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 "intelligent reflecting and transmitting surface aided millimeter wave massive mimo"):
  Abstract: In this paper, we study two novel massive MIMO architectures for millimeter wave (mmWave) communications which comprise few active antennas, each equipped with a dedicated radio frequency (RF) chain, that illuminate a nearby large intelligent reflecting/transmitting surface (IRS/ITS). The IRS (ITS) consists of a large number of low-cost and energy-efficient passive antenna elements which are able to reflect (transmit) a phase-shifted version of the incident electromagnetic field. Similar to lens array (LA) antennas, IRS/ITS-aided antenna architectures are energy efficient due to the almost lossless over-the-air connection between the active antennas and the intelligent surface. However, unlike for LA antennas, for which the number of active antennas has to linearly grow with the number of passive elements (i.e., the lens aperture) due to the non-reconfigurablility (i.e., non-intelligence) of the lens, for IRS/ITS-aided antennas, the reconfigurablility of the IRS/ITS facilitates scaling up the number of radiating passive elements without increasing the number of costly and bulky active antennas. We show that the constraints that the precoders for IRS/ITS-aided antennas have to meet differ from those of conventional MIMO architectures. Taking these constraints into account and exploiting the sparsity of mmWave channels, we design two efficient precoders and develop a power consumption model for IRS/ITS-aided antennas that takes into account the impacts of the IRS/ITS imperfections, namely the spillover loss, taper loss, aperture loss, and phase shifter loss. Our simulation results reveal that unlike conventional MIMO architectures, IRS/ITS-aided antennas are both highly energy efficient and fully scalable in terms of the number of transmitting antennas. Therefore, IRS/ITS-aided antennas are promising candidates for realizing the potential of mmWave massive MIMO communications in practice.

Includes members:
  Member "a novel communication paradigm for high capacity and security via programmable indoor wireless environments in next generation wireless systems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "exploiting randomly located blockages for large scale deployment of intelligent surfaces")
  Member "intelligent reflecting surfaces for free space optical communications":
    also connected through other hyperedges:
      (none)
  Member "feedback aware precoding for millimeter wave massive mimo systems":
    also connected through other hyperedges:
      (none)
  Member "energy efficiency of mmwave massive mimo precoding with low resolution dacs":
    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 "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 "scalable and energy efficient millimeter massive mimo architectures reflect array and transmit array antennas":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a single rf architecture for multiuser massive mimo via reflecting surfaces")
  Member "intelligent reflecting surface enhanced wireless network joint active and passive beamforming design":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "overhead aware design of reconfigurable intelligent surfaces in smart radio environments")
  Member "c ran with hybrid rf fso fronthaul links joint optimization of rf time allocation and fronthaul compression":
    also connected through other hyperedges:
      (none)

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)