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 secrecy capacity of compound gaussian mimo wiretap channels"
  Abstract: Strong secrecy capacity of compound wiretap channels is studied. The known lower bounds for the secrecy capacity of compound finite-state memoryless channels under discrete alphabets are extended to arbitrary uncertainty sets and continuous alphabets under the strong secrecy criterion. The conditions under which these bounds are tight are given. Under the saddle-point condition, the compound secrecy capacity is shown to be equal to that of the worst-case channel. Based on this, the compound Gaussian MIMO wiretap channel is studied under the spectral norm constraint and without the degradedness assumption. First, it is assumed that only the eavesdropper channel is unknown, but is known to have a bounded spectral norm (maximum channel gain). The compound secrecy capacity is established in a closed form and the optimal signaling is identified: the compound capacity equals the worst-case channel capacity thus establishing the saddle-point property; the optimal signaling is Gaussian and on the eigenvectors of the legitimate channel and the worst-case eavesdropper is isotropic. The eigenmode power allocation somewhat resembles the standard water-filling but is not identical to it. More general uncertainty sets are considered and the existence of a maximum element is shown to be sufficient for a saddle-point to exist, so that signaling on the worst-case channel achieves the compound capacity of the whole class of channels. The case of rank-constrained eavesdropper is considered and the respective compound secrecy capacity is established. Subsequently, the case of additive uncertainty in the legitimate channel, in addition to the unknown eavesdropper channel, is studied. Its compound secrecy capacity and the optimal signaling are established in a closed-form as well, revealing the same saddle-point property.

Connected through hyperedge HE-1 (induced by source paper "semantically secure lattice codes for compound mimo channels"):
  with members:
    - "random ensembles of lattices from generalized reductions"
    - "optimal signaling for secure communications over gaussian mimo wiretap channels"
    - "universal lattice codes for mimo channels"
    - "a general formula for compound channel capacity"
    - "the mimo wiretap channel decomposed"
    - "construction a of lattices over number fields and block fading wiretap coding"
    - "probability estimates for fading and wiretap channels from ideal class zeta functions"
    - "achieving secrecy capacity of the wiretap channel and broadcast channel with a confidential component"

Connected through hyperedge HE-2 (induced by source paper "arbitrarily varying wiretap channel with state sequence known or unknown at the receiver"):
  with members:
    - "a channel under simultaneous jamming and eavesdropping attack correlated random coding capacities under strong secrecy criteria"
    - "arbitrarily varying wiretap channels with type constrained states"
    - "finite state markov wiretap channel with delayed feedback"
    - "the arbitrarily varying wiretap channel secret randomness stability and super activation"
    - "on the continuity of the secrecy capacity of compound and arbitrarily varying wiretap channels"
    - "semantic security capacity for wiretap channels of type ii"
    - "secrecy results for compound wiretap channels"
    - "capacity results for arbitrarily varying wiretap channels"

Connected through hyperedge HE-3 (induced by source paper "energy efficient power and bandwidth allocation in an integrated sub 6 ghz millimeter wave system"):
  with members:
    - "on the compound mimo wiretap channel with mean feedback"
    - "millimeter wave beam selection using out of band spatial information"
    - "dual sub 6 ghz millimeter wave beamforming and communications to achieve low latency and high energy efficiency in 5g systems"
    - "low power analog to digital conversion in millimeter wave systems impact of resolution and bandwidth on performance"
    - "spatially sparse precoding in millimeter wave mimo systems"
    - "joint spatial division and multiplexing for mm wave channels"

Connected through hyperedge HE-4 (induced by source paper "fundamental limits of covert communication over mimo awgn channel"):
  with members:
    - "on the compound mimo wiretap channel with mean feedback"
    - "fundamental limits of communication with low probability of detection"
    - "covert communication over noisy channels a resolvability perspective"
    - "reliable deniable communication hiding messages in noise"
    - "limits of reliable communication with low probability of detection on awgn channels"

Connected through hyperedge HE-5 (induced by source paper "on the compound mimo wiretap channel with mean feedback"):
  with members:
    - "secrecy results for compound wiretap channels"
    - "secure transmission with multiple antennas ii the mimome wiretap channel"
    - "transmitter optimization for achieving secrecy capacity in gaussian mimo wiretap channels"
    - "the secrecy capacity of the mimo wiretap channel"

Connected through hyperedge HE-6 (induced by source paper "secret key generation using compound sources and one way public communication"):
  with members:
    - "secrecy results for compound wiretap channels"

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)