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 "wideband channel estimation for hybrid beamforming millimeter wave communication systems with low resolution adcs"):
  Abstract: A potential tremendous spectrum resource makes millimeter wave (mmWave) communications a promising technology. High power consumption due to a large number of antennas and analog-to-digital converters (ADCs) for beamforming to overcome the large propagation losses is problematic in practice. As a hybrid beamforming architecture and low-resolution ADCs are considered to reduce power consumption, estimation of mmWave channels becomes challenging. We evaluate several channel estimation algorithms for wideband mmWave systems with hybrid beamforming and low-resolution ADCs. Through simulation, we show that 1) infinite bit ADCs with least-squares estimation have worse channel estimation performance than do one-bit ADCs with orthogonal matching pursuit (OMP) in an SNR range of interest, 2) three- and four-bit quantizers can achieve channel estimation performance close to the unquantized case when using OMP, 3) a receiver with a single RF chain can yield better estimates than that with four RF chains if enough frames are exploited, and 4) for one-bit ADCs, exploitation of higher transmit power and more frames for performance enhancement adversely affects estimation performance after a certain point.

Includes members:
  Member "resolution adaptive hybrid mimo architectures for millimeter wave communications":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "hybrid combining based on constant phase shifters and active inactive switches")
  Member "channel estimation for hybrid architecture based wideband millimeter wave systems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "multiple antenna technologies for beyond 5g")
  Member "hybrid architectures with few bit adc receivers achievable rates and energy rate tradeoffs":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "capacity bounds for communication systems with quantization and spectral constraints")
  Member "millimeter wave receiver efficiency a comprehensive comparison of beamforming schemes with low resolution adcs":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "capacity bounds for communication systems with quantization and spectral constraints")
  Member "channel estimation in broadband millimeter wave mimo systems with few bit adcs":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "capacity bounds for communication systems with quantization and spectral constraints")
  Member "compressed sensing based multi user millimeter wave systems how many measurements are needed":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "deep learning for massive mimo channel state acquisition and feedback")
  Member "near maximum likelihood detector and channel estimator for uplink multiuser massive mimo systems with one bit adcs":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "performance analysis of quantized uplink massive mimo ofdm with oversampling under adjacent channel interference")
  Member "channel estimation and hybrid precoding for millimeter wave cellular systems":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "deep learning for massive mimo channel state acquisition and feedback")

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)