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 "path selection and rate allocation in self backhauled mmwave networks"):
  Abstract: We investigate the problem of multi-hop scheduling in self-backhauled millimeter wave (mmWave) networks. Owing to the high path loss and blockage of mmWave links, multi-hop paths between the macro base station and the intended users via full-duplex small cells need to be carefully selected. This paper addresses the fundamental question: how to select the best paths and how to allocate rates over these paths subject to latency constraints. To answer this question, we propose a new system design, which factors in mmWave-specific channel variations and network dynamics. The problem is cast as a network utility maximization subject to a bounded delay constraint and network stability. The studied problem is decoupled into: (i) a path selection and (ii) rate allocation, whereby learning the best paths is done by means of a reinforcement learning algorithm, and the rate allocation is solved by applying the successive convex approximation method. Via numerical results, our approach ensures reliable communication with a guaranteed probability of 99.9999%, and reduces latency by 50.64% and 92.9% as compared to baselines.

Includes members:
  Member "joint load balancing and interference mitigation in 5g heterogeneous networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "joint path selection and rate allocation framework for 5g self backhauled mm wave networks")
  Member "ultra reliable and low latency communication in mmwave enabled massive mimo networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "analyzing the tradeoffs in using millimeter wave directional links for high data rate tactile internet applications")
  Member "tracking mm wave channel dynamics fast beam training strategies under mobility":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "joint path selection and rate allocation framework for 5g self backhauled mm wave networks")
  Member "joint in band backhauling and interference mitigation in 5g heterogeneous networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "wireless edge computing with latency and reliability guarantees")
  Member "on the joint impact of beamwidth and orientation error on throughput in directional wireless poisson networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "analyzing the tradeoffs in using millimeter wave directional links for high data rate tactile internet applications")
  Member "what will 5g be":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "5g network slicing using sdn and nfv a survey of taxonomy architectures and future challenges")
  Member "millimeter wave beamforming for wireless backhaul and access in small cell networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "learning beam codebooks with neural networks towards environment aware mmwave mimo")
  Member "backhaul aware interference management in the uplink of wireless small cell networks":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "risk sensitive task fetching and offloading for vehicular edge computing")

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)