Risk Area Alert Through Heterogeneous Mobile Networks: A New Approach to Fight COVID-19 and Beyond

COVID-19 has now been sweeping the whole world, and fundamentally affecting our daily life. An effective mechanism to further fight against COVID-19 and prevent the spread of this pandemic is to alert people when they are in the vicinity of areas with a high infection risk, yielding them to adjust their routes and consequently, leave these areas. Inspired by the fact that mobile communication networks are capable of precise positioning, data processing and information broadcasting, as well as are available for almost every person, in this paper, we propose a mobile network assisted Risk arEa ALerting scheme, named REAL, which exploits heterogeneous mobile networks to alert users who are in/near to the areas with high risks of COVID- 19 infection. Specifically, in REAL scheme, all base stations (BSs) periodically estimate their serving users' locations, which are then analyzed by macro BSs (MBSs) to identify risk areas. Next, each MBS transmits the information about risk areas to small BSs (SBSs), which in their turn adjust the beamforming direction to cover these areas and send alerts to users located therein. Simulation results validate the effectiveness of the proposed REAL scheme. In addition, some key challenges associated with implementing REAL are discussed at the end. IEEE

An Efficient Cost Performance Placement of Macro Sites and Small Cells Under Restricted Topology

The global COVID-19 pandemic leads people to intermittent quarantines and lockdowns. Many large and crowded gatherings were postponed or even cancelled to prevent social distance violation. The paper aims to tackle the placement problem of macro sites, microcells and picocells under a restricted network topology. The cell placement problem is defined based on linear programming. The algorithm named Cost Efficiency algorithm is proposed to construct a network with higher performance and lower cost. Simulation results showed that the proposed algorithm yields higher SINR value and more number of served users over construction cost compared with other planning algorithms. The result of this work is expected to help users have better network service quality when they are isolated in hospital or self-health monitoring at home. © 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.