human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "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.

Connected through hyperedge HE-1 (induced by source paper "resource allocation in green dense cellular networks complexity and algorithms"):
  with members:
    - "large scale spectrum allocation for cellular networks via sparse optimization"
    - "optimal user scheduling in energy harvesting wireless networks"
    - "boost base station on off switching strategy for energy efficient massive mimo hetnets"
    - "online ski rental for on off scheduling of energy harvesting base stations"
    - "online energy efficient packet scheduling for a common deadline with and without energy harvesting"
    - "gate greening at the edges"
    - "energy efficient cell activation user association and spectrum allocation in heterogeneous networks"
    - "optimizing user association and spectrum allocation in hetnets a utility perspective"

Connected through hyperedge HE-2 (induced by source paper "large scale spectrum allocation for cellular networks via sparse optimization"):
  with members:
    - "energy management in heterogeneous networks with cell activation user association and interference coordination"
    - "energy efficient cell activation user association and spectrum allocation in heterogeneous networks"
    - "licensed and unlicensed spectrum allocation in heterogeneous networks"
    - "distributed pricing based user association for downlink heterogeneous cellular networks"
    - "base station activation and linear transceiver design for optimal resource management in heterogeneous networks"
    - "distributed linear precoder optimization and base station selection for an uplink heterogeneous network"
    - "user association for load balancing in heterogeneous cellular networks"

Connected through hyperedge HE-3 (induced by source paper "scalable spectrum allocation for large networks based on sparse optimization"):
  with members:
    - "energy management in heterogeneous networks with cell activation user association and interference coordination"
    - "energy efficient cell activation user association and spectrum allocation in heterogeneous networks"
    - "traffic driven spectrum allocation in heterogeneous networks"
    - "joint user association and reuse pattern selection in heterogeneous networks"
    - "distributed linear precoder optimization and base station selection for an uplink heterogeneous network"

Connected through hyperedge HE-4 (induced by source paper "device to device load balancing for cellular networks"):
  with members:
    - "licensed and unlicensed spectrum allocation in heterogeneous networks"
    - "traffic driven spectrum allocation in heterogeneous networks"
    - "an overview of load balancing in hetnets old myths and open problems"
    - "user association for load balancing in heterogeneous cellular networks"
    - "economics of wifi offloading trading delay for cellular capacity"

Connected through hyperedge HE-5 (induced by source paper "dual timescale spectrum management in small cell wireless networks"):
  with members:
    - "energy management in heterogeneous networks with cell activation user association and interference coordination"
    - "traffic driven spectrum allocation in heterogeneous networks"
    - "algorithms for enhanced inter cell interference coordination eicic in lte hetnets"
    - "distributed pricing based user association for downlink heterogeneous cellular networks"
    - "base station activation and linear transceiver design for optimal resource management in heterogeneous networks"
    - "user association for load balancing in heterogeneous cellular networks"

Connected through hyperedge HE-6 (induced by source paper "licensed and unlicensed spectrum allocation in heterogeneous networks"):
  with members:
    - "hybrid spectrum sharing in mmwave cellular networks"
    - "the impact of unlicensed access on small cell resource allocation"
    - "energy management in heterogeneous networks with cell activation user association and interference coordination"
    - "dual timescale spectrum management in wireless heterogeneous networks"
    - "cell free massive mimo versus small cells"
    - "energy efficient cell activation user association and spectrum allocation in heterogeneous networks"
    - "small cell traffic balancing over licensed and unlicensed bands"
    - "allocation of licensed and unlicensed spectrum in heterogeneous networks"

Question: Please tell me which class the center node 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)