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: "green heterogeneous cloud radio access networks potential techniques performance trade offs and challenges"
  Abstract: As a flexible and scalable architecture, heterogeneous cloud radio access networks (H-CRANs) inject strong vigor into the green evolution of current wireless networks. But the brutal truth is that EE improves at the cost of other indices such as SE, fairness, and delay. It is thus important to investigate performance trade-offs for striking flexible balances between energy-efficient transmission and excellent QoS guarantees under this new architecture. In this article, we first propose some potential techniques to energy-efficiently operate H-CRANs by exploiting their features. We then elaborate the initial ideas of modeling three fundamental trade-offs, namely EE-SE, EE-fairness, and EE-delay trade-offs, when applying these green techniques, and present open issues and challenges for future investigation. These related results are expected to shed light on green operation of H-CRANs from adaptive resource allocation, intelligent network control, and scalable network planning.

Connected through hyperedge HE-1 (induced by source paper "integer forcing architectures for uplink cloud radio access networks"):
  with members:
    - "achievability performance bounds for integer forcing source coding"
    - "on the optimal fronthaul compression and decoding strategies for uplink cloud radio access networks"
    - "outage behavior of integer forcing with random unitary pre processing"
    - "fronthaul compression and transmit beamforming optimization for multi antenna uplink c ran"
    - "system architecture and key technologies for 5g heterogeneous cloud radio access networks"
    - "cloud radio access network virtualizing wireless access for dense heterogeneous systems"
    - "optimized backhaul compression for uplink cloud radio access network"
    - "successive integer forcing and its sum rate optimality"

Connected through hyperedge HE-2 (induced by source paper "wireless traffic prediction with scalable gaussian process framework algorithms and verification"):
  with members:
    - "on asymptotic properties of hyperparameter estimators for kernel based regularization methods"
    - "caching in the sky proactive deployment of cache enabled unmanned aerial vehicles for optimized quality of experience"
    - "recent advances in cloud radio access networks system architectures key techniques and open issues"
    - "electricity demand forecasting by multi task learning"
    - "an approach for spatial temporal traffic modeling in mobile cellular networks"
    - "system architecture and key technologies for 5g heterogeneous cloud radio access networks"
    - "generalized product of experts for automatic and principled fusion of gaussian process predictions"

Connected through hyperedge HE-3 (induced by source paper "ultra dense hetnets meet big data green frameworks techniques and approaches"):
  with members:
    - "energy efficient user association and power allocation in millimeter wave based ultra dense networks with energy harvesting base stations"
    - "fog radio access networks mobility management interference mitigation and resource optimization"
    - "fronthauling for 5g lte u ultra dense cloud small cell 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)