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 "scalable spectrum allocation and user association in networks with many small cells"):
  Abstract: A scalable framework is developed to allocate radio resources across a large number of densely deployed small cells with given traffic statistics on a slow timescale. Joint user association and spectrum allocation is first formulated as a convex optimization problem by dividing the spectrum among all possible transmission patterns of active access points (APs). To improve scalability with the number of APs, the problem is reformulated using local patterns of interfering APs. To maintain global consistency among local patterns, inter-cluster interaction is characterized as hyper-edges in a hyper-graph with nodes corresponding to neighborhoods of APs. A scalable solution is obtained by iteratively solving a convex optimization problem for bandwidth allocation with reduced complexity and constructing a global spectrum allocation using hyper-graph coloring. Numerical results demonstrate the proposed solution for a network with 100 APs and several hundred user equipments. For a given quality of service (QoS), the proposed scheme can increase the network capacity several fold compared to assigning each user to the strongest AP with full-spectrum reuse.

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 "distributed pricing based user association for downlink heterogeneous cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (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-5 (induced by source paper "power efficient resource allocation in c rans with sinr constraints and deadlines")
  Member "on association cells in random heterogeneous networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "millimeter wave integrated access and backhaul in 5g performance analysis and design insights")
  Member "distributed linear precoder optimization and base station selection for an uplink heterogeneous network":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "load balancing user association in millimeter wave mimo networks")
  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)