4.7 Article

Graph-Based Joint User-Centric Overlapped Clustering and Resource Allocation in Ultradense Networks

Journal

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
Volume 67, Issue 5, Pages 4440-4453

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TVT.2017.2787802

Keywords

UDN; user-centric; overlapped clustering; resource allocation; graph theory

Funding

  1. National Natural Science Foundation of China [61372101, 61671144]
  2. 863 Program of China [2015AA01A703]
  3. China Scholarship Council
  4. Engineering and Physical Sciences Research Council projects of U.K. [EP/N004558/1, EP/N023862/1]
  5. European Research Council under the Advanced Fellow Grant Beam-Me-Up
  6. Royal Society
  7. EPSRC [EP/N004558/1, EP/N023862/1] Funding Source: UKRI
  8. Engineering and Physical Sciences Research Council [EP/N004558/1, EP/N023862/1] Funding Source: researchfish

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With the increase of access point (AP) density and the exponential growth of mobile devices supported by ultradense networks (UDNs), user-centric overlapped clustering relying on AP cooperation is becoming a promising design principle for guaranteeing the quality of service (QoS) required by each user equipment. This ambitious goal can be achieved by the joint design of user-centric overlapped clustering and resource allocation. In this context, both the traffic-load balancing and the limited availability of orthogonal resource blocks (RBs) have to be carefully considered in UDNs. To tackle these challenges, we formulate a joint user-centric overlapped clustering and resource allocation problem with the goal of maximizing the system's spectral efficiency. To efficiently solve this problem, it is decoupled into two subproblems, which can be solved independently with the aid of our graph-theoretical framework. We first develop a novel distributed three-stage user-centric clustering solution, which is aware of the APs' traffic-loads. Then, based on the overlapped clusters constructed, we propose a novel two-stage graph-based user-centric resource allocation scheme for mitigating the resultant inter-cluster interference, despite the limited availability of orthogonal RBs. Our numerical results confirm the benefits of the proposed framework and show that it outperforms the benchmark solutions in terms of both its per area aggregated user rate and user rate.

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