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Energy and Delay Guaranteed Joint Beam and User Scheduling Policy in 5G CoMP Networks

Title
Energy and Delay Guaranteed Joint Beam and User Scheduling Policy in 5G CoMP Networks
Author(s)
Kim, YeongjinJeong, JaehwanAhn, SuyoungKwak, JeonghoChong, Song
Issued Date
2022-04
Citation
IEEE Transactions on Wireless Communications, v.21, no.4, pp.2742 - 2756
Type
Article
Author Keywords
Beamforminguser schedulingmassive MIMOCoMP5G networksenergy-delay tradeoff
Keywords
RESOURCE-ALLOCATIONDYNAMIC RESOURCEMASSIVE-MIMOCLOUDMINIMIZATIONDOWNLINKCAPACITYSYSTEMS
ISSN
1536-1276
Abstract
Massive Multi-Input Multi-Output (MIMO) and Coordinated MultiPoint (CoMP) technologies in Cloud-RAN (C-RAN) architecture become inevitable trend due to the advent of next-generation mobile applications, which are traffic-intensive, such as ultra high definition (UHD) video. In this paper, we study a joint beam activation and user scheduling problem in a 5G cellular network with massive MIMO and CoMP utilizing orthogonal random beamforming technique. This paper aims to minimize total Remote Radio Heads' (RRHs') energy expenditure in a dynamic C-RAN architecture while ensuring finite service time for all user traffic arrivals in the communication coverage. We leverage Lyapunov drift-plus-penalty framework to transform an original long-term average problem into a series of per-slot modified problems. Since the provided per-slot problem is combinatorial and nonlinear optimization problem, we are inspired by a greedy algorithm to design energy and delay guaranteed joint beam activation and user scheduling policy, namely BEANS. We prove that the proposed BEANS ensures finite upper bounds of average RRH energy consumption and average queue backlogs for all traffic arrival rates within constant ratio of capacity region and all energy-delay tradeoff parameters. These proofs are the first attempt to theoretically demonstrate guarantees of energy and queue bounds in a framework consisting of possibly negative submodular objective function and non-matriod constraints. Finally, via extensive simulations, we compare the capacity region and energy-queue backlog tradeoff of BEANS with optimal and existing algorithms, and show that BEANS attains up to 65% of energy saving for the same average queue backlog compared to the algorithms which do not take traffic dynamics and energy consumption into considerations. © IEEE.
URI
http://hdl.handle.net/20.500.11750/15857
DOI
10.1109/TWC.2021.3115162
Publisher
Institute of Electrical and Electronics Engineers
Related Researcher
  • 곽정호 Kwak, Jeongho
  • Research Interests 클라우드 컴퓨팅; 엣지컴퓨팅; 네트워크 자원관리; 모바일 시스템
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Department of Electrical Engineering and Computer Science Intelligent Computing & Networking Laboratory 1. Journal Articles

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