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RAM: resource allocation in MIMO–MISO cognitive IoT for 5G wireless networks using two-level weighted majority cooperative game

Abstract

Cognitive Internet of things (CIoT) is the solution for resource allocation problem in an exponentially increasing number of Internet of things in fifth generation wireless networks. Two-tier massive multiple-input-multiple-output (MIMO) and multiple-input-single-output small cell-based CIoT using weighted majority cooperative game (WMCG) is deployed in RAM. We have proposed a two-level WMCG theoretic model and two utility functions, to detect the channel is free or not and for allocating the spectrum to a high majority CIoT device by the spectrum manager based on their applied maximum weight or price values. In RAM, we have calculated power consumption, signal-to-interference-plus-noise ratio (SINR), spectral efficiency, and energy efficiency of the proposed network. We have simulated the RAM using QualNet 7.1 simulator. The power consumption of the RAM has been shown to decrease by approximately 15–30%, and SINR has been shown to increase by approximately 6–7% as compared to the existing approaches.

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Acknowledgements

The authors are grateful to the Department of Science & Technology (DST), Govt. of India, for sanctioning a research INSPIRE Fellowship under INSPIRE Program with DST Ref. No.: DST/INSPIRE Fellowship/2018/IF180846 under which this contribution has been completed. The authors are also grateful to the Department of Science & Technology (DST), Govt. of India, for sanctioning a research Project Ref. No.: SR/FST/ETI-296/2011.

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Correspondence to Subha Ghosh.

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Ghosh, S., De, D. RAM: resource allocation in MIMO–MISO cognitive IoT for 5G wireless networks using two-level weighted majority cooperative game. J Supercomput (2022). https://doi.org/10.1007/s11227-022-04546-9

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  • DOI: https://doi.org/10.1007/s11227-022-04546-9

Keywords

  • CIoT
  • Massive MIMO
  • MISO small cell
  • Power consumption
  • SINR
  • WMCG