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 "energy management in heterogeneous networks with cell activation user association and interference coordination"):
  Abstract: The densification and expansion of wireless network pose new challenges on interference management and reducing energy consumption. This paper studies energy-efficient resource management in heterogeneous networks by jointly optimizing cell activation, user association and multicell multiuser channel assignment, according to the long-term average traffic and channel conditions. The proposed framework is built on characterizing the interference coupling by pre-defined interference patterns, and performing resource allocation among these patterns. In this way, the interference fluctuation caused by (de)activating cells is explicitly taken into account when calculating the user achievable rates. A tailored algorithm is developed to solve the formulated problem in the dual domain by exploiting the problem structure, which gives a significant complexity saving. Numerical results show a huge improvement in energy saving achieved by the proposed scheme. The user association derived from the proposed joint resource optimization is mapped to standard-compliant cell selection biasing. This mapping reveals that the cell-specific biasing for energy saving is quite different from that for load balancing investigated in the literature.

Includes members:
  Member "network topology adaptation and interference coordination for energy saving in heterogeneous networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "optimized sensor collaboration for estimation of temporally correlated parameters")
  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 "base station activation and linear transceiver design for optimal resource management in heterogeneous networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (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-5 (induced by source paper "dual timescale spectrum management in wireless heterogeneous networks")
  Member "joint user association and reuse pattern selection in heterogeneous networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "scalable spectrum allocation for large networks based on sparse optimization")
  Member "group sparse beamforming for green cloud ran":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "sparse optimization for green edge ai inference")
  Member "base station selection for energy efficient network operation with the majorization minimization algorithm":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "a note on decoding order in optimizing multi cell noma")

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)