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 "directional beamforming for millimeter wave mimo systems"):
  Abstract: The focus of this paper is on beamforming in a millimeter-wave (mmW) multi-input multi-output (MIMO) setup that has gained increasing traction in meeting the high data-rate requirements of next-generation wireless systems. For a given MIMO channel matrix, the optimality of beamforming with the dominant right-singular vector (RSV) at the transmit end and with the matched filter to the RSV at the receive end has been well-understood. When the channel matrix can be accurately captured by a physical (geometric) scattering model across multiple clusters/paths as is the case in mmW MIMO systems, we provide a physical interpretation for this optimal structure: beam steering across the different paths with appropriate power allocation and phase compensation. While such an explicit physical interpretation has not been provided hitherto, practical implementation of such a structure in a mmW system is fraught with considerable difficulties (complexity as well as cost) as it requires the use of per-antenna gain and phase control. This paper characterizes the loss in received SNR with an alternate low-complexity beamforming solution that needs only per-antenna phase control and corresponds to steering the beam to the dominant path at the transmit and receive ends. While the loss in received SNR can be arbitrarily large (theoretically), this loss is minimal in a large fraction of the channel realizations reinforcing the utility of directional beamforming as a good candidate solution for mmW MIMO systems.

Includes members:
  Member "channel estimation and hybrid precoding for millimeter wave cellular systems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "deep learning for massive mimo channel state acquisition and feedback")
  Member "millimeter wave cellular wireless networks potentials and challenges":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "wirelessly powered sensor networks power allocation for channel estimation and energy beamforming")
  Member "spatially sparse precoding in millimeter wave mimo systems":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "energy efficient hybrid precoding design for integrated multicast unicast millimeter wave communications with swipt")
  Member "five disruptive technology directions for 5g":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "deep learning enabled optimization of downlink beamforming under per antenna power constraints algorithms and experimental demonstration")
  Member "millimeter wave beamforming for wireless backhaul and access in small cell networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "learning beam codebooks with neural networks towards environment aware mmwave mimo")
  Member "scaling up mimo opportunities and challenges with very large arrays":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "downlink secrecy rate of one bit massive mimo system with active eavesdropping")
  Member "capacity of sparse wideband channels with partial channel feedback":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "noisy beam alignment techniques for reciprocal mimo channels")

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)