Dynamic Spectrum Access of Virtualized-Operated Networks over MIMO-OFDMA Dedicated to 5G Cognitive WSSNs
The wireless smart sensors networks (WSSNs) is expected to play significant role in Internet of Things (IoT) and wireless based application service delivery such as: in healthcare, in environment monitoring, in intelligent agriculture, … . Therefore, cognitive radio is promising in handling spectrum efficiently, however the Cognitive Radio approach for WSSNs is not efficient in utilizing spectrum because they also suffer from interference which induced collision. In this paper, we present a dynamic spectrum access for WSSNs based on the channel availability of likelihood distribution using continuous-time Markov chain considering primary transmitting users, temporal channel usage, channel pattern and spatial distribution. On the other hand, as the 5G promising technique, Multiple Inputs-Multiple Outputs Orthogonal Frequency Division Multiple Access (MIMO-OFDMA) based Cognitive Radio schemes are proposed to significantly improve the system capacity while mitigate the interference for dynamic spectrum access networks. The energy efficient spectrum sensing employing a dedicated smart sensors and virtualized-operated networks for spectrum sensing is given focus in this paper. The experiment outcome shows that the proposed approach improves overall spectrum efficiency of Cognitive Radio wireless smart sensors networks. On the subject of the power-allocation policies for the MIMO-OFDMA based Cognitive Radio network, a set of simulations show that our proposed scheme outperforms the other existing schemes in terms of effective capacity to efficiently implement the heterogeneous statistical QoS over MIMO-OFDMA based Cognitive Radio network. The improvement virtualized-operated network life time and energy efficiency is shown through simulations.
KeywordsDynamic spectrum access Virtualized operated networks MIMO-OFDMA 5G cognitive WSSNs Intelligent agriculture Automated irrigation system
This work has been accomplished at WIMCS-Research Team, ENET’COM, Sfax-University, Tunisia.
Part of this work has been supported by APIA-Tunisia Agriculture Ministry & MESRSTIC Scientific Research Group-Tunisia.
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