Optimal Viterbi Based Total Variation Sequence Detection (TVSD) For Robust Image/Video Decoding In Wireless Sensor Networks

Kudeshia, Ankit; Jagannatham, Aditya K.

doi:10.1109/lsp.2014.2313887

Cited by 10 publications

(5 citation statements)

References 11 publications

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“…This is due to the edge preserving property [41] of the l 1 norm based anisotropic TV regularization term that can lead to a significant improvement in reconstruction quality [42]. 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. Furthermore, this is well suited for sensor networks since it does not increase the processing complexity at the sensors.…”

Section: A Review Of Work In Existing Literaturementioning

confidence: 99%

Hierarchical Trellis Based Decoder for Total Variation Sequence Detection (TVSD) in Space-Time Trellis Coded (STTC) Wireless Image/Video Communication

et al. 2020

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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. INDEX TERMS Image/video communication, MIMO, space-time trellis codes, total variation, Viterbi algorithm, wireless multimedia sensor networks.

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Section: A Review Of Work In Existing Literaturementioning

confidence: 99%

Hierarchical Trellis Based Decoder for Total Variation Sequence Detection (TVSD) in Space-Time Trellis Coded (STTC) Wireless Image/Video Communication

et al. 2020

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“…Thus, there is significant scope for the development of techniques that improve the accuracy of measurement detection at the receiver followed by accurate state estimation at the control center. To this end, total variation (TV) regularization has shown significantly improved performance for signal recovery in various practical applications pertaining to signal denoising [26], image/video deblurring [27], image/video recovery in wireless sensor networks [28], compressive sensing [29] etc. The proposed scheme therefore incorporates TV regularization for joint detection and dynamic state estimation (JDSE) in smart grids.…”

Section: A Wireless Communication For Smart Gridmentioning

confidence: 99%

“…In essence, the TV term ξ m n TV characterizes the temporal correlation of the state vector elements and it is mathematically defined as the integral of the absolute temporal gradient of the state vector sequence [59]. Hence, for a discrete vector sequence x n (m) it can be defined in terms of the l 1 norm of the difference between the current and the previous state vectors similar to [26]- [28], as shown below…”

Section: Tv-regularization Based Joint Detection and Dynamic Stamentioning

confidence: 99%

Total Variation Based Joint Detection and State Estimation for Wireless Communication in Smart Grids

2019

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A novel total variation (TV) framework is conceived for joint detection and dynamic state estimation (JDSE) for wireless transmission from the measurement devices to the control center in a smart grid. The proposed scheme employs a TV regularization based decoder in conjunction with a Kalman filter-based dynamic power system state estimator to minimize the detection error for transmission of the measurements over a fading wireless channel. A novel application of the Viterbi algorithm is proposed for TV detection of the received measurement vectors. Furthermore, the proposed JDSE scheme is also extended to a system in which each measurement is quantized to a single bit. This reduced-bandwidthbased TV-JDSE leads to a significant bandwidth efficiency improvement in the smart grid and to improved state estimation. Our simulation results provided for the standard IEEE−14 bus test system under different operating conditions demonstrate improved performance in comparison to conventional techniques and they are capable of approaching the ideal Clairvoyant Kalman filter benchmark.

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“…This method is low complex and gives 9‐dB better detection performance than traditional methods in various interferences, time delay, phase, or frequency offset conditions. A novel ML‐based VD for multimedia WSN applications is implemented in Kudeshia and Jagannatham . Exploiting bounded variation property and using a regularization factor, a modified branch metric calculations and total variation state is used in this VD.…”

Section: Introductionmentioning

confidence: 99%

“…A novel ML-based VD for multimedia WSN applications is implemented in Kudeshia and Jagannatham. 2 Exploiting bounded variation property and using a regularization factor, a modified branch metric calculations and total variation state is used in this VD. Viterbi decoder for UWB technology is designed with ML algorithm in Cholan.…”

Section: Introductionmentioning

confidence: 99%

Power efficient low latency architecture for decoder: Breaking the ACS bottleneck

Radha

Shylu

Nagabushanam

2019

Circuit Theory & Apps

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Summary Viterbi decoder (VD) is the majority used decoder for convolutional codes which play a role in WLAN and WSN applications. The trellis in VD needs proper analysis to calculate the metric at each stage to obtain a shortest path from every state to the next state. Existing techniques in VD design are namely (a) pipelined architecture, (b) modular ACS and buffers technique, and (c) quasi cyclic trellis technique. The key challenge of the VD trellis circuit is to attain high throughput and better latency performance with low power consumption without affecting hardware complexity of VD. This paper presents several of conventional methods used in VD. We also proposed a new method for VD with K the constraint length as multiple of M, the radix in trellis to calculate the shortest survival path to travel in trellis. The proposed VD is simulated using Xilinx. Use of a trace back approach in the proposed Viterbi decoder with capacitive and resistive feedback yields better throughput, latency, and power consumption with respect to other techniques. The static power outputs obtained in RE, shift update, and selective update methods using Libero IDE are also compared.

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Optimal Viterbi Based Total Variation Sequence Detection (TVSD) For Robust Image/Video Decoding In Wireless Sensor Networks

Cited by 10 publications

References 11 publications

Hierarchical Trellis Based Decoder for Total Variation Sequence Detection (TVSD) in Space-Time Trellis Coded (STTC) Wireless Image/Video Communication

Hierarchical Trellis Based Decoder for Total Variation Sequence Detection (TVSD) in Space-Time Trellis Coded (STTC) Wireless Image/Video Communication

Total Variation Based Joint Detection and State Estimation for Wireless Communication in Smart Grids

Power efficient low latency architecture for decoder: Breaking the ACS bottleneck

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