human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "wireless power transfer for distributed estimation in sensor networks"):
  Abstract: This paper studies power allocation for distributed estimation of an unknown scalar random source in sensor networks with a multiple-antenna fusion center (FC), where wireless sensors are equipped with radio-frequency-based energy harvesting technology. The sensors’ observation is locally processed by using an  uncoded amplify-and-forward  scheme. The processed signals are then sent to the FC, and are coherently combined at the FC, at which the best linear unbiased estimator (BLUE) is adopted for reliable estimation. We aim to solve the following two power allocation problems: 1) minimizing distortion under various power constraints; and 2) minimizing total transmit power under distortion constraints, where the distortion is measured in terms of mean-squared error of the BLUE. Two iterative algorithms are developed to solve the nonconvex problems, which converge at least to a local optimum. In particular, the above algorithms are designed to jointly optimize the  amplification coefficients  ,  energy beamforming , and  receive filtering . For each problem, a suboptimal design, a single-antenna FC scenario, and a  common harvester  deployment for collocated sensors, are also studied. Using the powerful  semidefinite relaxation  framework, our result is shown to be valid for any number of sensors, each with different noise power, and for an arbitrarily number of antennas at the FC.

Includes members:
  Member "source channel coding under energy delay and buffer constraints":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "leveraging linear quadratic regulator cost and energy consumption for ultra reliable and low latency iot control systems")
  Member "secrecy wireless information and power transfer with miso beamforming":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "energy efficient resource allocation for secure noma enabled mobile edge computing networks")
  Member "massive mimo for wireless sensing with a coherent multiple access channel":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "on throughput of compressive random access for one short message delivery in iot")
  Member "multiuser miso beamforming for simultaneous wireless information and power transfer":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "design of an miso swipt aided code index modulated multi carrier m dcsk system for e health iot")
  Member "joint transmit beamforming and receive power splitting for miso swipt systems":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "random access based reliable uplink communication and power transfer using dynamic power splitting")
  Member "wireless information and energy transfer in multi antenna interference channel":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "uav positioning and power control for two way wireless relaying")
  Member "optimal power allocation for parameter tracking in a distributed amplify and forward sensor network":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "over the air computation systems optimization analysis and scaling laws")
  Member "throughput maximization in wireless powered communication networks":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "on maximizing information reliability in wireless powered cooperative networks")

Question: Please tell me which class the source paper 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)