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 "power scaling laws and near field behaviors of massive mimo and intelligent reflecting surfaces"):
  Abstract: Large arrays might be the solution to the capacity problems in wireless communications. The signal-to-noise ratio (SNR) grows linearly with the number of array elements $N$ when using Massive MIMO receivers/relays. Moreover, intelligent reflecting surfaces (IRSs) have recently attracted attention since their SNR grows as $N^2$, which seems like a major benefit. In this paper, we use a deterministic propagation model for a planar array of arbitrary size, to demonstrate that the mentioned SNR behaviors, and associated power scaling laws, only apply in the far-field. They cannot be used to study the regime where $N\to\infty$. We derive an exact channel gain expression that captures the near-field behavior and use it to revisit the power scaling laws. We derive new finite asymptotic SNR limits but also conclude that these are unlikely to be approached in practice. We further prove that an IRS setup cannot achieve a higher SNR than the corresponding Massive MIMO setups, despite its faster SNR growth. The IRS typically must have a much larger array size to achieve the same SNR. Finally, we show that an optimized IRS can be interpreted as a reconfigurable lens and that it is generally suboptimal to operate it as an "anomalous" mirror.

Includes members:
  Member "intelligent reflecting surface versus decode and forward how large surfaces are needed to beat relaying":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "exploiting randomly located blockages for large scale deployment of intelligent surfaces")
  Member "spatially stationary model for holographic mimo small scale fading":
    also connected through other hyperedges:
      (none)
  Member "propagation modeling and analysis of reconfigurable intelligent surfaces for indoor and outdoor applications in 6g wireless systems":
    also connected through other hyperedges:
      (none)
  Member "beyond max snr joint encoding for reconfigurable intelligent surfaces":
    also connected through other hyperedges:
      (none)
  Member "towards smart and reconfigurable environment intelligent reflecting surface aided wireless network":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "mimo noma networks relying on reconfigurable intelligent surface a signal cancellation based design")
  Member "reconfigurable intelligent surfaces bridging the gap between scattering and reflection":
    also connected through other hyperedges:
      (none)
  Member "intelligent reflecting surface enhanced wireless network via joint active and passive beamforming":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "overhead aware design of reconfigurable intelligent surfaces in smart radio environments")
  Member "beyond massive mimo the potential of data transmission with large intelligent surfaces":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "overhead aware design of reconfigurable intelligent surfaces in smart radio environments")

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)