Reliability vs. efficiency in distributed source coding for field-gathering sensor networks

The tradeoff between reliability and efficiency in distributed source coding for field-gathering sensor networks is examined. In the considered networks, sensors measure some underlying random field, quantize their measurements, encode the quantized values into bits and transmit these directly, or via relays, to a collector that reconstructs the field. The bits from one sensor's encoder are regarded as a packet. The minimum achievable coding rate can be attained if the sensors are ordered and each applies Slepian-Wolf distributed coding to its data assuming the decoder knows the data from all prior sensors. However, with such a coding scheme, losing even one sensor's packet would cause decoding failure for all subsequent sensors' values. Therefore, one might consider other ways of applying Slepian-Wolf coding, where in trade for increased coding rate, fewer sensor values are lost when a packet is lost. In this paper, the tradeoff between efficiency, i.e. coding rate, and reliability, characterized by a loss factor, is considered for several different Slepian-Wolf based coding schemes as a function of the packet error probability and the size of the network.