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: "optimal multiuser loading in quantized massive mimo under spatially correlated channels"
  Abstract: Low-resolution digital-to-analog converter (DAC) has shown great potential in facilitating cost- and power-efficient implementation of massive multiple-input multiple-output (MIMO) systems. We investigate the performance of a massive MIMO downlink network with low-resolution DACs using regularized zero-forcing (RZF) precoding. It serves multiple receivers equipped with finite-resolution analog-to-digital converters (ADCs). By taking the quantization errors at both the transmitter and receivers into account under spatially correlated channels, the regularization parameter for RZF is optimized with a closed-form solution by applying the asymptotic random matrix theory. The optimal regularization parameter increases linearly with respect to the user loading ratio while independent of the ADC quantization resolution and the channel correlation. Furthermore, asymptotic sum rate performance is characterized and a closed-form expression for the optimal user loading ratio is obtained at a low signal-to-noise ratio. The optimal ratio increases with the DAC resolution while it decreases with the ADC resolution. Numerical simulations verify our observations.

Connected through hyperedge HE-1 (induced by source paper "secure massive mimo communication with low resolution dacs"):
  with members:
    - "mimo channel information feedback using deep recurrent network"
    - "quantized constant envelope precoding with psk and qam signaling"
    - "on performance of quantized transceiver in multiuser massive mimo downlinks"
    - "spectral and energy efficiency of multi pair massive mimo relay network with hybrid processing"
    - "power efficient and secure wpcns with hardware impairments and non linear eh circuit"
    - "a tractable framework for performance analysis of dense multi antenna networks"
    - "analysis of one bit quantized precoding for the multiuser massive mimo downlink"
    - "analysis and design of secure massive mimo systems in the presence of hardware impairments"

Connected through hyperedge HE-2 (induced by source paper "slnr based precoding for one bit quantized massive mimo in mmwave communications"):
  with members:
    - "one bit sphere decoding for uplink massive mimo systems with one bit adcs"
    - "uplink performance of wideband massive mimo with one bit adcs"
    - "overview of millimeter wave communications for fifth generation 5g wireless networks with a focus on propagation models"
    - "analysis of one bit quantized precoding for the multiuser massive mimo downlink"
    - "quantized precoding for massive mu mimo"
    - "low power analog to digital conversion in millimeter wave systems impact of resolution and bandwidth on performance"
    - "capacity analysis of one bit quantized mimo systems with transmitter channel state information"
    - "massive mimo for next generation wireless systems"

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)