Performance Analysis of Umbrella based Cognitive Environment Map in Uplink Cellular Networks

Abstract

Future devices are envisioned to be ‘Super Smart’ empowered by convergence of diverse advanced hardware and software technologies such as Cloud Computing, Cognitive Radio, Big Data, Machine Learning and Artificial Intelligence. These devices armed with cognitive intelligence will use perception capability to interact and learn from the environment and make the decisions instantly. It is challenging to accurately determine spatial spectrum opportunities available in uplink bands of cellular network due to varied primary user locations. This paper has laid a framework for spectrum opportunity detection wherein the future devices embedded with cognitive intelligence will have a potential to build a ‘Cognitive Environment Map (CEM)’. A CEM that can be viewed as a sort of internal neural representation of the geographical space in which the device operates to effectively detect spectrum opportunities. The performance improvement provided by the CEM, constructed using an efficient computational geometry technique named ‘Umbrella-based algorithm’ over traditional circular ranges is analyzed in an uplink cellular network. Results show that CEM are able to solve the hidden and exposed nodes problem considerably and performance of the opportunity detector is analyzed. Further, the impact of varying detection range, interference ranges of primary and secondary users as well as effect of propagation environment in terms of operational SNR and SINR is also discussed.