human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "power minimization based joint task scheduling and resource allocation in downlink c ran"):
  Abstract: In this paper, we consider the network power minimization problem in a downlink cloud radio access network (C-RAN), taking into account the power consumed at the baseband unit (BBU) for computation and the power consumed at the remote radio heads and fronthaul links for transmission. The power minimization problem for transmission is a fast time-scale issue whereas the power minimization problem for computation is a slow time-scale issue. Therefore, the joint network power minimization problem is a mixed time-scale problem. To tackle the time-scale challenge, we introduce large system analysis to turn the original fast time-scale problem into a slow time-scale one that only depends on the statistical channel information. In addition, we propose a bound improving branch-and-bound algorithm and a combinational algorithm to find the optimal and suboptimal solutions to the power minimization problem for computation, respectively, and propose an iterative coordinate descent algorithm to find the solutions to the power minimization problem for transmission. Finally, a distributed algorithm based on hierarchical decomposition is proposed to solve the joint network power minimization problem. In summary, this work provides a framework to investigate how execution efficiency and computing capability at BBU as well as delay constraint of tasks can affect the network power minimization problem in C-RANs.

Includes members:
  Member "joint energy minimization and resource allocation in c ran with mobile cloud":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "energy efficient resource allocation in uav enabled mobile edge computing networks")
  Member "joint precoding and rrh selection for user centric green mimo c ran":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "hybrid precoder design for cache enabled millimeter wave radio access networks")
  Member "energy efficiency of downlink transmission strategies for cloud radio access networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "sparse optimization for green edge ai inference")
  Member "joint multiuser downlink beamforming and admission control for green cloud rans with limited fronthaul based on mixed integer semi definite program":
    also connected through other hyperedges:
      (none)
  Member "decentralized computation offloading game for mobile cloud computing":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "context aware distribution of fog applications using deep reinforcement learning")
  Member "fronthaul constrained cloud radio access networks insights and challenges":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "on the capacity regions of cloud radio access networks with limited orthogonal fronthaul")
  Member "heterogeneous cloud radio access networks a new perspective for enhancing spectral and energy efficiencies":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "joint power allocation and load balancing optimization for energy efficient cell free massive mimo networks")
  Member "distributed pricing based user association for downlink heterogeneous cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "reinforcement learning based vehicle cell association algorithm for highly mobile millimeter wave communication")

Question: Please tell me which class the source paper belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.IT(Information Theory)