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 "low rank spatial channel estimation for millimeter wave cellular systems"):
  Abstract: The tremendous bandwidth available in the millimeter wave (mmW) frequencies between 30 and 300 GHz have made these bands an attractive candidate for next-generation cellular systems. However, reliable communication at these frequencies depends extensively on beamforming with very high-dimensional antenna arrays. Estimating the channel sufficiently accurately to perform beamforming can thus be challenging both due to low coherence time and large number of antennas. Also, the measurements used for channel estimation may need to be made with analog beamforming where the receiver can "look" in only direction at a time. This work presents a novel method for estimation of the receive-side spatial covariance matrix of a channel from a sequence of power measurements made at different angular directions. The method reduces the spatial covariance estimation to a matrix completion optimization problem. To reduce the number of measurements, the optimization can incorporate the low-rank constraints in the channels that are typical in the mmW setting. The optimization is convex and fast, iterative methods are presented to solving the problem. Simulations are presented for both single and multi-path channels using channel models derived from real measurements in New York City at 28 GHz.

Includes members:
  Member "millimeter wave human blockage at 73 ghz with a simple double knife edge diffraction model and extension for directional antennas":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "statistical blockage modeling and robustness of beamforming in millimeter wave systems")
  Member "channel dynamics and snr tracking in millimeter wave cellular systems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a tutorial on beam management for 3gpp nr at mmwave frequencies")
  Member "transport layer performance in 5g mmwave cellular":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a survey on recent advances in transport layer protocols")
  Member "low power analog to digital conversion in millimeter wave systems impact of resolution and bandwidth on performance":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "capacity bounds for communication systems with quantization and spectral constraints")
  Member "directional cell discovery in millimeter wave cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a tutorial on beam management for 3gpp nr at mmwave frequencies")
  Member "millimeter wave cellular wireless networks potentials and challenges":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "wirelessly powered sensor networks power allocation for channel estimation and energy beamforming")
  Member "low complexity hybrid precoding in massive multiuser mimo systems":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "energy efficient hybrid precoding design for integrated multicast unicast millimeter wave communications with swipt")
  Member "millimeter wave channel modeling and cellular capacity evaluation":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "coverage analysis of uavs in millimeter wave networks a stochastic geometry approach")

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)