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 "high mobility wideband massive mimo communications doppler compensation analysis and scaling law"):
  Abstract: In this paper, we apply angle-domain Doppler compensation for high-mobility wideband massive multi-input multi-output (MIMO) uplink transmission. The time-varying multipath channel is considered between high-speed terminal and static base station (BS), where multiple Doppler frequency offsets (DFOs) are associated with distinct angle of departures (AoDs). With the aid of the large-scale uniform linear array (ULA) at the transmitter, we design a beamforming network to generate multiple parallel beamforming branches, each transmitting signal pointing to one particular angle. Then, the transmitted signal in each branch will experience only one dominant DFO when passing over the time-varying channel, which can be easily compensated before transmission starts. We theoretically analyze the Doppler spread of the equivalent uplink channel after angle-domain Doppler compensation, which takes into account both the mainlobe and sidelobes of the transmit beam in each branch. It is seen that the channel time-variation can be effectively suppressed if the number of transmit antennas is sufficiently large. Interestingly, the asymptotic scaling law of channel variation is obtained, which shows that the Doppler spread is proportional to the maximum DFO and decreases approximately as $1/\sqrt{M}$ ($M$ is the number of transmit antennas) when $M$ is sufficiently large. Numerical results are provided to corroborate the proposed scheme.

Includes members:
  Member "a new view of multi user hybrid massive mimo non orthogonal angle division multiple access":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "beam squint and channel estimation for wideband mmwave massive mimo ofdm systems")
  Member "frequency synchronization for uplink massive mimo systems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a survey on deep learning based techniques for modeling and estimation of massivemimo channels")
  Member "high mobility ofdm downlink transmission with large scale antenna array":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "otfs based receiver scheme with multi antennas in high mobility v2x systems")
  Member "angle domain doppler pre compensation for high mobility ofdm uplink with a massive ula":
    also connected through other hyperedges:
      (none)
  Member "directivity beamwidth tradeoff of massive mimo uplink beamforming for high speed train communication":
    also connected through other hyperedges:
      (none)
  Member "bdma for millimeter wave terahertz massive mimo transmission with per beam synchronization":
    also connected through other hyperedges:
      - Hyperedge HE-4 (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)