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 "indoor massive mimo uplink pilot mitigation using channel state information map"):
  Abstract: Massive MIMO brings both motivations and challenges to develop the 5th generation Mobile wireless technology. The promising number of users and the high bitrate offered per unit area are challenged by uplink pilot contamination due to pilot reuse and a limited number of orthogonal pilot sequences. This paper proposes a solution to mitigate uplink pilot contamination in an indoor scenario where multi-cell share the same pool of pilot sequences, that are supposed to be less than the number of users. This can be done by reducing uplink pilots using Channel State Information (CSI) prediction. The proposed method is based on machine learning approach, where a quantized version of Channel State Information (QCSI) is learned during estimation session and stored at the Base Station (BS) to be exploited for future CSI prediction. The learned QCSI are represented by a weighted directed graph, which is responsible to monitor and predict the CSI of User Terminals (UTs) in the local cell. We introduce an online learning algorithm to create and update this graph which we call CSI map. Simulation results show an increase in the downlink sum-rate and a significant feedback reduction.

Includes members:
  Member "selective uplink training for massive mimo systems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "channel coherence classification with frame shifting in massive mimo systems")
  Member "scaling up mimo opportunities and challenges with very large arrays":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "downlink secrecy rate of one bit massive mimo system with active eavesdropping")
  Member "massive mimo how many antennas do we need":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "decentralized equalization with feedforward architectures for massive mu mimo")
  Member "channel state prediction feedback and scheduling for a multiuser mimo ofdm downlink":
    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.NI(Networking and Internet Architecture)