2,306 research outputs found
Real-time image streaming over a low-bandwidth wireless camera network
In this paper we describe the recent development of a low-bandwidth wireless camera sensor network. We propose a simple, yet effective, network architecture which allows multiple cameras to be connected to the network and synchronize their communication schedules. Image compression of greater than 90% is performed at each node running on a local DSP coprocessor, resulting in nodes using 1/8th the energy compared to streaming uncompressed images. We briefly introduce the Fleck wireless node and the DSP/camera sensor, and then outline the network architecture and compression algorithm. The system is able to stream color QVGA images over the network to a base station at up to 2 frames per second. ΓΒ© 2007 IEEE
A New Compressive Video Sensing Framework for Mobile Broadcast
A new video coding method based on compressive
sampling is proposed. In this method, a video is coded using
compressive measurements on video cubes. Video reconstruction
is performed by minimization of total variation (TV) of the pixelwise
discrete cosine transform coefficients along the temporal
direction. A new reconstruction algorithm is developed from
TVAL3, an efficient TV minimization algorithm based on the
alternating minimization and augmented Lagrangian methods.
Video coding with this method is inherently scalable, and has
applications in mobile broadcast
One Video Stream to Serve Diverse Receivers
The fundamental problem of wireless video multicast is to scalably serve multiple receivers which may have very different channel characteristics. Ideally, one would like to broadcast a single stream that allows each receiver to benefit from all correctly received bits to improve its video quality. We introduce Digital Rain, a new approach to wireless video multicast that adapts to channel characteristics without any need for receiver feedback or variable codec rates. Users that capture more packets or have fewer bit errors naturally see higher video quality. Digital Rain departs from current approaches in two ways: 1) It allows a receiver to exploit video packets that may contain bit errors; 2) It builds on the theory of compressed sensing to develop robust video encoding and decoding algorithms that degrade smoothly with bit errors and packet loss. Implementation results from an indoor wireless testbed show that Digital Rain significantly improves the received video quality and the number of supported receivers
Gossip Algorithms for Distributed Signal Processing
Gossip algorithms are attractive for in-network processing in sensor networks
because they do not require any specialized routing, there is no bottleneck or
single point of failure, and they are robust to unreliable wireless network
conditions. Recently, there has been a surge of activity in the computer
science, control, signal processing, and information theory communities,
developing faster and more robust gossip algorithms and deriving theoretical
performance guarantees. This article presents an overview of recent work in the
area. We describe convergence rate results, which are related to the number of
transmitted messages and thus the amount of energy consumed in the network for
gossiping. We discuss issues related to gossiping over wireless links,
including the effects of quantization and noise, and we illustrate the use of
gossip algorithms for canonical signal processing tasks including distributed
estimation, source localization, and compression.Comment: Submitted to Proceedings of the IEEE, 29 page
Multiband Spectrum Access: Great Promises for Future Cognitive Radio Networks
Cognitive radio has been widely considered as one of the prominent solutions
to tackle the spectrum scarcity. While the majority of existing research has
focused on single-band cognitive radio, multiband cognitive radio represents
great promises towards implementing efficient cognitive networks compared to
single-based networks. Multiband cognitive radio networks (MB-CRNs) are
expected to significantly enhance the network's throughput and provide better
channel maintenance by reducing handoff frequency. Nevertheless, the wideband
front-end and the multiband spectrum access impose a number of challenges yet
to overcome. This paper provides an in-depth analysis on the recent
advancements in multiband spectrum sensing techniques, their limitations, and
possible future directions to improve them. We study cooperative communications
for MB-CRNs to tackle a fundamental limit on diversity and sampling. We also
investigate several limits and tradeoffs of various design parameters for
MB-CRNs. In addition, we explore the key MB-CRNs performance metrics that
differ from the conventional metrics used for single-band based networks.Comment: 22 pages, 13 figures; published in the Proceedings of the IEEE
Journal, Special Issue on Future Radio Spectrum Access, March 201
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