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: "increasing the throughput of an unlicensed wireless network through retransmissions"
  Abstract: This paper analyzes the throughput of an unlicensed wireless network where messages decoded in outage may be retransmitted. We assume that some wireless devices such as sensors are the unlicensed users, which communicate in the licensed uplink channel. In this case, the licensed users that interfere with the unlicensed transmissions devices are mobile devices whose spatial distribution are assumed to follow a Poisson point process with respect to a reference unlicensed link. We investigate how the number of allowed retransmissions and the spectrum efficiency jointly affect the throughput in [bits/s/Hz] of a reference unlicensed link for different licensed network densities, constrained by a given required error rate. The optimal throughput is derived for this case as a function of the network density. We also prove that the optimal constrained throughput can always reach the unconstrained optimal value. Our numerical results corroborate those of the analytical findings, also illustrating how the number of allowed retransmissions that leads to the optimal throughput changes with the error rate requirements.

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"
    - "energy efficiency of an unlicensed wireless network in the presence of 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"

Connected through hyperedge HE-2 (induced by source paper "energy internet via packetized management enabling technologies and deployment challenges"):
  with members:
    - "event based electricity metering an autonomous method to determine transmission thresholds"
    - "finite blocklength communications in smart grids for dynamic spectrum access and locally licensed scenarios"
    - "sparse signal processing for grant free massive connectivity a future paradigm for random access protocols in the internet of things"
    - "why smart appliances may result in a stupid energy grid"
    - "narrowband iot data transmission procedures for massive machine type communications"
    - "multi layer analysis of iot based systems"
    - "aggregation and resource scheduling in machine type communication networks a stochastic geometry approach"
    - "self regulating supply demand systems"

Connected through hyperedge HE-3 (induced by source paper "energy efficiency of an unlicensed wireless network in the presence of retransmissions"):
  with members:
    - "maximizing the link throughput between smart meters and aggregators as secondary users under power and outage constraints"
    - "on the joint impact of beamwidth and orientation error on throughput in directional wireless poisson networks"
    - "throughput analysis of cognitive wireless networks with poisson distributed nodes based on location information"
    - "green cellular networks a survey some research issues and challenges"
    - "an overview of the transmission capacity of wireless 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)