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: "traffic driven spectrum allocation in heterogeneous networks"
  Abstract: Next generation cellular networks will be heterogeneous with dense deployment of small cells in order to deliver high data rate per unit area. Traffic variations are more pronounced in a small cell, which in turn lead to more dynamic interference to other cells. It is crucial to adapt radio resource management to traffic conditions in such a heterogeneous network (HetNet). This paper studies the optimization of spectrum allocation in HetNets on a relatively slow timescale based on average traffic and channel conditions (typically over seconds or minutes). Specifically, in a cluster with $n$ base transceiver stations (BTSs), the optimal partition of the spectrum into $2^n$ segments is determined, corresponding to all possible spectrum reuse patterns in the downlink. Each BTS's traffic is modeled using a queue with Poisson arrivals, the service rate of which is a linear function of the combined bandwidth of all assigned spectrum segments. With the system average packet sojourn time as the objective, a convex optimization problem is first formulated, where it is shown that the optimal allocation divides the spectrum into at most $n$ segments. A second, refined model is then proposed to address queue interactions due to interference, where the corresponding optimal allocation problem admits an efficient suboptimal solution. Both allocation schemes attain the entire throughput region of a given network. Simulation results show the two schemes perform similarly in the heavy-traffic regime, in which case they significantly outperform both the orthogonal allocation and the full-frequency-reuse allocation. The refined allocation shows the best performance under all traffic conditions.

Connected through hyperedge HE-1 (induced by source paper "optimization of mimo device to device networks via matrix fractional programming a minorization maximization approach"):
  with members:
    - "a centralized metropolitan scale radio resource management scheme"
    - "fractional programming for communication systems part i power control and beamforming"
    - "fractional programming for communication systems part ii uplink scheduling via matching"
    - "optimality of treating interference as noise a combinatorial perspective"
    - "fast resource scheduling in hetnets with d2d support"
    - "distributed algorithms for spectrum allocation power control routing and congestion control in wireless networks"

Connected through hyperedge HE-2 (induced by source paper "delay optimal biased user association in heterogeneous networks"):
  with members:
    - "random cell association and void probability in poisson distributed cellular networks"
    - "optimizing user association and spectrum allocation in hetnets a utility perspective"
    - "optimal base station deployment for small cell networks with energy efficient power control"
    - "an overview of load balancing in hetnets old myths and open problems"
    - "what will 5g be"
    - "joint resource partitioning and offloading in heterogeneous cellular networks"
    - "offloading in heterogeneous networks modeling analysis and design insights"
    - "load aware modeling and analysis of heterogeneous cellular networks"

Connected through hyperedge HE-3 (induced by source paper "scalable spectrum allocation and user association in networks with many small cells"):
  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"
    - "distributed pricing based user association for downlink heterogeneous cellular networks"
    - "base station activation and linear transceiver design for optimal resource management in heterogeneous networks"
    - "on association cells in random 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-4 (induced by source paper "scalable spectrum allocation for large networks based on sparse optimization"):
  with members:
    - "scalable spectrum allocation and user association in networks with many small cells"
    - "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"
    - "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-5 (induced by source paper "device to device load balancing for cellular networks"):
  with members:
    - "scalable spectrum allocation and user association in networks with many small cells"
    - "licensed and unlicensed 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-6 (induced by source paper "energy management in heterogeneous networks with cell activation user association and interference coordination"):
  with members:
    - "network topology adaptation and interference coordination for energy saving in heterogeneous networks"
    - "energy efficient cell activation user association and spectrum allocation in heterogeneous networks"
    - "base station activation and linear transceiver design for optimal resource management in heterogeneous networks"
    - "optimal joint user association and resource allocation in heterogeneous networks via sparsity pursuit"
    - "joint user association and reuse pattern selection in heterogeneous networks"
    - "group sparse beamforming for green cloud ran"
    - "base station selection for energy efficient network operation with the majorization minimization algorithm"
    - "user association for load balancing in heterogeneous cellular networks"

Connected through hyperedge HE-7 (induced by source paper "dual timescale spectrum management in wireless heterogeneous networks"):
  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"
    - "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"
    - "optimal joint user association and resource allocation in heterogeneous networks via sparsity pursuit"
    - "user association for load balancing in heterogeneous cellular networks"

Connected through hyperedge HE-8 (induced by source paper "dual timescale spectrum management in small cell wireless networks"):
  with members:
    - "scalable spectrum allocation and user association in networks with many small cells"
    - "energy management in heterogeneous networks with cell activation user association and interference coordination"
    - "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"

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)