human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "uplink spectral efficiency of massive mimo with spatially correlated rician fading"
  Abstract: This paper considers the uplink (UL) of a multi-cell Massive MIMO (multiple-input multiple-output) system with spatially correlated Rician fading channels. The channel model is composed of a deterministic line-of-sight (LoS) path and a stochastic non-line-of-sight (NLoS) component describing a spatially correlated multipath environment. We derive the statistical properties of the minimum mean squared error (MMSE) and least-square (LS) channel estimates for this model. Using these estimates for maximum ratio (MR) combining, rigorous closed-form UL spectral efficiency (SE) expressions are derived. Numerical results show that the SE is higher when using the MMSE estimator than the LS estimator, and the performance gap increases with the number of antennas. Moreover, Rician fading provides higher achievable SEs than Rayleigh fading since the LoS path improves the sum SE.

Connected through hyperedge HE-1 (induced by source paper "massive mimo with spatially correlated rician fading channels"):
  with members:
    - "covariance matrix estimation for massive mimo"
    - "covariance matrix estimation in massive mimo"
    - "impact of line of sight and unequal spatial correlation on uplink mu mimo systems"
    - "massive mimo pilot decontamination and channel interpolation via wideband sparse channel estimation"
    - "massive mimo with imperfect channel covariance information"
    - "asymptotic analysis of multicell massive mimo over rician fading channels"
    - "power scaling of uplink massive mimo systems with arbitrary rank channel means"
    - "massive mimo for next generation wireless systems"

Connected through hyperedge HE-2 (induced by source paper "spectral efficiency analysis of multi cell massive mimo systems with ricean fading"):
  with members:
    - "spectral efficiency analysis of cell free massive mimo systems with zero forcing detector"
    - "massive mimo with spatially correlated rician fading channels"
    - "massive mimo has unlimited capacity"
    - "pilot power allocation through user grouping in multi cell massive mimo systems"
    - "asymptotic analysis of multicell massive mimo over rician fading channels"
    - "multipair full duplex relaying with massive arrays and linear processing"
    - "power scaling of uplink massive mimo systems with arbitrary rank channel means"
    - "massive mimo for maximal spectral efficiency how many users and pilots should be allocated"

Question: Please tell me which class the center node 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)