2024/02/06 by Maryam Salamatmoghadasi, Salamatmoghadasi, Maryam, Metin Öztürk +3 · 1 citation
Engineering · #Advanced MIMO Systems Optimization #Advanced Wireless Communication Technologies #FOS: Computer and information sciences #FOS: Electrical engineering #IoT Networks and Protocols #Networking and Internet Architecture (cs.NI) #Systems and Control (eess.SY) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2402.04386
openalex publication_date 2024/02/06 · openalex created_date 2024/02/09 · openalex updated_date 2026/08/01
In the evolving landscape of vertical heterogeneous networks, the practice of cell switching particularly for small base stations faces a significant challenge due to the lack of accurate data on the traffic load of sleeping SBSs. This information gap is crucial as it hinders the feasibility and applicability of existing power consumption optimization methods; however, the studies in the literature predominantly assume perfect knowledge about the traffic load of sleeping SBSs. Addressing this critical issue, our study introduces innovative methodologies for estimating the traffic load of sleeping SBSs in a vHetNet including the integration of a high altitude platform as a super macro base station into the terrestrial network. We propose three distinct spatial interpolation-based estimation schemes: clustering-based, distance based, and random neighboring selection. Employing a real data set for empirical validations, we compare the estimation performance of the developed traffic load estimation schemes and assess the impact of estimation errors. Our findings demonstrate that accurate estimation of sleeping SBSs' traffic loads is essential for making network power consumption optimization methods both feasible and applicable in vHetNets.