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 "dual timescale spectrum management in wireless heterogeneous networks"):
  Abstract: To attain the targeted data rates of next generation (5G) cellular networks requires dense deployment of small cells in addition to macro cells which provide wide coverage. Dynamic radio resource management (RRM) is crucial to the success of such heterogeneous networks due to much more pronounced traffic and interference variations in small cells. This work proposes a framework for spectrum management organized according to two timescales, which includes 1) centralized optimization on a second/minute timescale corresponding to typical durations of user sessions, and 2) distributed spectrum allocation on a millisecond timescale corresponding to typical latency requirements. The dual-timescale allocation is formulated as an optimization problem in the slower timescale with consideration of (distributed) opportunistic scheduling on the faster timescale. We consider both fixed and fully flexible user association. Iterative algorithms are developed to solve these optimization problems efficiently for a small cluster of cells. Simulation results demonstrate advantages of the dual-timescale RRM framework.

Includes members:
  Member "energy management in heterogeneous networks with cell activation user association and interference coordination":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a centralized metropolitan scale radio resource management scheme")
  Member "energy efficient cell activation user association and spectrum allocation in heterogeneous networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "reinforcement learning based vehicle cell association algorithm for highly mobile millimeter wave communication")
  Member "traffic driven spectrum allocation in heterogeneous networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "optimization of mimo device to device networks via matrix fractional programming a minorization maximization approach")
  Member "algorithms for enhanced inter cell interference coordination eicic in lte hetnets":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "analog subspace coding a new approach to coding for non coherent wireless networks")
  Member "distributed pricing based user association for downlink heterogeneous cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "reinforcement learning based vehicle cell association algorithm for highly mobile millimeter wave communication")
  Member "base station activation and linear transceiver design for optimal resource management in heterogeneous networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "power efficient resource allocation in c rans with sinr constraints and deadlines")
  Member "optimal joint user association and resource allocation in heterogeneous networks via sparsity pursuit":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "energy management in heterogeneous networks with cell activation user association and interference coordination")
  Member "user association for load balancing in heterogeneous cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "reinforcement learning based cooperative coded caching under dynamic popularities in ultra dense networks")

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)