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: "effective capacity in wireless networks a comprehensive survey"
  Abstract: Low latency applications, such as multimedia communications, autonomous vehicles, and Tactile Internet are the emerging applications for next-generation wireless networks, such as 5th generation (5G) mobile networks. Existing physical-layer channel models, however, do not explicitly consider quality-of-service (QoS) aware related parameters under specific delay constraints. To investigate the performance of low-latency applications in future networks, a new mathematical framework is needed. Effective capacity (EC), which is a link-layer channel model with QoS-awareness, can be used to investigate the performance of wireless networks under certain statistical delay constraints. In this paper, we provide a comprehensive survey on existing works, that use the EC model in various wireless networks. We summarize the work related to EC for different networks such as cognitive radio networks (CRNs), cellular networks, relay networks, adhoc networks, and mesh networks. We explore five case studies encompassing EC operation with different design and architectural requirements. We survey various delay-sensitive applications such as voice and video with their EC analysis under certain delay constraints. We finally present the future research directions with open issues covering EC maximization.

Connected through hyperedge HE-1 (induced by source paper "effective capacity of noma with finite blocklength for low latency communications"):
  with members:
    - "on the performance of non orthogonal multiple access in the finite blocklength regime"
    - "effective capacity and power allocation for machine type communication"
    - "a vision of 6g wireless systems applications trends technologies and open research problems"
    - "ultra reliable and low latency wireless communication tail risk and scale"
    - "short packet downlink transmission with non orthogonal multiple access"
    - "performance analysis of noma for ultra reliable and low latency communications"
    - "power domain non orthogonal multiple access noma in 5g systems potentials and challenges"
    - "a survey on non orthogonal multiple access for 5g networks research challenges and future trends"

Connected through hyperedge HE-2 (induced by source paper "noma versus oma in finite blocklength regime link layer rate performance"):
  with members:
    - "on the performance of non orthogonal multiple access in the finite blocklength regime"
    - "effective capacity and power allocation for machine type communication"
    - "a vision of 6g wireless systems applications trends technologies and open research problems"
    - "performance analysis of noma for ultra reliable and low latency communications"

Connected through hyperedge HE-3 (induced by source paper "machine learning for link quality estimation a survey"):
  with members:
    - "machine learning based link fault identification and localization in complex networks"
    - "over the air deep learning based radio signal classification"
    - "deep learning methods for improved decoding of linear codes"
    - "learning the mmse channel estimator"
    - "electrosense open and big spectrum data"
    - "deep learning in mobile and wireless networking a survey"
    - "power of deep learning for channel estimation and signal detection in ofdm systems"
    - "on deep learning based channel decoding"

Connected through hyperedge HE-4 (induced by source paper "effective capacity for renewal service processes with applications to harq systems"):
  with members:
    - "asymptotic outage analysis of harq ir over time correlated nakagami m fading channels"
    - "adaptive cross packet harq"
    - "effective capacity of retransmission schemes a recurrence relation approach"
    - "energy efficiency of hybrid arq under statistical queuing constraints"
    - "ultra reliable communication in 5g wireless systems"
    - "effective capacity of delay constrained cognitive radio links exploiting primary feedback"

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)