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: "on scaling laws of diversity schemes in decentralized estimation"
  Abstract: This paper is concerned with decentralized estimation of a Gaussian source using multiple sensors. We consider a diversity scheme where only the sensor with the best channel sends their measurements over a fading channel to a fusion center, using the analog amplify and forwarding technique. The fusion centre reconstructs an MMSE estimate of the source based on the received measurements. A distributed version of the diversity scheme where sensors decide whether to transmit based only on their local channel information is also considered. We derive asymptotic expressions for the expected distortion (of the MMSE estimate at the fusion centre) of these schemes as the number of sensors becomes large. For comparison, asymptotic expressions for the expected distortion for a coherent multi-access scheme and an orthogonal access scheme are derived. We also study for the diversity schemes, the optimal power allocation for minimizing the expected distortion subject to average total power constraints. The effect of optimizing the probability of transmission on the expected distortion in the distributed scenario is also studied. It is seen that as opposed to the coherent multi-access scheme and the orthogonal scheme (where the expected distortion decays as 1/M, M being the number of sensors), the expected distortion decays only as 1/ln(M) for the diversity schemes. This reduction of the decay rate can be seen as a tradeoff between the simplicity of the diversity schemes and the strict synchronization and large bandwidth requirements for the coherent multi-access and the orthogonal schemes, respectively.

Connected through hyperedge HE-1 (induced by source paper "optimal communication strategies in networked cyber physical systems with adversarial elements"):
  with members:
    - "information theoretic approach to strategic communication as a hierarchical game"
    - "power distortion metrics for path planning over gaussian sensor networks"
    - "matched multiuser gaussian source channel communications via uncoded schemes"
    - "optimal power allocation for parameter tracking in a distributed amplify and forward sensor network"
    - "gaussian sensor networks with adversarial nodes"
    - "distributed source coding in the presence of byzantine sensors"

Connected through hyperedge HE-2 (induced by source paper "optimal power allocation for parameter tracking in a distributed amplify and forward sensor network"):
  with members:
    - "estimation in phase shift and forward wireless sensor networks"
    - "parameter tracking via optimal distributed beamforming in an analog sensor network"
    - "optimal spectrum sharing in mimo cognitive radio networks via semidefinite programming"
    - "estimation diversity and energy efficiency in distributed sensing"

Connected through hyperedge HE-3 (induced by source paper "estimation in phase shift and forward wireless sensor networks"):
  with members:
    - "phase only analog encoding for a multi antenna fusion center"
    - "the ergodic capacity of phase fading interference networks"
    - "distributed detection over fading macs with multiple antennas at the fusion center"
    - "universal distributed estimation over multiple access channels with constant modulus signaling"
    - "optimal spectrum sharing in mimo cognitive radio networks via semidefinite programming"
    - "estimation diversity and energy efficiency in distributed sensing"

Connected through hyperedge HE-4 (induced by source paper "the effect of correlated observations on the performance of distributed estimation"):
  with members:
    - "controlled collaboration for linear coherent estimation in wireless sensor networks"
    - "decentralized estimation over orthogonal multiple access fading channels in wireless sensor networks optimal and suboptimal estimators"
    - "estimation diversity and energy efficiency in distributed sensing"

Connected through hyperedge HE-5 (induced by source paper "phase only analog encoding for a multi antenna fusion center"):
  with members:
    - "distributed detection over fading macs with multiple antennas at the fusion center"
    - "optimal spectrum sharing in mimo cognitive radio networks via semidefinite programming"
    - "estimation diversity and energy efficiency in distributed sensing"

Connected through hyperedge HE-6 (induced by source paper "asymptotic capacity analysis for adaptive transmission schemes under general fading distributions"):
  with members:
    - "applications of tauberian theorem for high snr analysis of performance over fading channels"
    - "opportunistic scheduling and beamforming for mimo sdma downlink systems with linear combining"

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)