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: "mmwave system for future its a mac layer approach for v2x beam steering"
  Abstract: Millimeter Waves (mmWave) systems have the potential of enabling multi-gigabit-per-second communications in future Intelligent Transportation Systems (ITSs). Unfortunately, because of the increased vehicular mobility, they require frequent antenna beam realignments - thus significantly increasing the in-band Beamforming (BF) overhead. In this paper, we propose Smart Motion-prediction Beam Alignment (SAMBA), a MAC-layer algorithm that exploits the information broadcast via DSRC beacons by all vehicles. Based on this information, overhead-free BF is achieved by estimating the position of the vehicle and predicting its motion. Moreover, adapting the beamwidth with respect to the estimated position can further enhance the performance. Our investigation shows that SAMBA outperforms the IEEE 802.11ad BF strategy, increasing the data rate by more than twice for sparse vehicle density while enhancing the network throughput proportionally to the number of vehicles. Furthermore, SAMBA was proven to be more efficient compared to legacy BF algorithm under highly dynamic vehicular environments and hence, a viable solution for future ITS services.

Connected through hyperedge HE-1 (induced by source paper "efficient millimeter wave infrastructure placement for city scale its"):
  with members:
    - "modeling and design of millimeter wave networks for highway vehicular communication"

Connected through hyperedge HE-2 (induced by source paper "end to end simulation of 5g mmwave networks"):
  with members:
    - "integration of carrier aggregation and dual connectivity for the ns 3 mmwave module"
    - "x tcp a cross layer approach for tcp uplink flows in mmwave networks"
    - "enhancing tcp end to end performance in millimeter wave communications"
    - "beam alignment for millimetre wave links with motion prediction of autonomous vehicles"
    - "tcp in 5g mmwave networks link level retransmissions and mp tcp"
    - "provisioning low latency resilient mobile edge clouds for 5g"
    - "caching meets millimeter wave communications for enhanced mobility management in 5g networks"
    - "reliable video streaming over mmwave with multi connectivity and network coding"

Connected through hyperedge HE-3 (induced by source paper "efficient v2v communication scheme for 5g mmwave hyper connected cavs"):
  with members:
    - "multi radio 5g architecture for connected and autonomous vehicles application and design insights"
    - "beyond wysiwyg sharing contextual sensing data through mmwave v2v communications"
    - "decoding delay performance of random linear network coding for broadcast"
    - "modeling and design of millimeter wave networks for highway vehicular communication"
    - "matching theory for future wireless networks fundamentals and applications"
    - "millimeter wave channel modeling and cellular capacity evaluation"

Connected through hyperedge HE-4 (induced by source paper "multi radio 5g architecture for connected and autonomous vehicles application and design insights"):
  with members:
    - "beam alignment for millimetre wave links with motion prediction of autonomous vehicles"
    - "decoding delay performance of random linear network coding for broadcast"
    - "agile calibration process of full stack simulation frameworks for v2x communications"
    - "modeling and design of millimeter wave networks for highway vehicular communication"
    - "wireless vehicular networks in emergencies a single frequency network approach"
    - "rethinking the intercept probability of random linear network coding"

Connected through hyperedge HE-5 (induced by source paper "a city scale its g5 network for next generation intelligent transportation systems design insights and challenges"):
  with members:
    - "efficient v2v communication scheme for 5g mmwave hyper connected cavs"
    - "multi radio 5g architecture for connected and autonomous vehicles application and design insights"
    - "agile calibration process of full stack simulation frameworks for v2x communications"
    - "modeling and design of millimeter wave networks for highway vehicular communication"
    - "optimized certificate revocation list distribution for secure v2x communications"
    - "harbornet a real world testbed for vehicular 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)