LA-ANA Based Data Transmission in UWB Tx-Rx

Energy efficiency is the major concern in designing Ultra-Wideband (UWB) based WSN
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. In designing the heterogeneous WSN
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in a dynamic environment data transmission would be difficult due to the presence of larger density nodes. This problem can be resolved using an autonomic based learning in a MAC Layer of UWB TxRx. In this paper, the process of Local Automate based Autonomic Network Architecture (LA-ANA) is deployed at the MAC Layer of the WSN
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. The method learns repeatedly from the previous occurrences and avoids the congestion. The simulation results show an increase in throughput and decrease in energy consumption.