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 "transmission strategies for remote estimation with an energy harvesting sensor"):
  Abstract: We consider the remote estimation of a time-correlated signal using an energy harvesting (EH) sensor. The sensor observes the unknown signal and communicates its observations to a remote fusion center using an amplify-and-forward strategy. We consider the design of optimal power allocation strategies in order to minimize the mean-square error at the fusion center. Contrary to the traditional approaches, the degree of correlation between the signal values constitutes an important aspect of our formulation. We provide the optimal power allocation strategies for a number of illustrative scenarios. We show that the most majorized power allocation strategy, i.e. the power allocation as balanced as possible, is optimal for the cases of circularly wide-sense stationary (c.w.s.s.) signals with a static correlation coefficient, and sampled low-pass c.w.s.s. signals for a static channel. We show that the optimal strategy can be characterized as a water-filling type solution for sampled low-pass c.w.s.s. signals for a fading channel. Motivated by the high-complexity of the numerical solution of the optimization problem, we propose low-complexity policies for the general scenario. Numerical evaluations illustrate the close performance of these low-complexity policies to that of the optimal policies, and demonstrate the effect of the EH constraints and the degree of freedom of the signal.

Includes members:
  Member "energy harvesting wireless communications a review of recent advances":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "analysis of d2d communication with rf energy harvesting and interference management")
  Member "source channel coding under energy delay and buffer constraints":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "leveraging linear quadratic regulator cost and energy consumption for ultra reliable and low latency iot control systems")
  Member "dynamic compression transmission for energy harvesting multihop networks with correlated sources":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "reconstruction of correlated sources with energy harvesting constraints in delay constrained and delay tolerant communication scenarios")
  Member "near optimal energy control and approximate capacity of energy harvesting communication":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a maximin optimal online power control policy for energy harvesting communications")
  Member "support recovery with sparsely sampled free random matrices":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "bilinear recovery using adaptive vector amp")
  Member "optimal strategies for communication and remote estimation with an energy harvesting sensor":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "optimal causal rate constrained sampling for a class of continuous markov processes")
  Member "broadcasting with an energy harvesting rechargeable transmitter":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "age of information minimization for an energy harvesting source with updating erasures with and without feedback")
  Member "unitary precoding and basis dependency of mmse performance for gaussian erasure channels":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "lattice erasure codes of low rank with noise margins")

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)