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: "5g massive mimo architectures self backhauled small cells versus direct access"
  Abstract: In this paper, we focus on one of the key technologies for the fifth-generation wireless communication networks, massive multiple-input-multiple-output (mMIMO), by investigating two of its most relevant architectures: 1) to provide in-band wireless backhauling to a dense deployment of self-backhauled small cells (SCs) acting as communication relays to end-users, and 2) to provide direct wireless access (DA) to end-users. Through comprehensive 3GPP-based system-level simulations and analytical formulation, we show the end-to-end user rates achievable with these two architectures. Different from the existing work, we provide results for two strategies of self-backhauled SCs deployments, namely random and ad-hoc. Where in the latter SCs are purposely positioned close to UEs to achieve line-of-sight (LoS) access links. We also show the optimal backhaul and access time resource partition due to the in-band self-backhauling operations. For the mMIMO DA, we consider the implication of different pilot reuse schemes for the channel state information (CSI) acquisition, associated overhead and contamination effects. We find that the ad-hoc deployment of self-backhauled SCs closer to the users (UEs) with optimal resource partition and with directive antenna patterns, provides rate improvements for cell-edge UEs that amount to 30%, and a tenfold gain as compared to mMIMO DA architecture with pilot reuse 3 and reuse 1, respectively. On the other hand, mMIMO s-BH underperforms mMIMO DA above the median of the UE rates when the UEs are in the center of the cell, and the effect of pilot contamination is mitigated.

Connected through hyperedge HE-1 (induced by source paper "survey on uav cellular communications practical aspects standardization advancements regulation and security challenges"):
  with members:
    - "understanding uav cellular communications from existing networks to massive mimo"
    - "supporting uav cellular communications through massive mimo"
    - "uav aided offloading for cellular hotspot"
    - "the essential guide to realizing 5g connected uavs with massive mimo"
    - "performance analysis for practical unmanned aerial vehicle networks with los nlos transmissions"
    - "promises and caveats of uplink iot ultra dense networks"
    - "the sky is not the limit lte for unmanned aerial vehicles"
    - "cellular enabled uav communication a connectivity constrained trajectory optimization perspective"

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)