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: "the impact of physical channel on performance of subspace based channel estimation in massive mimo systems"
  Abstract: A subspace method for channel estimation has been recently proposed for tackling the pilot contamination effect, which is regarded by some researchers as a bottleneck in massive MIMO systems. It was shown in the literature that if the power ratio between the desired signal and interference is kept above a certain value, the received signal spectrum splits into signal and interference eigenvalues, namely, the “pilot contamination” effect can be completely eliminated. However, in the literature an independently distributed (i.d.) channel is assumed, which is actually not much the case in practice. Considering this, a more sensible finite-dimensional physical channel model (i.e., a finite scattering environment, where signals impinge on the base station (BS) from a finite number of angles of arrival (AoA)) is employed in this paper. Via asymptotic spectral analysis, it is demonstrated that, compared with the i.d. channel, the physical channel imposes a penalty in the form of an increased power ratio between the useful signal and the interference. Furthermore, we demonstrate an interesting “antenna saturation” effect, i.e., when the number of the BS antennas approaches infinity, the performance under the physical channel with    $P$   AoAs is limited by and nearly the same as the performance under the i.d. channel with    $P$   receive antennas.

Connected through hyperedge HE-1 (induced by source paper "downlink secrecy rate of one bit massive mimo system with active eavesdropping"):
  with members:
    - "robust designs of beamforming and power splitting for distributed antenna systems with wireless energy harvesting"
    - "secure massive mimo communication with low resolution dacs"
    - "on the uplink achievable rate for massive mimo with 1 bit adc and superimposed pilots"
    - "data aided secure massive mimo transmission with active eavesdropping"
    - "secure massive mimo systems with limited rf chains"
    - "secure transmission with large numbers of antennas and finite alphabet inputs"
    - "jamming resistant receivers for the massive mimo uplink"
    - "beamforming and power splitting designs for an aided secure multi user mimo swipt systems"

Connected through hyperedge HE-2 (induced by source paper "on the spectral efficiency of space constrained massive mimo with linear receivers"):
  with members:
    - "on the spectral efficiency of massive mimo systems with low resolution adcs"
    - "achievable rate of rician large scale mimo channels with transceiver hardware impairments"
    - "space constrained massive mimo hitting the wall of favorable propagation"
    - "massive mimo with non ideal arbitrary arrays hardware scaling laws and circuit aware design"
    - "power scaling of uplink massive mimo systems with arbitrary rank channel means"
    - "massive mimo for next generation wireless systems"
    - "what will 5g be"
    - "energy and spectral efficiency of very large multiuser mimo 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)