular this univariate case highly suffers from several non-trivial ambiguities and therefore blind deconvolution is known to be ill-posed in general. However, if additional autocorrelation information is available and the corresponding polynomials are co-prime, blind deconvolution is uniquely solvable up to global phase. Using lifting, the outer product of the unknown vectors is the solution to a (convex) semi-definite program (SDP) demonstrating that -theoretically- recovery is computationally tractable. However, for practical applications efficient algorithms are required which should operate in the original signal space. To this end we also discuss a gradient descent algorithm (Wirtinger flow) for the original non-convex problem. We demonstrate numerically that such an approach has performance comparable to the semidefinite program in the noisy case. Our work is motivated by applications in blind communication scenarios and we will discuss a specific signaling scheme where information is encoded into polynomial roots.

Balanced and sparse Tamo-Barg codes

Halbawi, Wael; Duursma, Iwan; Dau, Hoang; Hassibi, Babak (2017 IEEE International Symposium on Information Theory (ISIT), Institute of Electrical and Electronics Engineers (IEEE), 2017-08-29) [Conference Paper]

We construct balanced and sparse generator matrices for Tamo and Barg's Locally Recoverable Codes (LRCs). More specifically, for a cyclic Tamo-Barg code of length n, dimension k and locality r, we show how to deterministically construct a generator matrix where the number of nonzeros in any two columns differs by at most one, and where the weight of every row is d + r - 1, where d is the minimum distance of the code. Since LRCs are designed mainly for distributed storage systems, the results presented in this work provide a computationally balanced and efficient encoding scheme for these codes. The balanced property ensures that the computational effort exerted by any storage node is essentially the same, whilst the sparse property ensures that this effort is minimal. The work presented in this paper extends a similar result previously established for Reed-Solomon (RS) codes, where it is now known that any cyclic RS code possesses a generator matrix that is balanced as described, but is sparsest, meaning that each row has d nonzeros.

Location-aware network operation for cloud radio access network

Wang, Fanggang; Ruan, Liangzhong; Win, Moe Z. (2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Institute of Electrical and Electronics Engineers (IEEE), 2017-06-20) [Conference Paper]

One of the major challenges in effectively operating a cloud radio access network (C-RAN) is the excessive overhead signaling and computation load that scale rapidly with the size of the network. In this paper, the exploitation of location information of the mobile devices is proposed to address this challenge. We consider an approach in which location-assisted channel state information (CSI) acquisition methods are introduced to complement conventional pilot-based CSI acquisition methods and avoid excessive overhead signaling. A low-complexity algorithm is designed to maximize the sum rate. An adaptive algorithm is also proposed to address the uncertainty issue in CSI acquisition. Both theoretical and numerical analyses show that location information provides a new dimension to improve throughput for next-generation massive cooperative networks.

Large scale 2D spectral compressed sensing in continuous domain

Cai, Jian-Feng; Xu, Weiyu; Yang, Yang (2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Institute of Electrical and Electronics Engineers (IEEE), 2017-06-20) [Conference Paper]

We consider the problem of spectral compressed sensing in continuous domain, which aims to recover a 2-dimensional spectrally sparse signal from partially observed time samples. The signal is assumed to be a superposition of s complex sinusoids. We propose a semidefinite program for the 2D signal recovery problem. Our model is able to handle large scale 2D signals of size 500 × 500, whereas traditional approaches only handle signals of size around 20 × 20.

Low profile frequency agile MIMO slot antenna with TCM characterization

Ghalib, Asim; Hussain, Rifaqat; Sharawi, Mohammad S. (2017 11th European Conference on Antennas and Propagation (EUCAP), Institute of Electrical and Electronics Engineers (IEEE), 2017-06-07) [Conference Paper]

In this paper, a frequency reconfigurable multiple-input-multiple-output (MIMO) slot antenna is presented. The proposed design is low profile and compact with wide tunability range, covering several well-known frequency bands from 1800 MHz to 2450 MHz. The frequency reconfigurability is achieved by loading the annular slot with varactor diodes. The antenna system is also analyzed for MIMO performance metrics. Moreover, the effect of circular slot antenna on the chassis modes is also investigated using the theory of characteristic modes (TCM). The physical principle behind frequency reconfigurability is also investigated using TCM analysis. An interesting finding is observed using varactor diodes for frequency reconfigurability, that is the reactive impedance loading does not alter the modal significance (MS) plots but only aid in the input impedance matching at different frequency bands.

Subgraph detection using graph signals

Chepuri, Sundeep Prabhakar; Leus, Geert (2016 50th Asilomar Conference on Signals, Systems and Computers, Institute of Electrical and Electronics Engineers (IEEE), 2017-03-06) [Conference Paper]

In this paper we develop statistical detection theory for graph signals. In particular, given two graphs, namely, a background graph that represents an usual activity and an alternative graph that represents some unusual activity, we are interested in answering the following question: To which of the two graphs does the observed graph signal fit the best? To begin with, we assume both the graphs are known, and derive an optimal Neyman-Pearson detector. Next, we derive a suboptimal detector for the case when the alternative graph is not known. The developed theory is illustrated with numerical experiments.

Rate-cost tradeoffs in control

Kostina, Victoria; Hassibi, Babak (2016 54th Annual Allerton Conference on Communication, Control, and Computing (Allerton), Institute of Electrical and Electronics Engineers (IEEE), 2017-02-13) [Conference Paper]

Consider a distributed control problem with a communication channel connecting the observer of a linear stochastic system to the controller. The goal of the controller is minimize a quadratic cost function. The most basic special case of that cost function is the mean-square deviation of the system state from the desired state. We study the fundamental tradeoff between the communication rate r bits/sec and the limsup of the expected cost b, and show a lower bound on the rate necessary to attain b. The bound applies as long as the system noise has a probability density function. If target cost b is not too large, that bound can be closely approached by a simple lattice quantization scheme that only quantizes the innovation, that is, the difference between the controller's belief about the current state and the true state.

Improved bounds on the epidemic threshold of exact SIS models on complex networks

Ruhi, Navid Azizan; Thrampoulidis, Christos; Hassibi, Babak (2016 IEEE 55th Conference on Decision and Control (CDC), Institute of Electrical and Electronics Engineers (IEEE), 2017-01-05) [Conference Paper]

The SIS (susceptible-infected-susceptible) epidemic model on an arbitrary network, without making approximations, is a 2n-state Markov chain with a unique absorbing state (the all-healthy state). This makes analysis of the SIS model and, in particular, determining the threshold of epidemic spread quite challenging. It has been shown that the exact marginal probabilities of infection can be upper bounded by an n-dimensional linear time-invariant system, a consequence of which is that the Markov chain is “fast-mixing” when the LTI system is stable, i.e. when equation (where β is the infection rate per link, δ is the recovery rate, and λmax(A) is the largest eigenvalue of the network's adjacency matrix). This well-known threshold has been recently shown not to be tight in several cases, such as in a star network. In this paper, we provide tighter upper bounds on the exact marginal probabilities of infection, by also taking pairwise infection probabilities into account. Based on this improved bound, we derive tighter eigenvalue conditions that guarantee fast mixing (i.e., logarithmic mixing time) of the chain. We demonstrate the improvement of the threshold condition by comparing the new bound with the known one on various networks with various epidemic parameters.

Multi-rate control over AWGN channels via analog joint source-channel coding

Khina, Anatoly; Pettersson, Gustav M.; Kostina, Victoria; Hassibi, Babak (2016 IEEE 55th Conference on Decision and Control (CDC), Institute of Electrical and Electronics Engineers (IEEE), 2017-01-05) [Conference Paper]

We consider the problem of controlling an unstable plant over an additive white Gaussian noise (AWGN) channel with a transmit power constraint, where the signaling rate of communication is larger than the sampling rate (for generating observations and applying control inputs) of the underlying plant. Such a situation is quite common since sampling is done at a rate that captures the dynamics of the plant and which is often much lower than the rate that can be communicated. This setting offers the opportunity of improving the system performance by employing multiple channel uses to convey a single message (output plant observation or control input). Common ways of doing so are through either repeating the message, or by quantizing it to a number of bits and then transmitting a channel coded version of the bits whose length is commensurate with the number of channel uses per sampled message. We argue that such “separated source and channel coding” can be suboptimal and propose to perform joint source-channel coding. Since the block length is short we obviate the need to go to the digital domain altogether and instead consider analog joint source-channel coding. For the case where the communication signaling rate is twice the sampling rate, we employ the Archimedean bi-spiral-based Shannon-Kotel'nikov analog maps to show significant improvement in stability margins and linear-quadratic Gaussian (LQG) costs over simple schemes that employ repetition.

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