Continuous and Responsive D2D Victim Localization for Post-Disaster Emergencies

One of the most challenging tasks in a disaster scenario is the detection and localization of victims with high accuracy and minimum delay, especially in out-of-coverage areas. In the event of a disaster that disrupts the cellular network infrastructure, emergency calls can be relayed to the core network via multi-hop D2D communications. In this paper, a localization system is proposed that uses radio measurements obtained through such D2D multi-hop assisted emergency calls to localize in-coverage and out-of-coverage devices. To address the uncertainty and gradual reception of data in real-time in this scenario, a dynamic constraint satisfaction-based Multi Victim Localization Algorithm
(MVLA)
is proposed. This algorithm locates multi-hop devices in a progressive propagation manner to provide fast and accurate updates on victim locations. Additionally, three modes of
${MVLA}$
, namely
${MVLA}_{recent}$
,
${MVLA}_{seq}$
, and
${MVLA}_{all}$
are proposed. Simulation results demonstrate that
${MVLA}_{all}$
has a lower localization error compared to
${MVLA}_{recent}$
and
${MVLA}_{seq}$
. Moreover,
${MVLA}_{all}$
, is compared with an existing particle filtering-based localization algorithm called RSSI Monte-Carlo Boxed Localization (
RSSI-MCL
) under an increasing number of emergency user devices and functional gNodeBs. Results show that
${MVLA}_{all}$
significantly outperforms the
RSSI-MCL
method in terms of localization accuracy and computational delay.