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 "agile millimeter wave networks with provable guarantees"):
  Abstract: There is much interest in integrating millimeter wave radios (mmWave) into wireless LANs and 5G cellular networks to benefit from their multiple GHz of available spectrum. Yet unlike existing technologies, e.g., WiFi, mmWave radios require highly directional antennas. Since the antennas have pencil-beams, the transmitter and receiver need to align their antenna beams before they can communicate. Existing solutions scan the entire space to find the best alignment. Such a process has been shown to introduce up to seconds of delay, and is unsuitable for wireless networks where an access point has to quickly switch between users and accommodate mobile clients. #R##N#This paper presents Rapid-Link, a new protocol that can find the best mmWave beam alignment without scanning the space. Given all possible directions for setting the antenna beam, Rapid-Link provably finds the optimal direction in logarithmic number of measurements. Further, Rapid-Link works within the existing 802.11ad standard for mmWave LAN, and can support both clients and access points. We have implemented Rapid-Link in a mmWave radio and evaluated it empirically. Our results show that it reduces beam alignment delay by orders of magnitude. In particular, for highly directional mmWave devices operating under 802.11ad, the delay drops from over a second to 2.5 ms.

Includes members:
  Member "phase retrieval an overview of recent developments":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "phase retrieval of low rank matrices by anchored regression")
  Member "channel estimation and hybrid precoding for millimeter wave cellular systems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "deep learning for massive mimo channel state acquisition and feedback")
  Member "nearly optimal sparse fourier transform":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "privacy preserving learning via deep net pruning")
  Member "coding the beams improving beamforming training in mmwave communication system":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "sub channel allocation for device to device underlaying full duplex mmwave small cells using coalition formation games")
  Member "1 eps approximate sparse recovery":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "stronger l2 l2 compressed sensing without iterating")
  Member "lower bounds for sparse recovery":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "querying a matrix through matrix vector products")
  Member "in building wideband partition loss measurements at 2 5 and 60 ghz":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "measurement characterization and modeling of lora technology in multi floor buildings")

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)