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 "cross layer estimation and control for cognitive radio exploiting sparse network dynamics"):
  Abstract: In this paper, a cross-layer framework to jointly optimize spectrum sensing and scheduling in resource constrained agile wireless networks is presented. A network of secondary users (SUs) accesses portions of the spectrum left unused by a network of licensed primary users (PUs). A central controller (CC) schedules the traffic of the SUs, based on distributed compressed measurements collected by the SUs. Sensing and scheduling are jointly controlled to maximize the SU throughput, with constraints on PU throughput degradation and SU cost. The sparsity in the spectrum dynamics is exploited: leveraging a prior spectrum occupancy estimate, the CC needs to estimate only a residual uncertainty vector via sparse recovery techniques. The high complexity entailed by the POMDP formulation is reduced by a low-dimensional belief representation via minimization of the Kullback-Leibler divergence. It is proved that the optimization of sensing and scheduling can be decoupled. A partially myopic scheduling strategy is proposed for which structural properties can be proved showing that the myopic scheme allocates SU traffic to likely idle spectral bands. Simulation results show that this framework balances optimally the resources between spectrum sensing and data transmission. This framework defines sensing-scheduling schemes most informative for network control, yielding energy efficient resource utilization.

Includes members:
  Member "cross layer design of distributed sensing estimation with quality feedback part i optimal schemes":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "multi scale spectrum sensing in dense multi cell cognitive networks")
  Member "time invariant error bounds for modified cs based sparse signal sequence recovery":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "provable low rank phase retrieval and compressive pca")
  Member "active sequential hypothesis testing":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "decentralized sequential active hypothesis testing and the mac feedback capacity")
  Member "dynamic compressive sensing of time varying signals via approximate message passing":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "an approximate message passing framework for side information")
  Member "coalitional games in partition form for joint spectrum sensing and access in cognitive radio networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "shipper cooperation in stochastic drone delivery a dynamic bayesian game approach")
  Member "sensor scheduling for energy efficient target tracking in sensor networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "novel sensor scheduling scheme for intruder tracking in energy efficient sensor networks")
  Member "collaborative spectrum sensing from sparse observations in cognitive radio networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "20 years of evolution from cognitive to intelligent communications")
  Member "cognitive interference management in retransmission based wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "optimal spectrum sharing with arq based legacy users via chain decoding")

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)