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: "performance analysis of dual user macrodiversity mimo systems with linear receivers in flat rayleigh fading"
  Abstract: The performance of linear receivers in the presence of co-channel interference in Rayleigh channels is a fundamental problem in wireless communications. Performance evaluation for these systems is well-known for receive arrays where the antennas are close enough to experience equal average SNRs from a source. In contrast, almost no analytical results are available for macrodiversity systems where both the sources and receive antennas are widely separated. Here, receive antennas experience unequal average SNRs from a source and a single receive antenna receives a different average SNR from each source. Although this is an extremely difficult problem, progress is possible for the two-user scenario. In this paper, we derive closed form results for the probability density function (pdf) and cumulative distribution function (cdf) of the output signal to interference plus noise ratio (SINR) and signal to noise ratio (SNR) of minimum mean squared error (MMSE) and zero forcing (ZF) receivers in independent Rayleigh channels with arbitrary numbers of receive antennas. The results are verified by Monte Carlo simulations and approximations and high SNR analysis are also derived. The results enable further system analysis such as the evaluation of outage probability, bit error rate (BER) and capacity.

Connected through hyperedge HE-1 (induced by source paper "large scale cloud radio access networks with practical constraints asymptotic analysis and its implications"):
  with members:
    - "performance analysis and scaling law of mrc mrt relaying with csi error in massive mimo systems"
    - "multipair two way half duplex relaying with massive arrays and imperfect csi"
    - "a stochastic geometry framework for analyzing pairwise cooperative cellular networks"
    - "spectral efficiency scaling laws in dense random wireless networks with multiple receive antennas"
    - "what will 5g be"
    - "scaling up mimo opportunities and challenges with very large arrays"
    - "asymptotic rate analysis of downlink multi user systems with co located and distributed antennas"
    - "downlink rate distribution in heterogeneous cellular networks under generalized cell selection"

Connected through hyperedge HE-2 (induced by source paper "performance analysis of macrodiversity mimo systems with mmse and zf receivers in flat rayleigh fading"):
  with members:
    - "ergodic sum capacity of macrodiversity mimo systems in flat rayleigh fading"

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)