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David Puig Oses

Researcher at Qualcomm

Publications -  24
Citations -  791

David Puig Oses is an academic researcher from Qualcomm. The author has contributed to research in topics: Channel (broadcasting) & Throughput. The author has an hindex of 14, co-authored 24 publications receiving 791 citations.

Papers
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Patent

Extended acknowledgement and rate control channel

TL;DR: In this article, the authors address the need in the art for an extended acknowledgment/rate control channel and propose a constellation of points, each point corresponding to a pair consisting of a rate control command and an acknowledgment command.
Patent

Predistortion technique for high power amplifiers

TL;DR: In this article, an adaptive predistortion technique for high power amplifiers includes an adaptive algorithm that operates independently of data samples to write a set of complex gain values to a lookup table and multiply them by a complex digital baseband waveform.
Patent

Channel quality feedback mechanism and method

TL;DR: In this article, the feedback of channel information to a serving base station is improved to reduce the reverse link load while allowing the base station to improve the forward link data throughput over a channel quality indicator channel, three subchannels are generated; the re-synch subchannel, the differential feedback subchannel and the transition indicator subchannel.
Patent

Combining grant, acknowledgement, and rate control commands

TL;DR: In this paper, the authors address the need in the art for reduced overhead control with the ability to adjust transmission rates as necessary, with the benefit of providing the flexibility of grant based control while utilizing lower overhead when rate control commands are used.
Patent

combined engine system and method for voice recognition

TL;DR: In this article, a method and system that combines voice recognition engines and resolves any differences between the results of individual voice recognition engine is presented, where a speaker independent (SI) Hidden Markov Model (HMM) engine and a speaker dependent Dynamic Time Warping (DTW-SD) engine are combined.