The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform
Brian D O Anderson - One of the best experts on this subject based on the ideXlab platform.
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understanding Error Propagation in multihop sensor network localization
IEEE Transactions on Industrial Electronics, 2013Co-Authors: Baoqi Huang, Brian D O AndersonAbstract:In multihop localization procedures where not every node at unknown positions (i.e., sensors) can directly measure distances to nodes at known positions (i.e., anchors), sensor localization Errors normally propagate (i.e., increase) as sensors progressively more distant from anchors are localized. To understand Error Propagation, we consider a primitive localization scenario: Nodes are deployed within a disk according to a homogeneous Poisson point process, the nodes around the disk center are anchors, the other nodes are sensors, and sensors are localized from the disk center to the outside in a hop-by-hop manner. Supposing noisy distance measurements between adjacent nodes, we analyze the quantitative relationship among sensor localization Errors, minimal hop counts from sensors to anchors, the sensor density, and the noise level of distance measurements. This relationship clearly reflects the properties of Error Propagation and is greatly helpful to the design and deployment of large-scale sensor networks. Finally, a simulation analysis based on actual localization procedures and the Cramer-Rao lower bound confirms our results.
Baoming Bai - One of the best experts on this subject based on the ideXlab platform.
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Error Propagation mitigation in sliding window decoding of braided convolutional codes
arXiv: Information Theory, 2020Co-Authors: Min Zhu, David G M Mitchell, Michael Lentmaier, Daniel J Costello, Baoming BaiAbstract:We investigate Error Propagation in sliding window decoding of braided convolutional codes (BCCs). Previous studies of BCCs have focused on iterative decoding thresholds, minimum distance properties, and their bit Error rate (BER) performance at small to moderate frame length. Here, we consider a sliding window decoder in the context of large frame length or one that continuously outputs blocks in a streaming fashion. In this case, decoder Error Propagation, due to the feedback inherent in BCCs, can be a serious this http URL order to mitigate the effects of Error Propagation, we propose several schemes: a \emph{window extension algorithm} where the decoder window size can be extended adaptively, a resynchronization mechanism where we reset the encoder to the initial state, and a retransmission strategy where erroneously decoded blocks are retransmitted. In addition, we introduce a soft BER stopping rule to reduce computational complexity, and the tradeoff between performance and complexity is examined. Simulation results show that, using the proposed window extension algorithm, resynchronization mechanism, and retransmission strategy, the BER performance of BCCs can be improved by up to four orders of magnitude in the signal-to-noise ratio operating range of interest, and in addition the soft BER stopping rule can be employed to reduce computational complexity.
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combating Error Propagation in window decoding of braided convolutional codes
International Symposium on Information Theory, 2018Co-Authors: Min Zhu, David G M Mitchell, Michael Lentmaier, Daniel J Costello, Baoming BaiAbstract:In this paper, we study sliding window decoding of braided convolutional codes (BCCs) in the context of a streaming application, where decoder Error Propagation can be a serious problem. A window extension algorithm and a resynchronization mechanism are introduced to mitigate the effect of Error Propagation. In addition, we introduce a soft bit-Error-rate stopping rule to reduce computational complexity, and the tradeoff between performance and complexity is examined. Simulation results show that, using the proposed window extension algorithm and resynchronization mechanism, the Error performance of BCCs can be improved by up to three orders of magnitude with reduced computational complexity.
Baoqi Huang - One of the best experts on this subject based on the ideXlab platform.
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understanding Error Propagation in multihop sensor network localization
IEEE Transactions on Industrial Electronics, 2013Co-Authors: Baoqi Huang, Brian D O AndersonAbstract:In multihop localization procedures where not every node at unknown positions (i.e., sensors) can directly measure distances to nodes at known positions (i.e., anchors), sensor localization Errors normally propagate (i.e., increase) as sensors progressively more distant from anchors are localized. To understand Error Propagation, we consider a primitive localization scenario: Nodes are deployed within a disk according to a homogeneous Poisson point process, the nodes around the disk center are anchors, the other nodes are sensors, and sensors are localized from the disk center to the outside in a hop-by-hop manner. Supposing noisy distance measurements between adjacent nodes, we analyze the quantitative relationship among sensor localization Errors, minimal hop counts from sensors to anchors, the sensor density, and the noise level of distance measurements. This relationship clearly reflects the properties of Error Propagation and is greatly helpful to the design and deployment of large-scale sensor networks. Finally, a simulation analysis based on actual localization procedures and the Cramer-Rao lower bound confirms our results.
Lian Zhao - One of the best experts on this subject based on the ideXlab platform.
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on the spatial Error Propagation characteristics of cooperative localization in wireless networks
IEEE Transactions on Vehicular Technology, 2017Co-Authors: Bingpeng Zhou, Qingchun Chen, Pei Xiao, Lian ZhaoAbstract:Cooperative localization is an important technique in wireless networks. However, there are always Errors in network node localization, which will spatially propagate among network nodes when performing network localization. In this paper, we study the spatial Error Propagation (EP) characteristics of network localization in terms of Fisher information. First, the spatial Propagation function is proposed to reveal the spatial cooperation principle of network localization. Second, the convergence property of spatial localization information Propagation (SLIP) is analyzed to shed light on the performance limits of network localization through spatial information Propagation. It is shown that 1) the network localization Error propagates in the way of Ohm's law in electric circuit theory, where the measurement accuracy, node location accuracy, and geometric-resolution information behave like the resistances connected in parallel or series; 2) the network location Error gradually diminishes with spatial localization cooperation procedures, due to the cooperative localization information Propagation; and 3) the essence of spatial localization cooperation among network nodes is the spatial Propagation of localization information.
Min Zhu - One of the best experts on this subject based on the ideXlab platform.
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Error Propagation mitigation in sliding window decoding of braided convolutional codes
arXiv: Information Theory, 2020Co-Authors: Min Zhu, David G M Mitchell, Michael Lentmaier, Daniel J Costello, Baoming BaiAbstract:We investigate Error Propagation in sliding window decoding of braided convolutional codes (BCCs). Previous studies of BCCs have focused on iterative decoding thresholds, minimum distance properties, and their bit Error rate (BER) performance at small to moderate frame length. Here, we consider a sliding window decoder in the context of large frame length or one that continuously outputs blocks in a streaming fashion. In this case, decoder Error Propagation, due to the feedback inherent in BCCs, can be a serious this http URL order to mitigate the effects of Error Propagation, we propose several schemes: a \emph{window extension algorithm} where the decoder window size can be extended adaptively, a resynchronization mechanism where we reset the encoder to the initial state, and a retransmission strategy where erroneously decoded blocks are retransmitted. In addition, we introduce a soft BER stopping rule to reduce computational complexity, and the tradeoff between performance and complexity is examined. Simulation results show that, using the proposed window extension algorithm, resynchronization mechanism, and retransmission strategy, the BER performance of BCCs can be improved by up to four orders of magnitude in the signal-to-noise ratio operating range of interest, and in addition the soft BER stopping rule can be employed to reduce computational complexity.
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combating Error Propagation in window decoding of braided convolutional codes
International Symposium on Information Theory, 2018Co-Authors: Min Zhu, David G M Mitchell, Michael Lentmaier, Daniel J Costello, Baoming BaiAbstract:In this paper, we study sliding window decoding of braided convolutional codes (BCCs) in the context of a streaming application, where decoder Error Propagation can be a serious problem. A window extension algorithm and a resynchronization mechanism are introduced to mitigate the effect of Error Propagation. In addition, we introduce a soft bit-Error-rate stopping rule to reduce computational complexity, and the tradeoff between performance and complexity is examined. Simulation results show that, using the proposed window extension algorithm and resynchronization mechanism, the Error performance of BCCs can be improved by up to three orders of magnitude with reduced computational complexity.
