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: "towards massive machine type cellular communications"
  Abstract: Cellular networks have been engineered and optimized to carrying ever-increasing amounts of mobile data, but over the last few years, a new class of applications based on machine-centric communications has begun to emerge. Automated devices such as sensors, tracking devices, and meters - often referred to as machine-to-machine (M2M) or machine-type communications (MTC) - introduce an attractive revenue stream for mobile network operators, if a massive number of them can be efficiently supported. The novel technical challenges posed by MTC applications include increased overhead and control signaling as well as diverse application-specific constraints such as ultra-low complexity, extreme energy efficiency, critical timing, and continuous data intensive uploading. This paper explains the new requirements and challenges that large-scale MTC applications introduce, and provides a survey on key techniques for overcoming them. We focus on the potential of 4.5G and 5G networks to serve both the high data rate needs of conventional human-type communications (HTC) subscribers and the forecasted billions of new MTC devices. We also opine on attractive economic models that will enable this new class of cellular subscribers to grow to its full potential.

Connected through hyperedge HE-1 (induced by source paper "learning how to communicate in the internet of things finite resources and heterogeneity"):
  with members:
    - "efficient deployment of multiple unmanned aerial vehicles for optimal wireless coverage"
    - "learning with finite memory for machine type communication"
    - "unmanned aerial vehicle with underlaid device to device communications performance and tradeoffs"
    - "mobile internet of things can uavs provide an energy efficient mobile architecture"
    - "towards massive ultra reliable and low latency wireless communication with short packets"
    - "wireless communications in the era of big data"
    - "towards a consumer centric grid a behavioral perspective"
    - "what can wireless cellular technologies do about the upcoming smart metering traffic"

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)