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 "opportunistic collaborative beamforming with one bit feedback"):
  Abstract: An energy-efficient opportunistic collaborative beamformer with one-bit feedback is proposed for ad hoc sensor networks transmitting a common message over independent Rayleigh fading channels to a relatively distant destination node. In contrast to conventional collaborative beamforming schemes in which each relay node uses channel state information (CSI) to pre-compensate for its channel phase and local carrier offset, the relay nodes in the proposed beamforming scheme do not perform any phase precompensation. Instead, the destination node broadcasts a relay node selection vector to the pool of available relay nodes to opportunistically select a subset of relay nodes whose transmitted signals combine in a quasicoherent manner at the destination. Since the selection vector only indicates which relay nodes are to participate in the collaborative beamformer and does not convey any CSI, only one bit of feedback is required per relay node. Theoretical analysis shows that the received signal power obtained with the proposed opportunistic collaborative beamforming scheme scales linearly with the number of available relay nodes under a fixed total power constraint. Since computation of the optimal selection vector is exponentially complex in the number of available relays, three low-complexity sub-optimal relay node selection rules are also proposed. Simulation results confirm the effectiveness of opportunistic collaborative beamforming with the low-complexity relay node selection rules.

Includes members:
  Member "minimum expected distortion in gaussian layered broadcast coding with successive refinement":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "source channel coding and separation for generalized communication systems")
  Member "a simple cooperative diversity method based on network path selection":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "dynwalks global topology and recent changes awareness dynamic network embedding")
  Member "collaborative beamforming for distributed wireless ad hoc sensor networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "coherent communications in self organizing networks with distributed beamforming")

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)