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 "snops short non orthogonal pilot sequences for downlink channel state estimation in fdd massive mimo"):
  Abstract: Channel state information (CSI) acquisition is a significant bottleneck in the design of Massive MIMO wireless systems, due to the length of the training sequences required to distinguish the antennas (in the downlink) and the users (for the uplink where a given spectral resource can be shared by a large number of users). In this article, we focus on the downlink CSI estimation case. Considering the presence of spatial correlation at the base transceiver station (BTS) side, and assuming that the per-user channel statistics are known, we seek to exploit this correlation to minimize the length of the pilot sequences. We introduce a scheme relying on non-orthogonal pilot sequences and feedback from the user terminal (UT), which enables the BTS to estimate all downlink channels. Thanks to the relaxed orthogonality assumption on the pilots, the length of the obtained pilot sequences can be strictly lower than the number of antennas at the BTS, while the CSI estimation error is kept arbitrarily small. We introduce two algorithms to dynamically design the required pilot sequences, analyze and validate the performance of the proposed CSI estimation method through numerical simulations using a realistic scenario based on the one-ring channel model.

Includes members:
  Member "pilot length optimization for spatially correlated multi user mimo channel estimation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "covariance aided csi acquisition with non orthogonal pilots in massive mimo a large system performance analysis")
  Member "channel covariance estimation in massive mimo frequency division duplex systems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "uplink downlink channel covariance transformations and precoding design for fdd massive mimo")
  Member "spatially common sparsity based adaptive channel estimation and feedback for fdd massive mimo":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "deep learning based fdd non stationary massive mimo downlink channel reconstruction")
  Member "massive mimo for next generation wireless systems":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "joint power control and lsfd for wireless powered cell free massive mimo")
  Member "downlink training techniques for fdd massive mimo systems open loop and closed loop training with memory":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "energy efficiency optimization for downlink massive mimo with statistical csit")
  Member "a coordinated approach to channel estimation in large scale multiple antenna systems":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "on the pilot contamination attack in multi cell multiuser massive mimo networks")

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)