Non-binary joint network-channel decoding of correlated sensor data in wireless sensor networks

Guha, Arindra; Psota, Eric T.; Pérez, Lance C.

doi:10.1109/wcnc.2011.5779264

Cited by 4 publications

(3 citation statements)

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“…Data aggregation can reduce data traffic significantly by removing data redundancy [ 27 ]. Since different sensor nodes partially monitor the same spatial region, sensing information is generally correlated [ 28 ]. To saving power, data should already be processed as it flows from the information source to the sink [ 29 ], which will decrease the accuracy of information around the monitoring area due to some relative packets being removed [ 30 ].…”

Section: Introductionmentioning

confidence: 99%

Maximum Data Collection Rate Routing Protocol Based on Topology Control for Rechargeable Wireless Sensor Networks

Lin

Dan

Gao

et al. 2016

Sensors

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In Rechargeable Wireless Sensor Networks (R-WSNs), in order to achieve the maximum data collection rate it is critical that sensors operate in very low duty cycles because of the sporadic availability of energy. A sensor has to stay in a dormant state in most of the time in order to recharge the battery and use the energy prudently. In addition, a sensor cannot always conserve energy if a network is able to harvest excessive energy from the environment due to its limited storage capacity. Therefore, energy exploitation and energy saving have to be traded off depending on distinct application scenarios. Since higher data collection rate or maximum data collection rate is the ultimate objective for sensor deployment, surplus energy of a node can be utilized for strengthening packet delivery efficiency and improving the data generating rate in R-WSNs. In this work, we propose an algorithm based on data aggregation to compute an upper data generation rate by maximizing it as an optimization problem for a network, which is formulated as a linear programming problem. Subsequently, a dual problem by introducing Lagrange multipliers is constructed, and subgradient algorithms are used to solve it in a distributed manner. At the same time, a topology controlling scheme is adopted for improving the network’s performance. Through extensive simulation and experiments, we demonstrate that our algorithm is efficient at maximizing the data collection rate in rechargeable wireless sensor networks.

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Section: Introductionmentioning

confidence: 99%

Maximum Data Collection Rate Routing Protocol Based on Topology Control for Rechargeable Wireless Sensor Networks

Lin

Dan

Gao

et al. 2016

Sensors

View full text Add to dashboard Cite

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“…SUMMARY OF CONTRIBUTIONS We explored the error mechanisms of iterative decoding of low-density parity-check (LDPC) codes. This work has resulted in nine peer-reviewed conference papers [1], [2], [3], [4], [5], [6], [7], [8], [9], three journal papers [10], [11], [12], and two pending journal papers [13], [14] in the fields of channel coding and information theory. The study of iterative decoders and their behavior is one of the most important problems in the area of channel coding, as their unpredictable behavior has impeded the deployment of LDPC codes in many real-world applications.…”

mentioning

confidence: 99%

“…Wireless sensors often require a high level of power-efficiency, and can benefit from network communications strategies that use both channel coding and network coding. We recently created a decoder that integrates non-binary LDPC codes, random linear network coding, and a new correlation decoder that operates on systems where the sensors have correlated data [9]. Preliminary results show that significant improvements can be achieved using this new decoder.…”

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confidence: 99%