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: "optimal power allocation for parameter tracking in a distributed amplify and forward sensor network"
  Abstract: We consider the problem of optimal power allocation in a sensor network where the sensors observe a dynamic parameter in noise and coherently amplify and forward their observations to a fusion center (FC). The FC uses the observations in a Kalman filter to track the parameter, and we show how to find the optimal gain and phase of the sensor transmissions under both global and individual power constraints in order to minimize the mean squared error (MSE) of the parameter estimate. For the case of a global power constraint, a closed-form solution can be obtained. A numerical optimization is required for individual power constraints, but the problem can be relaxed to a semidefinite programming problem (SDP), and we show that the optimal result can be constructed from the SDP solution. We also study the dual problem of minimizing global and individual power consumption under a constraint on the MSE. As before, a closed-form solution can be found when minimizing total power, while the optimal solution is constructed from the output of an SDP when minimizing the maximum individual sensor power. For purposes of comparison, we derive an exact expression for the outage probability on the MSE for equal-power transmission, which can serve as an upper bound for the case of optimal power control. Finally, we present the results of several simulations to show that the use of optimal power control provides a significant reduction in either MSE or transmit power compared with a non-optimized approach (i.e., equal power transmission).

Connected through hyperedge HE-1 (induced by source paper "over the air computation systems optimization analysis and scaling laws"):
  with members:
    - "machine learning at the wireless edge distributed stochastic gradient descent over the air"
    - "wireless networked control systems with coding free data transmission for industrial iot"
    - "wireless federated distillation for distributed edge learning with heterogeneous data"
    - "optimal power control for over the air computation in fading channels"
    - "exploiting the superposition property of wireless communication for max consensus problems in multi agent systems"
    - "towards an intelligent edge wireless communication meets machine learning"
    - "inference from randomized transmissions by many backscatter sensors"
    - "over the air function computation in sensor networks"

Connected through hyperedge HE-2 (induced by source paper "wireless networked control systems with coding free data transmission for industrial iot"):
  with members:
    - "machine learning at the wireless edge distributed stochastic gradient descent over the air"
    - "wireless federated distillation for distributed edge learning with heterogeneous data"
    - "towards an intelligent edge wireless communication meets machine learning"
    - "mimo over the air computation for high mobility multi modal sensing"
    - "wireless network design for control systems a survey"
    - "state secrecy codes for networked linear systems"
    - "learning hand eye coordination for robotic grasping with deep learning and large scale data collection"
    - "sensor scheduling in variance based event triggered estimation with packet drops"

Connected through hyperedge HE-3 (induced by source paper "optimized transmission for consensus in wireless sensor networks"):
  with members:
    - "massive mimo for wireless sensing with a coherent multiple access channel"
    - "designing unimodular codes via quadratic optimization"
    - "estimation in phase shift and forward wireless sensor networks"
    - "optimal relay functionality for snr maximization in memoryless relay networks"

Connected through hyperedge HE-4 (induced by source paper "wireless power transfer for distributed estimation in sensor networks"):
  with members:
    - "source channel coding under energy delay and buffer constraints"
    - "secrecy wireless information and power transfer with miso beamforming"
    - "massive mimo for wireless sensing with a coherent multiple access channel"
    - "multiuser miso beamforming for simultaneous wireless information and power transfer"
    - "joint transmit beamforming and receive power splitting for miso swipt systems"
    - "wireless information and energy transfer in multi antenna interference channel"
    - "throughput maximization in wireless powered communication networks"
    - "multi antenna wireless powered communication with energy beamforming"

Connected through hyperedge HE-5 (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"
    - "gaussian sensor networks with adversarial nodes"
    - "on scaling laws of diversity schemes in decentralized estimation"
    - "distributed source coding in the presence of byzantine sensors"

Connected through hyperedge HE-6 (induced by source paper "power distortion metrics for path planning over gaussian sensor networks"):
  with members:
    - "gaussian sensor networks with adversarial nodes"
    - "sampling and reconstruction of spatial fields using mobile sensors"

Connected through hyperedge HE-7 (induced by source paper "massive mimo for wireless sensing with a coherent multiple access channel"):
  with members:
    - "detection in analog sensor networks with a large scale antenna fusion center"
    - "estimation in phase shift and forward wireless sensor networks"
    - "detection performance in balanced binary relay trees with node and link failures"
    - "energy and spectral efficiency of very large multiuser mimo systems"
    - "estimation diversity and energy efficiency in distributed sensing"

Connected through hyperedge HE-8 (induced by source paper "detection in analog sensor networks with a large scale antenna fusion center"):
  with members:
    - "estimation in phase shift and forward wireless sensor networks"
    - "energy and spectral efficiency of very large multiuser mimo systems"
    - "estimation diversity and energy efficiency in distributed sensing"

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)