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 "auxiliary beam pair enabled aod and aoa estimation in closed loop large scale mmwave mimo systems"):
  Abstract: Channel estimation is of critical importance in millimeter-wave (mmWave) multiple-input multiple-output (MIMO) systems. Due to the use of large antenna arrays, low-complexity mmWave specific channel estimation algorithms are required. In this paper, an auxiliary beam pair design is proposed to provide high-resolution estimates of the channel's angle-of-departure (AoD) and angle-of-arrival (AoA) for mmWave MIMO systems. By performing an amplitude comparison with respect to each auxiliary beam pair, a set of ratio measures that characterize the channel's AoD and AoA are obtained by the receiver. Either the best ratio measure or the estimated AoD is quantized and fed back to the transmitter via a feedback channel. The proposed technique can be incorporated into control channel design to minimize initial access delay. Though the design principles are derived assuming a high-power regime, evaluation under more realistic assumption shows that by employing the proposed method, good angle estimation performance is achieved under various signal-to-noise ratio levels and channel conditions.

Includes members:
  Member "a lse and sparse message passing based channel estimation for mmwave mimo systems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "principal component analysis based broadband hybrid precoding for millimeter wave massive mimo systems")
  Member "an overview of signal processing techniques for millimeter wave mimo systems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "energy efficient hybrid precoding design for integrated multicast unicast millimeter wave communications with swipt")
  Member "low complexity channel estimation for millimeter wave systems with hybrid a d antenna processing":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "principal component analysis based broadband hybrid precoding for millimeter wave massive mimo systems")
  Member "frequency selective hybrid precoding for limited feedback millimeter wave systems":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "gmd based hybrid beamforming for large reconfigurable intelligent surface assisted millimeter wave massive mimo")
  Member "beamforming tradeoffs for initial ue discovery in millimeter wave mimo systems":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "statistical blockage modeling and robustness of beamforming in millimeter wave systems")
  Member "near optimal hybrid analog and digital precoding for downlink mmwave massive mimo systems":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "hybrid precoder and combiner design with low resolution phase shifters in mmwave mimo systems")
  Member "hybrid analog digital channel estimation and beamforming training throughput tradeoff":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "wirelessly powered sensor networks power allocation for channel estimation and energy beamforming")
  Member "energy efficient hybrid analog and digital precoding for mmwave mimo systems with large antenna arrays":
    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.IT(Information Theory)