Resource Allocation for Ultra-Dense Networks: A Survey, Some Research Issues and Challenges
Driven by the explosive data traffic and new quality of service (QoS) requirement of mobile users, the communication industry has been experiencing a new evolution by means of network infrastructure densification. With the increase of the density as well as the variety of access points (APs), the network benefits from proximal transmissions and increased spatial reuse of system resources, thus introducing a new paradigm named ultra-dense networks (UDNs). Since the limited available resources are shared by ubiquitous APs in UDNs, the demand for efficient resource allocation schemes becomes even more compelling. However, the large scale of UDNs impedes the exploration of effective resource allocation approaches particularly on the computational complexity and significance overhead or feedback. In this paper, we provide a survey-style introduction to resource allocation approaches in UDNs. Specifically, we first present some common scenarios of UDNs with the relevant special issues. Second, we provide a taxonomy to classify the resource allocation methods in the existing literatures. Then, to alleviate the main difficulties of UDNs, some prevailing and feasible solutions are elaborated. Next, we present some emerging technologies thriving UDNs with special RA features discussed. Additionally, the challenges and open research directions are outlined in this field.
|Keywords||caching, Computer architecture, Device-to-device communication, mean field game., Microprocessors, mobile edge computing, Quality of service, resource allocation, Resource management, stochastic geometry, stochastic optimization, Ultra-dense network, Wireless communication|
|Journal||IEEE Communications Surveys and Tutorials|
Teng, Y. (Yinglei), Liu, M. (Mengting), Yu, F.R, Leung, V.C.M. (Victor C. M.), Song, M. (Mei), & Zhang, Y. (Yong). (2018). Resource Allocation for Ultra-Dense Networks: A Survey, Some Research Issues and Challenges. IEEE Communications Surveys and Tutorials. doi:10.1109/COMST.2018.2867268