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 "blind estimation of sparse broadband massive mimo channels with ideal and one bit adcs"):
  Abstract: We study the maximum likelihood problem for the blind estimation of massive mmWave MIMO channels while taking into account their underlying sparse structure, the temporal shifts across antennas in the broadband regime, and ultimately one-bit quantization at the receiver. The sparsity in the angular domain is exploited as a key property to enable the unambiguous blind separation between user's channels. The main advantage of this approach is the fact that the overhead due to pilot sequences can be dramatically reduced especially when operating at low SNR per antenna. In addition, as sparsity is the only assumption made about the channel, the proposed method is robust with respect to the statistical properties of the channel and data and allows the channel estimation and the separation of interfering users from adjacent base stations to be performed in rapidly time-varying scenarios. For the case of one-bit receivers, a blind channel estimation is proposed that relies on the Expectation Maximization (EM) algorithm. Additionally, performance limits are derived based on the clairvoyant Cramer Rao lower bound. Simulation results demonstrate that this maximum likelihood formulation yields superior estimation accuracy in the narrowband as well as the wideband regime with reasonable computational complexity and limited model assumptions.

Includes members:
  Member "channel estimation and performance analysis of one bit massive mimo systems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "performance analysis of quantized uplink massive mimo ofdm with oversampling under adjacent channel interference")
  Member "blind signal detection in massive mimo exploiting the channel sparsity":
    also connected through other hyperedges:
      (none)
  Member "uplink performance of wideband massive mimo with one bit adcs":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "capacity bounds for communication systems with quantization and spectral constraints")
  Member "bayes optimal joint channel and data estimation for massive mimo with low precision adcs":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "faster activity and data detection in massive random access a multi armed bandit approach")
  Member "mixed adc massive mimo":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a regression approach to certain information transmission problems")
  Member "channel acquisition for massive mimo ofdm with adjustable phase shift pilots":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "energy efficiency optimization for downlink massive mimo with statistical csit")
  Member "channel estimation in broadband millimeter wave mimo systems with few bit adcs":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "capacity bounds for communication systems with quantization and spectral constraints")
  Member "one bit massive mimo channel estimation and high order modulations":
    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")

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)