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The routing of packets are generally performed based on the destinationaddress and forward link channel available from the instantaneous Routerwithout sufficient cognizance of either the performance of the forward Routeror forward channel characteristics. The lack of awareness of forward channelproperty can lead to packet loss or delayed delivery leading tomultipleretransmissions or routing to an underperforming pathway. This paperdescribes an application of Cognitive Network to improve the networkperformance by implementing a Hidden Markov Model (HMM) algorithm for learningand predicting the performance of surrounding routers continuously while arouting demand is initiated. The cognition segment/domain of every router cangain knowledge about the quality of forward network. The information of thecurrent network conditions is shared between routers by the Forward ChannelPerformance Index FCPI. This enables complete cognition of surroundings andefficient delivery of messages in various paradigms of performance

Cognitive Routing with Stretched Network Awareness through Hidden Markov Model Learning at Router Level