Cognitive channel adaptation in wireless sensor networks

Cognitive radio adaptation is employed in WSNs to reduce effects of RF interference. Communication channel quality is assessed locally at each node. Using beacons to propagate channel quality and node related information among the nodes of the network, channel adaptation decision is made either centrally by identifying a channel that is optimum for a majority of nodes through a tree-structure dissemination (Majority Voting Scheme) or in a distributed manner by identifying a channel where maximum interference for any node is less than maximum interference on the other channels (Veto Voting Scheme). If two channels have the same level of maximal interference, the channel with a lesser number is chosen. Channel quality assessment may be optimized based on expected interference type and/or statistical methods.