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: "energy efficiency of an unlicensed wireless network in the presence of retransmissions"
  Abstract: This paper analysis the energy efficiency of an unlicensed wireless network in which retransmission is possible if the transmitted message is decoded in outage. A wireless sensor network is considered in which the sensor nodes are unlicensed users of a wireless network which transmit its data in the uplink channel used by the licensed users. Poisson point process is used to model the distributions of the nodes and the interference caused by the licensed users for the sensor nodes. After finding the optimal throughput in the presence of retransmissions, we focus on analyzing the total power consumption and energy efficiency of the network and how retransmissions, network density and outage threshold affects the energy efficiency of the network.

Connected through hyperedge HE-1 (induced by source paper "a throughput and energy efficiency scheme for unlicensed massive machine type communications"):
  with members:
    - "finite blocklength communications in smart grids for dynamic spectrum access and locally licensed scenarios"
    - "5g wireless network slicing for embb urllc and mmtc a communication theoretic view"
    - "increasing the throughput of an unlicensed wireless network through retransmissions"
    - "massive machine type communications in 5g physical and mac layer solutions"
    - "next generation m2m cellular networks challenges and practical considerations"
    - "a survey on internet of things from industrial market perspective"
    - "on the joint impact of beamwidth and orientation error on throughput in directional wireless poisson networks"
    - "green cellular networks a survey some research issues and challenges"

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)