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: "transmit radiation pattern invariance in mimo radar with application to doa estimation"
  Abstract: The desired property of having the same beampattern for different columns of a beamspace transformation matrix (beamforming vectors) often plays a key importance in practical applications. At most   ${2^{M - 1}} - 1$    beamforming vectors with the same beampattern can be generated from any given beamforming vector, where    $M$   is the size of the beamforming vector. Thus, one can start with a single (mother) beamforming vector, which gives a desired beampattern, but may not satisfy some other desired properties, and generate all other beamforming vectors, which give the same beampattern, in a computationally efficient way. Then the beamforming vectors, which in addition satisfy other desired properties that the mother beamforming vector may not satisfy, can be selected. Such procedure is developed in this letter in the application to the transmit beamspace design that ensures practically important properties for multiple-input multiple-output radar. A computationally efficient sub-optimal method for selecting best beamforming vectors from a population of vectors that give the same beampattern is also developed.

Connected through hyperedge HE-1 (induced by source paper "energy efficient beamforming for massive mimo public channel"):
  with members:
    - "performance analysis of mixed adc massive mimo systems over rician fading channels"
    - "joint beamforming and broadcasting in massive mimo"
    - "on the spectral efficiency of massive mimo systems with low resolution adcs"
    - "broadbeam for massive mimo systems"
    - "omnidirectional space time block coding for common information broadcasting in massive mimo systems"
    - "spatially sparse precoding in millimeter wave mimo systems"

Connected through hyperedge HE-2 (induced by source paper "power efficient hybrid beamforming for massive mimo public channel"):
  with members:
    - "performance analysis of mixed adc massive mimo systems over rician fading channels"
    - "joint beamforming and broadcasting in massive mimo"
    - "broadbeam for massive mimo systems"
    - "omnidirectional space time block coding for common information broadcasting in massive mimo systems"
    - "spatially sparse precoding in millimeter wave mimo systems"

Connected through hyperedge HE-3 (induced by source paper "transmit array interpolation for doa estimation via tensor decomposition in 2 d mimo radar"):
  with members:
    - "efficient transmit beamspace design for search free based doa estimation in mimo radar"
    - "transmit energy focusing for doa estimation in mimo radar with colocated antennas"
    - "phased mimo radar a tradeoff between phased array and mimo radars"

Connected through hyperedge HE-4 (induced by source paper "broadbeam for massive mimo systems"):
  with members:
    - "massive mimo 10 myths and one grand question"
    - "a generalized spatial correlation model for 3d mimo channels based on the fourier coefficients of power spectrums"
    - "massive mimo for next generation wireless systems"
    - "preliminary results on 3d channel modeling from theory to standardization"
    - "five disruptive technology directions for 5g"
    - "scaling up mimo opportunities and challenges with very large arrays"
    - "constant envelope multi user precoding for frequency selective massive mimo systems"
    - "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)