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 "a scalable framework for csi feedback in fdd massive mimo via dl path aligning"):
  Abstract: Unlike the time-division duplexing (TDD) systems, the downlink (DL) and uplink (UL) channels are not reciprocal anymore in the case of frequency-division duplexing (FDD). However, some long-term parameters, e.g. the time delays and angles of arrival (AoAs) of the channel paths, still enjoy reciprocity. In this paper, by efficiently exploiting the aforementioned limited reciprocity, we address the DL channel state information (CSI) feedback in a practical wideband massive multiple-input multiple-output (MIMO) system operating in the FDD mode. With orthogonal frequency-division multiplexing (OFDM) waveform and assuming frequency-selective fading channels, we propose a scalable framework for the DL pilots design, DL CSI acquisition, and the corresponding CSI feedback in the UL. In particular, the base station (BS) can transmit the FFT-based pilots with the carefully-selected phase shifts. Then the user can rely on the so-called time-domain aggregate channel (TAC) to derive the feedback of reduced imensionality according to either its own knowledge about the statistics of the DL channels or the instruction from the serving BS. We demonstrate that each user can just feed back one scalar number per DL channel path for the BS to recover the DL CSIs. Comprehensive numerical results further corroborate our designs.

Includes members:
  Member "pilot decontamination via pdp alignment":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "flexible pilot contamination mitigation with doppler psd alignment")
  Member "channel acquisition for massive mimo ofdm with adjustable phase shift pilots":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "energy efficiency optimization for downlink massive mimo with statistical csit")
  Member "flexible pilot contamination mitigation with doppler psd alignment":
    also connected through other hyperedges:
      (none)
  Member "structured compressive sensing based superimposed pilot design in downlink large scale mimo systems":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "an overview of transmission theory and techniques of large scale antenna systems for 5g wireless communications")
  Member "achievable rates of fdd massive mimo systems with spatial channel correlation":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "deep learning for massive mimo channel state acquisition and feedback")
  Member "pilot beam pattern design for channel estimation in massive mimo systems":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "secure massive mimo communication with low resolution dacs")
  Member "distributed compressive csit estimation and feedback for fdd multi user massive mimo systems":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "dl based csi feedback and cooperative recovery in 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-7 (induced by source paper "energy efficiency optimization for downlink massive mimo with statistical csit")

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)