Abstract
This paper proposes a robust reconstruction scheme for image/ video transmission in space-time trellis coding (STTC) based MIMO wireless multimedia sensor networks (WMSN). The information bits of the image/ video stream are modulated using STTC prior to transmission over the MIMO wireless channel between the multimedia sensors and the cluster head. At the receiver, a novel total variation sequence detector (TVSD) is developed that employs an anisotropic total variation (TV) regularized cost function to leverage the bounded variation property of the image/ video stream, in addition to the coding and diversity advantages of the STTC, for improved image/ video recovery. For reconstruction, a novel bi-layered hierarchical trellis based modified Viterbi decoder is developed to decode the optimal bit sequence corresponding to the least TV cost function using appropriately modified node and branch metrics. Simulation results using several test images and video sequences demonstrate the improved reconstruction performance of the proposed scheme, especially in the low SNR regime (0 - 10 dB), in comparison to the conventional maximum likelihood (ML) decoder, which makes it ideally suited for implementation in practical WMSN.
Highlights
Wireless multimedia sensor networks (WMSN) have gained popularity due to their applicability in a diverse spectrum of applications such as surveillance, law enforcement, industrial monitoring, health care, agriculture, UAVs, among others [1], [2]
A appealing aspect of these frames that makes them ideally suited for testing the performance of different algorithms is that they represent a wide variety of physical conditions, covering indoor as well as outdoor scenarios, with the objects of interest placed at different locations
An space-time trellis coding (STTC) coding based image/ video communication framework has been developed for WMSN
Summary
Wireless multimedia sensor networks (WMSN) have gained popularity due to their applicability in a diverse spectrum of applications such as surveillance, law enforcement, industrial monitoring, health care, agriculture, UAVs, among others [1], [2]. Previous works [43], [44] have described error resilient techniques for image/ video transmission in wireless networks that exploit their bounded variation property employing a novel Viterbi algorithm based TVSD technique for reconstruction. This is well suited for sensor networks since it does not increase the processing complexity at the sensors. A TV regularized cost function is proposed for improved reconstruction of the received frames Another contribution of this work is a novel hierarchical trellis structure, comprising of two layers, which is developed for optimal decoding of the received signal stream.
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