On minimum number of wireless sensors required for reliable binary source estimation

The CEO problem of estimating a single binary data source using multiple observations is considered. A closed form equation for maximum achievable information capacity of the system is derived for different system parameters including number of sensors, observation accuracy and channel quality. A ne...

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Veröffentlicht in:2011 IEEE Wireless Communications and Networking Conference S. 1852 - 1857
Hauptverfasser: Razi, A, Yasami, K, Abedi, A
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 01.03.2011
Schlagworte:
Accuracy
CEO problem
Channel coding
clustering algorithms
convolutional codes
Decoding
Distributed coding
Sensor systems
Signal to noise ratio
wireless sensor networks
ISBN:1612842550, 9781612842554
ISSN:1525-3511
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Zusammenfassung:The CEO problem of estimating a single binary data source using multiple observations is considered. A closed form equation for maximum achievable information capacity of the system is derived for different system parameters including number of sensors, observation accuracy and channel quality. A new criterion for sensor clustering is provided based on the minimum number of sensors required to achieve arbitrarily low estimation error using different coding rates. A distributed joint source-channel coding (D-JSCC) scheme is proposed as an implementation example. The proposed coding scheme is based on the parallel concatenated convolutional codes (PCCC) that achieves high BER performance utilizing the number of sensors determined by the derived criterion.
ISBN:1612842550
9781612842554
ISSN:1525-3511
DOI:10.1109/WCNC.2011.5779415