The routing of packets are generally performed based on the destination
address and forward link channel available from the instantaneous Router
without sufficient cognizance of either the performance of the forward Router
or forward channel characteristics. The lack of awareness of forward channel
property can lead to packet loss or delayed delivery leading to
multipleretransmissions or routing to an underperforming pathway. This paper
describes an application of Cognitive Network to improve the network
performance by implementing a Hidden Markov Model (HMM) algorithm for learning
and predicting the performance of surrounding routers continuously while a
routing demand is initiated. The cognition segment/domain of every router can
gain knowledge about the quality of forward network. The information of the
current network conditions is shared between routers by the Forward Channel
Performance Index FCPI. This enables complete cognition of surroundings and
efficient delivery of messages in various paradigms of performance