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: "capacity analysis of a multi cell multi antenna cooperative cellular network with co channel interference"
  Abstract: Characterization and modeling of co-channel interference is critical for the design and performance evaluation of realistic multi-cell cellular networks. In this paper, based on alpha stable processes, an analytical co-channel interference model is proposed for multi-cell multiple-input multi-output (MIMO) cellular networks. The impact of different channel parameters on the new interference model is analyzed numerically. Furthermore, the exact normalized downlink average capacity is derived for a multi-cell MIMO cellular network with co-channel interference. Moreover, the closed-form normalized downlink average capacity is derived for cell-edge users in multi-cell multiple-input single-output (MISO) cooperative cellular networks with co-channel interference. From the new co-channel interference model and capacity formulas, the impact of cooperative antennas and base stations on cell-edge user performance in the multi-cell multi-antenna cellular network is investigated by numerical methods. Numerical results show that cooperative transmission can improve the capacity performance of multi-cell multi-antenna cooperative cellular networks, especially in a scenario with a high density of interfering base stations. The capacity performance gain is degraded with the increased number of cooperative antennas or base stations.

Connected through hyperedge HE-1 (induced by source paper "smart contract based secure spectrum sharing in multi operators wireless communication networks"):
  with members:
    - "smart contract slas for dense small cell as a service"
    - "traffic management for heterogeneous networks with opportunistic unlicensed spectrum sharing"
    - "spatial spectrum and energy efficiency of random cellular networks"
    - "user mobility evaluation for 5g small cell networks based on individual mobility model"
    - "energy efficiency evaluation of cellular networks based on spatial distributions of traffic load and power consumption"

Connected through hyperedge HE-2 (induced by source paper "neural networks in hybrid precoding for millimeter wave massive mimo systems"):
  with members:
    - "deep learning based channel estimation for beamspace mmwave massive mimo systems"
    - "energy efficiency of mmwave massive mimo precoding with low resolution dacs"
    - "an introduction to deep learning for the physical layer"
    - "energy efficiency challenges of 5g small cell networks"
    - "energy efficiency optimization of 5g radio frequency chain systems"
    - "spatial spectrum and energy efficiency of random cellular networks"
    - "user mobility evaluation for 5g small cell networks based on individual mobility model"
    - "deep residual learning for image recognition"

Connected through hyperedge HE-3 (induced by source paper "a novel jt comp scheme in 5g fractal small cell networks"):
  with members:
    - "ultra reliable uav communication using altitude and cooperation diversity"
    - "downlink small cell base station cooperation strategy in fractal small cell networks"
    - "wireless fractal cellular networks"
    - "spatial spectrum and energy efficiency of random cellular networks"
    - "user mobility evaluation for 5g small cell networks based on individual mobility model"
    - "5g ultra dense cellular networks"
    - "a stochastic geometry framework for analyzing pairwise cooperative cellular networks"
    - "5g wireless backhaul networks challenges and research advances"

Connected through hyperedge HE-4 (induced by source paper "performance analysis of urban mmwave multi hop v2v communications with shifted exponential distribution headway"):
  with members:
    - "5g software defined vehicular networks"
    - "energy efficiency challenges of 5g small cell networks"
    - "multi hop links quality analysis of 5g enabled vehicular networks"
    - "energy efficiency optimization of 5g radio frequency chain systems"
    - "spatial spectrum and energy efficiency of random cellular networks"
    - "user mobility evaluation for 5g small cell networks based on individual mobility model"
    - "5g ultra dense cellular networks"
    - "5g wireless backhaul networks challenges and research advances"

Connected through hyperedge HE-5 (induced by source paper "energy efficiency of generalized spatial modulation aided massive mimo systems"):
  with members:
    - "machine learning inspired energy efficient hybrid precoding for mmwave massive mimo systems"
    - "energy efficiency challenges of 5g small cell networks"
    - "spatial spectrum and energy efficiency of random cellular networks"
    - "user mobility evaluation for 5g small cell networks based on individual mobility model"
    - "5g ultra dense cellular networks"
    - "5g wireless backhaul networks challenges and research advances"
    - "impact of transceiver power consumption on the energy efficiency of zero forcing detector in massive mimo systems"
    - "what will 5g be"

Connected through hyperedge HE-6 (induced by source paper "a new small world iot routing mechanism based on cayley graphs"):
  with members:
    - "ultra reliable low latency communications in autonomous vehicular networks"
    - "tradeoff between delay and physical layer security in wireless networks"
    - "joint optimization of computation and communication power in multi user massive mimo systems"
    - "coverage and handoff analysis of 5g fractal small cell networks"
    - "cache aided non orthogonal multiple access"
    - "toward a tractable delay analysis in ultra dense networks"
    - "energy efficiency evaluation of cellular networks based on spatial distributions of traffic load and power consumption"
    - "throughput delay reliability tradeoff with arq in wireless ad hoc networks"

Connected through hyperedge HE-7 (induced by source paper "coverage and handoff analysis of 5g fractal small cell networks"):
  with members:
    - "modeling and analyzing millimeter wave cellular systems"
    - "a novel millimeter wave channel simulator and applications for 5g wireless communications"
    - "vehicular communications for 5g cooperative small cell networks"
    - "analysis of human body blockage in urban millimeter wave cellular communications"
    - "a dual directional path loss model in 5g wireless fractal small cell networks"
    - "energy efficiency optimization of 5g radio frequency chain systems"
    - "wireless fractal cellular networks"
    - "fundamentals of the downlink green coverage and energy efficiency in heterogeneous networks"

Connected through hyperedge HE-8 (induced by source paper "vehicles to pedestrians signal transmissions based on cloud computing"):
  with members:
    - "5g software defined vehicular networks"
    - "vehicular communications for 5g cooperative small cell networks"
    - "spatial spectrum and energy efficiency of random cellular networks"
    - "user mobility evaluation for 5g small cell networks based on individual mobility model"
    - "5g ultra dense cellular networks"
    - "5g wireless backhaul networks challenges and research advances"

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)