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 macrodiversity mimo systems with mmse and zf receivers in flat rayleigh fading"
  Abstract: Consider a multiuser system where an arbitrary number of users communicate with a distributed receive array over independent Rayleigh fading paths. The receive array performs minimum mean squared error (MMSE) or zero forcing (ZF) combining and perfect channel state information is assumed at the receiver. This scenario is well-known and exact analysis is possible when the receive antennas are located in a single array. However, when the antennas are distributed, the individual links all have different average signal to noise ratio (SNRs) and this is a much more challenging problem. In this paper, we provide approximate distributions for the output SNR of a ZF receiver and the output signal to interference plus noise ratio (SINR) of an MMSE receiver. In addition, simple high SNR approximations are provided for the symbol error rate (SER) of both receivers assuming M-PSK or M-QAM modulations. These high SNR results provide array gain and diversity gain information as well as a remarkably simple functional link between performance and the link powers.

Connected through hyperedge HE-1 (induced by source paper "uplink analysis of large mu mimo systems with space constrained arrays in ricean fading"):
  with members:
    - "on the role of transmit correlation diversity in multiuser mimo systems"
    - "multi user massive mimo communication systems based on irregular antenna arrays"
    - "on the spectral efficiency of space constrained massive mimo with linear receivers"
    - "space constrained massive mimo hitting the wall of favorable propagation"
    - "power scaling of uplink massive mimo systems with arbitrary rank channel means"
    - "massive mimo for next generation wireless systems"
    - "millimeter wave channel modeling and cellular capacity evaluation"
    - "scaling up mimo opportunities and challenges with very large arrays"

Connected through hyperedge HE-2 (induced by source paper "interference management in 5g reverse tdd hetnets with wireless backhaul a large system analysis"):
  with members:
    - "large system analysis of the energy consumption distribution in multi user mimo systems with mobility"
    - "small cell in band wireless backhaul in massive mimo systems a cooperation of next generation techniques"
    - "wireless backhaul networks capacity bound scalability analysis and design guidelines"
    - "linear precoding based on polynomial expansion large scale multi cell mimo systems"
    - "massive mimo for next generation wireless systems"
    - "optimal linear precoding in multi user mimo systems a large system analysis"
    - "what will 5g be"
    - "optimal design of energy efficient multi user mimo systems is massive mimo the answer"

Connected through hyperedge HE-3 (induced by source paper "mimo zero forcing performance evaluation using the holonomic gradient method"):
  with members:
    - "schur complement based analysis of mimo zero forcing for rician fading"
    - "exact mimo zero forcing detection analysis for transmit correlated rician fading"
    - "diversity of mmse mimo receivers"

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)