• ETRI Journal
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• v.42 no.3
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• pp.341-350
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• 2020

In a wireless sensor network (WSN), the data transmission technique based on the cooperative multiple-input multiple-output (CMIMO) scheme reduces the energy consumption of sensor nodes quite effectively by utilizing the space-time block coding scheme. However, in networks with high node density, the scheme is ineffective due to the high degree of correlated data. Therefore, to enhance the energy efficiency in high node density WSNs, we implemented the distributed source coding (DSC) with the virtual multiple-input multiple-output (MIMO) data transmission technique in the WSNs. The DSC-MIMO first compresses redundant source data using the DSC and then sends it to a virtual MIMO link. The results reveal that, in the DSC-MIMO scheme, energy consumption is lower than that in the CMIMO technique; it is also lower in the DSC single-input single-output (SISO) scheme, compared to that in the SISO technique at various code rates, compression rates, and training overhead factors. The results also indicate that the energy consumption per bit is directly proportional to the velocity and training overhead factor in all the energy saving schemes.

• Journal of Broadcast Engineering
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• v.17 no.1
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• pp.122-128
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• 2012

Because of the system delay caused by the number of feedback retransmission in Distributed Video Coding (DVC) scheme, it is difficult to realize practical DVC in many cases. In this paper low feedback retransmission Distributed Source Coding (DSC) scheme is proposed for practical DVC scheme based on Low-Density Parity-Check (LDPC) codes because DVC system is an specific application of DSC system. This DSC scheme is achieved by using different LDPC codes optimized in each different compression rate and using source revealing scheme. Optimized LDPC codes provide us much better decoding performance which causes the 57% reduced number of iteration. Consequently, the number of feedback retransmission is decreased by 50%.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.4C
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• pp.329-336
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• 2010

Distributed source coding (DSC) system moves computational burden from encoder to decoder, so it takes higher decoding complexity. This paper explores the problem of reducing the decoding complexity of practical Slepian-Wolf coding using low-density parity check accumulate (LDPCA) codes. It is shown that the convergence of mean magnitude (CMM) stopping criteria for LDPC codes help reduce the 85% of decoding complexity under the 2% of compression rate loss, and marginal initial rate request reduces complexity below complexity minimum bound. Moreover, inter-rate stopping criterion, modified for rate-adaptable characteristic, is proposed for LDPCA codes, and it makes decoder perform less iterative decoding than normal stopping criterion does when channel characteristic is unknown.

• The Journal of the Korea Contents Association
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• v.9 no.11
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• pp.10-17
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• 2009

Wyner-Ziv video coding is a new video compression paradigm based on distributed source coding theory of Slepian-Wolf and Wyner-Ziv. Wyner-Ziv coding enables light-encoder/heavy-decoder structure by shifting complex modules including motion estimation/compensation task to the decoder. Instead of performing the complicated motion estimation process in the encoder, the Wyner-Ziv decoder performs the motion estimation for the generation of side information in order to make the predicted signal of the Wyner-Ziv frame. The efficiency of side information generation deeply affects the overall coding performance, since the bit-rates of the Wyner-Ziv coding is directly dependent on side information. In this paper, an improved side information generation method using field coding is proposed. In the proposed method, top fields are coded with the existing SI generation method and bottom fields are coded with new SI generation method using the information of the top fields. Simulation results show that the proposed method improves the quality of the side information and rate-distortion performance compared to the conventional method.

• Journal of information and communication convergence engineering
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• v.12 no.4
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• pp.215-220
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• 2014

We consider quantization optimized for distributed estimation, where a set of sensors at different sites collect measurements on the parameter of interest, quantize them, and transmit the quantized data to a fusion node, which then estimates the parameter. Here, we propose an iterative quantizer design algorithm with a weighted distance rule that allows us to reduce a system-wide metric such as the estimation error by constructing quantization partitions with their optimal weights. We show that the search for the weights, the most expensive computational step in the algorithm, can be conducted in a sequential manner without deviating from convergence, leading to a significant reduction in design complexity. Our experments demonstrate that the proposed algorithm achieves improved performance over traditional quantizer designs. The benefit of the proposed technique is further illustrated by the experiments providing similar estimation performance with much lower complexity as compared to the recently published novel algorithms.

• Journal of IKEEE
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• v.22 no.3
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• pp.558-564
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• 2018

In distributed estimation where each node can collect only partial information on the parameter of interest without communication between nodes and quantize it before transmission to a fusion node which conducts estimation of the parameter, we consider a novel quantization technique employed at local nodes. It should be noted that the performance can be greatly improved if each node can transmit its measurement to one designated node (namely, head node) which can quantize its estimate using the total rate available in the system. For this case, the best strategy at the head node would be simply to partition the parameter space using the generalized Lloyd algorithm, producing the global codewords, one of which is closest to the estimate is transmitted to a fusion node. In this paper, we propose an iterative design algorithm that seeks to efficiently assign the codewords into each of quantization partitions at nodes so as to achieve the performance close to that of the system with the head node. We show through extensive experiments that the proposed algorithm offers a performance improvement in rate-distortion perspective as compared with previous novel techniques.