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: "on the statistical multiplexing gain of virtual base station pools"
  Abstract: Facing the explosion of mobile data traffic, cloud radio access network (C-RAN) is proposed recently to overcome the efficiency and flexibility problems with the traditional RAN architecture by centralizing baseband processing. However, there lacks a mathematical model to analyze the statistical multiplexing gain from the pooling of virtual base stations (VBSs) so that the expenditure on fronthaul networks can be justified. In this paper, we address this problem by capturing the session-level dynamics of VBS pools with a multi-dimensional Markov model. This model reflects the constraints imposed by both radio resources and computational resources. To evaluate the pooling gain, we derive a product-form solution for the stationary distribution and give a recursive method to calculate the blocking probabilities. For comparison, we also derive the limit of resource utilization ratio as the pool size approaches infinity. Numerical results show that VBS pools can obtain considerable pooling gain readily at medium size, but the convergence to large pool limit is slow because of the quickly diminishing marginal pooling gain. We also find that parameters such as traffic load and desired Quality of Service (QoS) have significant influence on the performance of VBS pools.

Connected through hyperedge HE-1 (induced by source paper "statistical multiplexing of computations in c ran with tradeoffs in latency and energy"):
  with members:
    - "assessment of lte wireless access for monitoring of energy distribution in the smart grid"
    - "on the effect of fronthaul latency on arq in c ran systems"

Connected through hyperedge HE-2 (induced by source paper "statistical multiplexing gain analysis of heterogeneous virtual base station pools in cloud radio access networks"):
  with members:
    - "software defined hyper cellular architecture for green and elastic wireless access"
    - "redesigning fronthaul for next generation networks beyond baseband samples and point to point links"
    - "cloud radio access network virtualizing wireless access for dense heterogeneous systems"
    - "concert a cloud based architecture for next generation cellular systems"

Connected through hyperedge HE-3 (induced by source paper "a cooperative scheduling scheme of local cloud and internet cloud for delay aware mobile cloud computing"):
  with members:
    - "concert a cloud based architecture for next generation cellular systems"

Connected through hyperedge HE-4 (induced by source paper "graph based framework for flexible baseband function splitting and placement in c ran"):
  with members:
    - "concert a cloud based architecture for next generation cellular systems"

Connected through hyperedge HE-5 (induced by source paper "concert a cloud based architecture for next generation cellular systems"):
  with members:
    - "software defined radio implementation of signaling splitting in hyper cellular network"

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)