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 performance evaluation of massive mu mimo systems"
  Abstract: body abstract heading (also in Bold) Abstract— The present paper deals with an OFDM-based uplink within a multi-user MIMO (MU-MIMO) system where a massive MIMO approach is employed. In this context, the linear detectors Minimum Mean-Squared Error (MMSE), Zero Forcing (ZF) and Maximum Ratio Combining (MRC) are considered and assessed. This papers includes Bit Error Rate (BER) results for uncoded QPSK/OFDM transmissions through a flat Rayleigh fading channel under the assumption of perfect power control and channel estimation. BER results are obtained through Monte Carlo simulations. Performance results are dis- cussed in detail and we confirm the achievable "massive MIMO" effects, even for a reduced complexity detection technique, when the number of receive antennas at BS is much larger than the number of transmit antennas. Index Terms— Massive MU-MIMO, uplink detection, OFDM.

Connected through hyperedge HE-1 (induced by source paper "low complexity statistically robust precoder detector computation for massive mimo systems"):
  with members:
    - "low complexity and statistically robust beamformer design for massive mimo systems"
    - "on the ergodic rate lower bounds with applications to massive mimo"
    - "low complexity massive mimo subspace estimation and tracking from low dimensional projections"
    - "fifty years of mimo detection the road to large scale mimos"
    - "linear precoding based on polynomial expansion large scale multi cell mimo systems"
    - "massive mimo for next generation wireless systems"
    - "scaling up mimo opportunities and challenges with very large arrays"
    - "achieving massive mimo spectral efficiency with a not so large number of antennas"

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)