2 research outputs found
On the Optimal Beamwidth of UAV-Assisted Networks Operating at Millimeter Waves
The millimeter-wave (mm-wave) bands enable very large antenna arrays that can
generate narrow beams for beamforming and spatial multiplexing. However,
directionality introduces beam misalignment and leads to reduced energy
efficiency. Thus, employing the narrowest possible beam in a cell may not
necessarily imply maximum coverage. The objective of this work is to determine
the optimal sector beamwidth for a cellular architecture served by an unmanned
aerial vehicle (UAV) acting as a base station (BS). The users in a cell are
assumed to be distributed according to a Poisson Point Process (PPP) with a
given user density. We consider hybrid beamforming at the UAV, such that
multiple concurrent beams serve all the sectors simultaneously. An optimization
problem is formulated to maximize the sum rate over a given area while limiting
the total power available to each sector. We observe that, for a given transmit
power, the optimal sector beamwidth increases as the user density in a cell
decreases, and varies based on the height of the UAV. Thus, we provide
guidelines towards the optimal beamforming configurations for users in rural
areas.Comment: 7 pages, 7 figure
Minimizing Energy Consumption for 5G NR Beam Management for RedCap Devices
In 5G New Radio (NR), beam management entails periodic and continuous
transmission and reception of control signals in the form of synchronization
signal blocks (SSBs), used to perform initial access and/or channel estimation.
However, this procedure demands continuous energy consumption, which is
particularly challenging to handle for low-cost, low-complexity, and
battery-constrained devices, such as RedCap devices to support mid-market
Internet of Things (IoT) use cases. In this context, this work aims at reducing
the energy consumption during beam management for RedCap devices, while
ensuring that the desired Quality of Service (QoS) requirements are met. To do
so, we formalize an optimization problem in an Indoor Factory (InF) scenario to
select the best beam management parameters, including the beam update
periodicity and the beamwidth, to minimize energy consumption based on users'
distribution and their speed. The analysis yields the regions of feasibility,
i.e., the upper limit(s) on the beam management parameters for RedCap devices,
that we use to provide design guidelines accordingly