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Institution

Qualcomm

CompanyFarnborough, United Kingdom
About: Qualcomm is a company organization based out in Farnborough, United Kingdom. It is known for research contribution in the topics: Wireless & Signal. The organization has 19408 authors who have published 38405 publications receiving 804693 citations. The organization is also known as: Qualcomm Incorporated & Qualcomm, Inc..


Papers
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Patent
Juan Montojo1, Luo Tao1, Wanshi Chen1
30 Sep 2010
TL;DR: In this article, a shared initialization code for physical channel data scrambling in an LTE Advanced coordinated multipoint transmission network is provided for the sole purpose of complying with the Abstract requirement rules that allow a reader to quickly ascertain the disclosed subject matter.
Abstract: Methods, systems, apparatus and computer program products are provided for generating a shared initialization code for physical channel data scrambling in an LTE Advanced coordinated multipoint transmission network. This Abstract is provided for the sole purpose of complying with the Abstract requirement rules that allow a reader to quickly ascertain the disclosed subject matter. Therefore, it is to be understood that it should not be used to interpret or limit the scope or the meaning of the claims.

125 citations

Journal ArticleDOI
S. Vembu1, Sergio Verdu
TL;DR: The fixed-length results of this paper provide an operational characterization of the inf-entropy rate of a source and characterize the liminf of the entropy rate, thereby establishing a pleasing duality with the fundamental limits of source coding.
Abstract: Suppose we are given a random source and want to use it as a random number generator; at what rate can we generate fair bits from it? We address this question in an information-theoretic setting by allowing for some arbitrarily small but nonzero deviation from "ideal" random bits. We prove our results with three different measures of approximation between the ideal and the obtained probability distributions: the variational distance, the d-bar distance, and the normalized divergence. Two different contexts are studied: fixed-length and variable-length random number generation. The fixed-length results of this paper provide an operational characterization of the inf-entropy rate of a source, defined in Han and Verdu (see ibid., vol.39, no.3, p.752-772, 1993) and the variable-length results characterize the liminf of the entropy rate, thereby establishing a pleasing duality with the fundamental limits of source coding. A feature of our results is that we do not restrict ourselves to ergodic or to stationary sources. >

125 citations

Proceedings ArticleDOI
TL;DR: A deep generative model for lossy video compression is presented that outperforms the state-of-the-art learned video compression networks based on motion compensation or interpolation and opens up novel video compression applications, which have not been feasible with classical codecs.
Abstract: In this paper we present a a deep generative model for lossy video compression. We employ a model that consists of a 3D autoencoder with a discrete latent space and an autoregressive prior used for entropy coding. Both autoencoder and prior are trained jointly to minimize a rate-distortion loss, which is closely related to the ELBO used in variational autoencoders. Despite its simplicity, we find that our method outperforms the state-of-the-art learned video compression networks based on motion compensation or interpolation. We systematically evaluate various design choices, such as the use of frame-based or spatio-temporal autoencoders, and the type of autoregressive prior. In addition, we present three extensions of the basic method that demonstrate the benefits over classical approaches to compression. First, we introduce semantic compression, where the model is trained to allocate more bits to objects of interest. Second, we study adaptive compression, where the model is adapted to a domain with limited variability, e.g., videos taken from an autonomous car, to achieve superior compression on that domain. Finally, we introduce multimodal compression, where we demonstrate the effectiveness of our model in joint compression of multiple modalities captured by non-standard imaging sensors, such as quad cameras. We believe that this opens up novel video compression applications, which have not been feasible with classical codecs.

125 citations

Journal ArticleDOI
Roberto Avanzi1
TL;DR: It is argued that QARMA provides sufficient security margins within the constraints determined by the mentioned applications, while still achieving best-in-class latency, and a technique to extend the length of the tweak by using, for instance, a universal hash function, which can also be used to strengthen the security of QARma.
Abstract: This paper introduces QARMA, a new family of lightweight tweakable block ciphers targeted at applications such as memory encryption, the generation of very short tags for hardware-assisted prevention of software exploitation, and the construction of keyed hash functions. QARMA is inspired by reflection ciphers such as PRINCE, to which it adds a tweaking input, and MANTIS. However, QARMA differs from previous reflector constructions in that it is a three-round Even-Mansour scheme instead of a FX-construction, and its middle permutation is non-involutory and keyed . We introduce and analyse a family of Almost MDS matrices defined over a ring with zero divisors that allows us to encode rotations in its operation while maintaining the minimal latency associated to {0, 1}-matrices. The purpose of all these design choices is to harden the cipher against various classes of attacks. We also describe new S-Box search heuristics aimed at minimising the critical path. QARMA exists in 64- and 128-bit block sizes, where block and tweak size are equal, and keys are twice as long as the blocks. We argue that QARMA provides sufficient security margins within the constraints determined by the mentioned applications, while still achieving best-in-class latency. Implementation results on a state-of-the art manufacturing process are reported. Finally, we propose a technique to extend the length of the tweak by using, for instance, a universal hash function, which can also be used to strengthen the security of QARMA.

125 citations

Patent
Jeffrey Brian Sampsell1, Russell Wayne Gruhlke1, Marek Mienko1, Gang Xu1, Ion Bita1 
07 Jun 2010
TL;DR: In this article, a front light guide panel including a plurality of embedded surface features is provided, which is configured to deliver uniform illumination from an artificial light source disposed at one side of the font light panel to an array of display elements located behind the light guide.
Abstract: A front light guide panel including a plurality of embedded surface features is provided. The front light panel is configured to deliver uniform illumination from an artificial light source disposed at one side of the font light panel to an array of display elements located behind the front light guide while allowing for the option of illumination from ambient lighting transmitted through the light guide panel. The surface embedded surface relief features create air pockets within the light guide panel. Light incident on the side surface of the light guide propagates though the light guide until it strikes an air/light material guide interface at one on the air pockets. The light is then turned by total internal reflection through a large angle such that it exits an output face disposed in front of the array of display elements.

125 citations


Authors

Showing all 19413 results

NameH-indexPapersCitations
Jian Yang1421818111166
Xiaodong Wang1351573117552
Jeffrey G. Andrews11056263334
Martin Vetterli10576157825
Vinod Menon10126960241
Michael I. Miller9259934915
David Tse9243867248
Kannan Ramchandran9159234845
Michael Luby8928234894
Max Welling8944164602
R. Srikant8443226439
Jiaya Jia8029433545
Hai Li7957033848
Simon Haykin7745462085
Christopher W. Bielawski7633432512
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20229
20211,188
20202,266
20192,224
20182,124
20171,477