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: "worst case jamming on mimo gaussian channels"
  Abstract: Worst-case jamming of legitimate communications over multiple-input multiple-output Gaussian channels is studied in this paper. A worst-case scenario with a ‘smart’ jammer that knows all channels and the transmitter's strategy and is only power limited is considered. It is shown that the simplification of the system model by neglecting the properties of the jamming channel leads to a loss of important insights regarding the effects of the jamming power and jamming channel on optimal jamming strategies of the jammer. Without neglecting the jamming channel, a lower-bound on the rate of legitimate communication subject to jamming is derived, and conditions for this bound to be positive are given. The lower-bound rate can be achieved regardless of the quality of the jamming channel, the power limit of the jammer, and the transmit strategy of the jammer. Moreover, general forms of an optimal jamming strategy, on the basis of which insights into the effect of jamming power and jamming channel are exposed, are given. It is shown that the general forms can lead to closed-form optimal jamming solutions when the power limit of the jammer is larger than a threshold. Subsequently, the scenario in which the effect of jamming dominates the effect of noise (the case of practical interest) is considered, and an optimal jamming strategy is derived in closed-form. Simulation examples demonstrate lower-bound rates, performance of the derived jamming strategy, and an effect of inaccurate channel information on the jamming strategy.

Connected through hyperedge HE-1 (induced by source paper "real time detection of hybrid and stealthy cyber attacks in smart grid"):
  with members:
    - "machine learning methods for attack detection in the smart grid"
    - "optimal jammer placement in wireless localization systems"
    - "optimal data attacks on power grids leveraging detection measurement jamming"

Connected through hyperedge HE-2 (induced by source paper "jamming resistant receivers for the massive mimo uplink"):
  with members:
    - "jamming resistant receivers for massive mimo"
    - "pilot contamination is not a fundamental asymptotic limitation in massive mimo"
    - "subverting massive mimo by smart jamming"
    - "secure massive mimo transmission with an active eavesdropper"
    - "jamming aided secure communication in massive mimo rician channels"
    - "physical layer security for massive mimo an overview on passive eavesdropping and active attacks"
    - "securing massive mimo at the physical layer"
    - "interference reduction in multi cell massive mimo systems i large scale fading precoding and decoding"

Connected through hyperedge HE-3 (induced by source paper "optimal jammer placement in wireless localization systems"):
  with members:
    - "power optimization for network localization"
    - "fundamental limits of wideband localization part ii cooperative networks"
    - "fundamental limits of wideband localization part i a general framework"

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)