human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "multi connectivity in 5g mmwave cellular networks"):
  Abstract: The millimeter wave (mmWave) frequencies offer the potential of orders of magnitude increases in capacity for next-generation cellular wireless systems. However, links in mmWave networks are highly susceptible to blocking and may suffer from rapid variations in quality. Connectivity to multiple cells - both in the mmWave and in the traditional lower frequencies - is thus considered essential for robust connectivity. However, one of the challenges in supporting multi-connectivity in the mmWave space is the requirement for the network to track the direction of each link in addition to its power and timing. With highly directional beams and fast varying channels, this directional tracking may be the main bottleneck in realizing robust mmWave networks. To address this challenge, this paper proposes a novel measurement system based on (i) the UE transmitting sounding signals in directions that sweep the angular space, (ii) the mmWave cells measuring the instantaneous received signal strength along with its variance to better capture the dynamics and, consequently, the reliability of a channel/direction and, finally, (iii) a centralized controller making handover and scheduling decisions based on the mmWave cell reports and transmitting the decisions either via a mmWave cell or conventional microwave cell (when control signaling paths are not available). We argue that the proposed scheme enables efficient and highly adaptive cell selection in the presence of the channel variability expected at mmWave frequencies.

Includes members:
  Member "initial access in 5g mmwave cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "mobility and blockage aware communications in millimeter wave vehicular networks")
  Member "comparative analysis of initial access techniques in 5g mmwave cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "on optimal multi user beam alignment in millimeter wave wireless systems")
  Member "context information for fast cell discovery in mm wave 5g networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a tutorial on beam management for 3gpp nr at mmwave frequencies")
  Member "millimeter wave cellular networks a mac layer perspective":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "multi user provisioning in millimeter wave urban cellular networks")
  Member "directional initial access for millimeter wave cellular systems":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a tutorial on beam management for 3gpp nr at mmwave frequencies")
  Member "handoff rate and coverage analysis in multi tier heterogeneous networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "stochastic geometry analysis of sojourn time in multi tier cellular networks")
  Member "3 d statistical channel model for millimeter wave outdoor mobile broadband communications":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "machine learning beam tracking and weight optimization for mmwave multi uav links")
  Member "directional cell discovery in millimeter wave cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "a tutorial on beam management for 3gpp nr at mmwave frequencies")

Question: Please tell me which class the source paper 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)