In the last decade, a sharp surge in the number of user proximity wireless devices (UPWDs) has been observed. This has increased the level of electromagnetic field (EMF) exposure of the users substantially and hence, the possible physiological effects. Ambient backscatter communications (ABC) has appeared to be a promising solution to reduce the power consumption of UPWDs by converting ambient radio frequency (RF) signals into useful signals while non-orthogonal multiple access (NOMA) is a compelling multiplexing scheme for enhanced spectral efficiency. This paper utilises a novel combination of ABC and NOMA to reduce the EMF in the uplink of wireless communication systems. This contemporary approach of EMF-aware resource optimization is based on k-medoids and Silhouette analysis. To curtail the uplink EMF, a power allocation strategy is also derived by converting a non-convex problem to a convex one and solving accordingly. The numerical results exhibit that the proposed ABC, NOMA, and unsupervised learning based scheme achieves a reduction in the EMF by at least 75% in comparison to the existing solutions.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Emission-aware Resource Optimization Framework for Backscatter-enabled Uplink NOMA Networks




    Publication date :

    2022-06-01


    Size :

    1502266 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Energy-Efficient Resource Allocation for 6G Backscatter-Enabled NOMA IoV Networks

    Khan, Wali Ullah / Javed, Muhammad Awais / Nguyen, Tu N. et al. | IEEE | 2022


    Performance Analysis of Ambient Backscatter Uplink NOMA Networks

    Chrysologou, Athanasios P. / Chatzidiamantis, Nestor D. / Boulogeorgos, Alexandros-Apostolos A. et al. | IEEE | 2023




    Uplink Performance Analysis of Grant-Free NOMA Networks

    Zhengy, Canjian / Zhengy, Fu-Chun / Luoy, Jingjing et al. | IEEE | 2022