Density-aware cellular coverage control: Interference-based density estimation

Density-aware mobile networks: Opportunities and challenges

“…Ease of integration, no other auxiliary function, or monitoring traffic of network Sensitive to channel characteristics that may not be uniform in a field [58,70,71,72] ing more BSs. Therefore, the optimal density of BSs ( ) is vital for enhancing energy efficiency in networks [45,46].…”

“…Edge computing can be a valuable technology towards this aim by providing a higherlevel perspective and having more processing power with respect to BSs; it can collect and evaluate the required data for density measurements from BSs (such as received signal strength (RSS), channel quality indicator (CQI), SINR, etc.) and provide more accurate results [58,59].…”

“…Neighborhood-based estimators, which are not scalable and suffer from inaccurate results, infer density from a census on packet traffic [5,65,66,67,68,69]. Power-based estimators combine the merits of location-and neighborhood-based estimators [70,58,71,72], although RSS is not a robust distance estimator. While some of these approaches are designed for ad hoc networks, they can generally be employed in any wireless network with minor modifications.…”

“…MEC entities have a broader perspective over network topology in comparison to BSs facilitating decentralized optimizations. For instance, in [58,59], authors by adapting the transmit power of BSs to the network density, managed to enhance the network capacity and increase the throughput while coverage holes are prevented . Future networks guarantee the ubiquitous connectivity in case of a dis-aster, which causes a dysfunction of the network infrastructure [88].…”

“…As shown in Figure 6, the processing power of BSs can be enhanced by equipping the network with MECs. For instance, in this scenario the density of BSs can also be obtained by a density estimator model (as also explained in Section 2.5) deployed in MEC [58]. The simulation parameters are presented in Table 4.…”