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 "wireless backhaul networks capacity bound scalability analysis and design guidelines"):
  Abstract: This paper studies the scalability of a wireless backhaul network modeled as a random extended network with multi-antenna base stations (BSs), where the number of antennas per BS is allowed to scale as a function of the network size. The antenna scaling is justified by the current trend towards the use of higher carrier frequencies, which allows to pack large number of antennas in small form factors. The main goal is to study the per-BS antenna requirement that ensures scalability of this network, i.e., its ability to deliver non-vanishing rate to each source-destination pair. We first derive an information theoretic upper bound on the capacity of this network under a general propagation model, which provides a lower bound on the per-BS antenna requirement. Then, we characterize the scalability requirements for two competing strategies of interest: (i) long hop: each source-destination pair minimizes the number of hops by sacrificing multiplexing gain while achieving full beamforming (power) gain over each hop, and (ii) short hop: each source-destination pair communicates through a series of short hops, each achieving full multiplexing gain. While long hop may seem more intuitive in the context of massive multiple-input multiple-output (MIMO) transmission, we show that the short hop strategy is significantly more efficient in terms of per-BS antenna requirement for throughput scalability. As a part of the proof, we construct a scalable short hop strategy and show that it does not violate any fundamental limits on the spatial degrees of freedom (DoFs).

Includes members:
  Member "spatial degrees of freedom of mimo systems in line of sight environment":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "capacity scaling of cellular networks impact of bandwidth infrastructure density and number of antennas")
  Member "millimeter wave beamforming for wireless backhaul and access in small cell networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "learning beam codebooks with neural networks towards environment aware mmwave mimo")
  Member "joint spatial division and multiplexing for mm wave channels":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "statistical beamforming for fdd downlink massive mimo via spatial information extraction and beam selection")
  Member "improved capacity scaling in wireless networks with infrastructure":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "on the effects of subpacketization in content centric mobile networks")
  Member "capacity scaling of wireless ad hoc networks shannon meets maxwell":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "network decomposed hierarchical cooperation in ad hoc networks with social relationships")
  Member "information theoretic operating regimes of large wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "capacity scaling of cellular networks impact of bandwidth infrastructure density and number of antennas")
  Member "hierarchical cooperation achieves optimal capacity scaling in ad hoc networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "wireless mesh networking with devices equipped with multi connectivity")

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.IT(Information Theory)