Towards an information theory of large networks: an achievable rate region
IEEE Transactions on Information Theory
A network information theory for wireless communication: scaling laws and optimal operation
IEEE Transactions on Information Theory
Cooperative diversity in wireless networks: Efficient protocols and outage behavior
IEEE Transactions on Information Theory
Sensing capacity for discrete sensor network applications
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
The worst-case capacity of wireless sensor networks
Proceedings of the 6th international conference on Information processing in sensor networks
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Motivated by limited computational resources in sensor nodes, the impact of complexity constraints on the communication efficiency of sensor networks is studied. A single-parameter characterization of processing limitation of nodes in sensor networks is invoked. Specifically, the relaying nodes are assumed to "donate" only a small part of their total processor time to relay other nodes information. The amount of donated processor time is modelled by the node's ability to decode a channel code reliably at given rate R. Focusingon a four node network, with two relays, prior work for a complexity constrained single relay network is built upon. In the proposed coding scheme, the transmitter sends a broadcast code such that the relays decode only the "coarse" information, and assist the receiver in removing ambiguity only in that information. Via numerical examples,the impact of different power constraints in the system, ranging from per node power bound to network wide power constraint is explored. As the complexity bound R increases, the proposed scheme becomes identical to the recently proposed achievable rate by Gupta & Kumar. Both discrete memoryless and Gaussian channels are considered.