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: "are heterogeneous cloud based radio access networks cost effective"
  Abstract: Mobile networks of the future are predicted to be much denser than today's networks to cater to increasing user demands. In this context, cloud-based radio access networks have garnered significant interest as a cost-effective solution to the problem of coping with denser networks and providing higher data rates. However, to the best of the authors' knowledge, a quantitative analysis of the cost of such networks is yet to be undertaken. This paper develops a theoretic framework that enables computation of the deployment cost of a network (modeled using various spatial point processes) to answer the question posed by the paper's title. Then, the framework obtained is used along with a complexity model, which enables computing the information processing costs of a network, to compare the deployment cost of a cloud-based network against that of a traditional LTE network, and to analyze why they are more economical. Using this framework and an exemplary budget, this paper shows that cloud-based radio access networks require approximately 10% to 15% less capital expenditure per square kilometer than traditional LTE networks. It also demonstrates that the cost savings depend largely on the costs of base stations and the mix of backhaul technologies used to connect base stations with data centers.

Connected through hyperedge HE-1 (induced by source paper "full duplex cloud radio access network stochastic design and analysis"):
  with members:
    - "self interference in full duplex multi user mimo channels"
    - "cross layer design for downlink multihop cloud radio access networks with network coding"
    - "secrecy and energy efficiency in massive mimo aided heterogeneous c ran a new look at interference"
    - "echo state networks for proactive caching in cloud based radio access networks with mobile users"
    - "on the optimal fronthaul compression and decoding strategies for uplink cloud radio access networks"
    - "a stochastic analysis of network mimo systems"
    - "massive mimo enabled full duplex cellular networks"
    - "full duplex mimo small cell networks with interference cancellation"

Connected through hyperedge HE-2 (induced by source paper "will sdn be part of 5g"):
  with members:
    - "5g fronthaul latency and jitter studies of cpri over ethernet"
    - "r fft function split at ifft fft in unified lte cran and cable access network"
    - "nfv and sdn key technology enablers for 5g networks"
    - "hardware accelerated sdr platform for adaptive air interfaces"
    - "srslte an open source platform for lte evolution and experimentation"
    - "software defined optical networks sdons a comprehensive survey"
    - "cross layer software defined 5g network"
    - "fronthaul constrained cloud radio access networks insights and challenges"

Connected through hyperedge HE-3 (induced by source paper "recent advances in cloud radio access networks system architectures key techniques and open issues"):
  with members:
    - "fronthaul compression and precoding design for c rans over ergodic fading channels"
    - "optimal fronthaul quantization for cloud radio positioning"
    - "inter tier interference suppression in heterogeneous cloud radio access networks"
    - "contract based interference coordination in heterogeneous cloud radio access networks"
    - "energy efficient resource assignment and power allocation in heterogeneous cloud radio access networks"
    - "cooperative interference mitigation and handover management for heterogeneous cloud small cell networks"
    - "fronthaul constrained cloud radio access networks insights and challenges"
    - "distributed fronthaul compression and joint signal recovery in cloud ran"

Connected through hyperedge HE-4 (induced by source paper "cluster content caching an energy efficient approach to improve quality of service in cloud radio access networks"):
  with members:
    - "fog computing based radio access networks issues and challenges"
    - "inter tier interference suppression in heterogeneous cloud radio access networks"
    - "fronthaul constrained cloud radio access networks insights and challenges"
    - "system architecture and key technologies for 5g heterogeneous cloud radio access networks"
    - "on content centric wireless delivery networks"
    - "heterogeneous cloud radio access networks a new perspective for enhancing spectral and energy efficiencies"
    - "optimized backhaul compression for uplink cloud radio access network"
    - "living on the edge the role of proactive caching in 5g 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.NI(Networking and Internet Architecture)