8,256 research outputs found
Distributed video coding for wireless video sensor networks: a review of the state-of-the-art architectures
Distributed video coding (DVC) is a relatively new video coding architecture originated from two fundamental theorems namely, Slepian–Wolf and Wyner–Ziv. Recent research developments have made DVC attractive for applications in the emerging domain of wireless video sensor networks (WVSNs). This paper reviews the state-of-the-art DVC architectures with a focus on understanding their opportunities and gaps in addressing the operational requirements and application needs of WVSNs
Distortion-Tolerant Communications with Correlated Information
This dissertation is devoted to the development of distortion-tolerant communication techniques by exploiting the spatial and/or temporal correlation in a broad range of wireless communication systems under various system configurations. Signals observed in wireless communication systems are often correlated in the spatial and/or temporal domains, and the correlation can be used to facilitate system designs and to improve system performance. First, the optimum
node density, i.e., the optimum number of nodes in a unit area, is identified by utilizing the spatial data correlation in the one- and two-dimensional wireless sensor networks (WSNs), under the
constraint of fixed power per unit area. The WSNs distortion is quantized as the mean square error between the original and the reconstructed signals. Then we extend the analysis into WSNs with spatial-temporally correlated data. The optimum sampling in the space and time domains
is derived. The analytical optimum results can provide insights and guidelines on the design of practical WSNs. Second, distributed source coding schemes are developed by exploiting the data correlation in a wireless network with spatially distributed sources. A new symmetric distributed joint source-channel coding scheme (DJSCC) is proposed by utilizing the spatial source correlation. Then the DJSCC code is applied to spatial-temporally correlated sources. The temporal
correlated data is modeled as the Markov chain. Correspondingly, two decoding algorithms are proposed. The first multi-codeword message passing algorithm (MCMP) is designed for spatially correlated memoryless sources. In the second algorithm, a hidden Markov decoding process is added to the MCMP decoder to effectively exploit the data correlation in both the space and time domains. Third, we develop distortion-tolerant high mobility wireless communication systems by
considering correlated channel state information (CSI) in the time domain, and study the optimum designs with imperfect CSI. The pilot-assisted channel estimation mean square error is expressed
as a closed-form expression of various system parameters through asymptotic analysis. Based on the statistical properties of the channel estimation error, we quantify the impacts of imperfect CSI on system performance by developing the analytical symbol error rate and a spectral efficiency lower bound of the communication system
No-Sense: Sense with Dormant Sensors
Wireless sensor networks (WSNs) have enabled continuous monitoring of an area
of interest (body, room, region, etc.) while eliminating expensive wired
infrastructure. Typically in such applications, wireless sensor nodes report
the sensed values to a sink node, where the information is required for the
end-user. WSNs also provide the flexibility to the end-user for choosing
several parameters for the monitoring application. For example, placement of
sensors, frequency of sensing and transmission of those sensed data. Over the
years, the advancement in embedded technology has led to increased processing
power and memory capacity of these battery powered devices. However, batteries
can only supply limited energy, thus limiting the lifetime of the network. In
order to prolong the lifetime of the deployment, various efforts have been made
to improve the battery technologies and also reduce the energy consumption of
the sensor node at various layers in the networking stack. Of all the
operations in the network stack, wireless data transmission and reception have
found to consume most of the energy. Hence many proposals found in the
literature target reducing them through intelligent schemes like power control,
reducing retransmissions, etc. In this article we propose a new framework
called Virtual Sensing Framework (VSF), which aims to sufficiently satisfy
application requirements while conserving energy at the sensor nodes.Comment: Accepted for publication in IEEE Twentieth National Conference on
Communications (NCC-2014
- …