  One of the fundamental challenges in the design of distributed wireless
networks is the large dynamic range of network state. Since continuous tracking
of global network state at all nodes is practically impossible, nodes can only
acquire limited local views of the whole network to design their transmission
strategies. In this paper, we study multi-layer wireless networks and assume
that each node has only a limited knowledge, namely 1-local view, where each
S-D pair has enough information to perform optimally when other pairs do not
interfere, along with connectivity information for rest of the network. We
investigate the information-theoretic limits of communication with such limited
knowledge at the nodes. We develop a novel transmission strategy, namely Coded
Layer Scheduling, that solely relies on 1-local view at the nodes and
incorporates three different techniques: (1) per layer interference avoidance,
(2) repetition coding to allow overhearing of the interference, and (3) network
coding to allow interference neutralization. We show that our proposed scheme
can provide a significant throughput gain compared with the conventional
interference avoidance strategies. Furthermore, we show that our strategy
maximizes the achievable normalized sum-rate for some classes of networks,
hence, characterizing the normalized sum-capacity of those networks with
1-local view.
