Scalable Optimization of Ultra-Dense Heterogeneous Networks Using Stochastic Geometry and Deep Learning Techniques

Ultra-dense networks (UDNs) enable next-generation wireless systems by providing high capacity through aggressive base-station densification. However, dense deployments increase interference and energy consumption, making Quality-of-Service (QoS) aware performance evaluation and optimization challen...

Deskribapen osoa

Xehetasun bibliografikoak

Egile Nagusiak:	Amna Shabbir, Muhammad Hashir Bin Khalid, Hashim Raza Khan, Kamran Arshad, Khaled Assaleh
Formatua:	Artigo
Hizkuntza:	Inglês
Argitaratua:	MDPI AG 2026-02-01
Saila:	AI
Gaiak:	ultra-dense networks stochastic geometry machine learning deep learning coverage probability energy efficiency
Sarrera elektronikoa:	https://www.mdpi.com/2673-2688/7/2/76
Etiketak:	Etiketa erantsi Etiketarik gabe, Izan zaitez lehena erregistro honi etiketa jartzen!