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: "joint power control and rate allocation enabling ultra reliability and energy efficiency in simo wireless networks"
  Abstract: Coming cellular systems are envisioned to open up to new services with stringent reliability and energy efficiency requirements. In this paper, we focus on the joint power control and rate allocation problem in single-input multiple-output (SIMO) wireless systems with Rayleigh fading and stringent reliability constraints. We propose an allocation scheme that maximizes the energy efficiency of the system while making use only of average statistics of the signal and interference, and the number of antennas    $M$    that are available at the receiver side. We show the superiority of the maximum ratio combining (MRC) scheme over selection combining (SC) in terms of energy efficiency, and prove that the gap between the optimum allocated resources converges to    $(M!)^{1/(2M)}$    as the reliability constraint becomes more stringent. Meanwhile, in most cases, MRC was also shown to be more energy efficient than the switch and stay combining (SSC) scheme, although this does not hold only when operating with extremely large    $M$   , extremely high/small average signal/interference power and/or highly power consuming receiving circuitry. Numerical results show the feasibility of the ultra-reliable operation when    $M$    increases, while greater the fixed power consumption and/or drain efficiency of the transmit amplifier is, the greater the optimum transmit power and rate.

Connected through hyperedge HE-1 (induced by source paper "enabling urllc for low cost iot devices via diversity combining schemes"):
  with members:
    - "ultra reliable and low latency communications in 5g downlink physical layer aspects"
    - "a statistical learning approach to ultra reliable low latency communication"
    - "wide area wireless communication challenges for the internet of things"

Connected through hyperedge HE-2 (induced by source paper "distributed rate control in downlink noma networks with reliability constraints"):
  with members:
    - "hybrid resource scheduling for aggregation in massive machine type communication networks"
    - "rate control under finite blocklength for downlink cellular networks with reliability constraints"
    - "energy efficient resource allocation in noma heterogeneous networks"
    - "signal processing for mimo noma present and future challenges"
    - "non orthogonal multiple access for cooperative communications challenges opportunities and trends"
    - "power domain non orthogonal multiple access noma in 5g systems potentials and challenges"
    - "non orthogonal multiple access in large scale heterogeneous networks"
    - "aggregation and resource scheduling in machine type communication networks a stochastic geometry approach"

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.NI(Networking and Internet Architecture)