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: "capacity results for block stationary gaussian fading channels with a peak power constraint"
  Abstract: A peak-power-limited single-antenna block-stationary Gaussian fading channel is studied, where neither the transmitter nor the receiver knows the channel state information, but both know the channel statistics. This model subsumes most previously studied Gaussian fading models. The asymptotic channel capacity in the high signal-to-noise ratio (SNR) regime is first computed, and it is shown that the behavior of the channel capacity depends critically on the channel model. For the special case where the fading process is symbol-by-symbol stationary, it is shown that the codeword length must scale at least logarithmically with SNR in order to guarantee that the communication rate can grow logarithmically with SNR with decoding error probability bounded away from one. An expression for the capacity per unit energy is also derived. Furthermore, it is shown that the capacity per unit energy is achievable using temporal ON-OFF signaling with optimally allocated ON symbols, where the optimal ON-symbol allocation scheme may depend on the peak power constraint.

Connected through hyperedge HE-1 (induced by source paper "performance analysis of cognitive radio systems with imperfect channel sensing and estimation"):
  with members:
    - "performance analysis of cognitive radio systems under qos constraints and channel uncertainty"
    - "optimal multiband joint detection for spectrum sensing in cognitive radio networks"
    - "optimal power allocation for fading channels in cognitive radio networks ergodic capacity and outage capacity"
    - "effective capacity analysis of cognitive radio channels for quality of service provisioning"
    - "design of learning based mimo cognitive radio systems"
    - "on peak versus average interference power constraints for protecting primary users in cognitive radio networks"

Connected through hyperedge HE-2 (induced by source paper "on the achievable rate of stationary rayleigh flat fading channels with gaussian inputs"):
  with members:
    - "on the gain of joint processing of pilot and data symbols in stationary rayleigh fading channels"
    - "mutual information of iid complex gaussian signals on block rayleigh faded channels"
    - "low snr capacity of noncoherent fading channels"
    - "on multipath fading channels at high snr"
    - "capacity per unit energy of fading channels with a peak constraint"

Connected through hyperedge HE-3 (induced by source paper "bounds on the capacity of ofdm underspread frequency selective fading channels"):
  with members:
    - "noncoherent capacity of underspread fading channels"
    - "low snr capacity of noncoherent fading channels"
    - "on the sensitivity of noncoherent capacity to the channel model"
    - "channel uncertainty in ultra wideband communication systems"
    - "capacity per unit energy of fading channels with a peak constraint"

Connected through hyperedge HE-4 (induced by source paper "on the gain of joint processing of pilot and data symbols in stationary rayleigh fading channels"):
  with members:
    - "mutual information of iid complex gaussian signals on block rayleigh faded channels"
    - "low snr capacity of noncoherent fading channels"
    - "what is the value of joint processing of pilots and data in block fading channels"

Connected through hyperedge HE-5 (induced by source paper "noncoherent capacity of underspread fading channels"):
  with members:
    - "low snr capacity of noncoherent fading channels"
    - "on the sensitivity of noncoherent capacity to the channel model"
    - "multipath channels of bounded capacity"
    - "capacity of sparse multipath channels in the ultra wideband regime"
    - "low snr capacity of fading channels with peak and average power constraints"
    - "channel uncertainty in ultra wideband communication systems"
    - "mutual information and minimum mean square error in gaussian channels"
    - "capacity per unit energy of fading channels with a peak constraint"

Connected through hyperedge HE-6 (induced by source paper "channels that heat up"):
  with members:
    - "on multipath fading channels at high snr"
    - "capacity per unit energy of fading channels with a peak constraint"

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)