EMF Exposure Mitigation via MAC Scheduling

International standards bodies define Electromagnetic field (EMF) emission requirements that can be translated into control of the base station actual Effective Isotropic Radiated Power (EIRP), i.e., averaged over a sliding time window. In this work we show how to comply with such requirements by designing a water-filling power allocation method operating at the MAC scheduler level. Our method ensures throughput fairness across users while constraining the EIRP to a value that is produced by an outer-loop procedure which is not the focus of our paper. The low computational complexity of our technique is appealing given the tight computational requirements of the MAC scheduler. Our proposal is evaluated against the prior art approaches through massive-MIMO system level simulations that include realistic modeling of physical and MAC level cellular procedures. We conclude that our proposal effectively mitigates EMF exposure with considerably less impact on network performance, making it a standout candidate for 5G and future 6G MAC scheduler implementations.

EMF Mitigation via 5G and 6G MAC Scheduling

High antenna directivity allows for high throughput transmission but also increases the exposure to electromagnetic field (EMF) of the end-users. Health regulations impose limitations on the incident power density, that generate a negative impact on network performance. In this work we focus at the slot-by-slot operations of a cellular Medium Access Control (MAC) scheduler to constrain the short-term EMF exposure upon real-time resource allocation, minimizing the impacts on network performance. We assume that the long-term EMF exposure is controlled by a proper outer-loop technique, that is not the object of this paper. Due to the minimal computational complexity allowed in MAC scheduling, existing solutions allowing practical implementation are few and focused at sub-optimal approaches curbing radio resource allocation. Our contribution is the derivation of a computationally efficient water-filling solution to allocate power and - then - resources, with a feasible integration of the necessary algorithms in the operations of a 5G MAC scheduler. We finally evaluate our proposal versus the prior art approaches with system level simulations with realistic modeling of physical and MAC level cellular procedures. We conclude that our proposal can control EMF with considerable less impact on network performance, making it a standout candidate for 5G and future 6G MAC scheduler implementations.