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: "cooperative beamforming for wireless ad hoc networks"
  Abstract: Via collaborative beamforming, nodes in a wireless network are able to transmit a common message over long distances in an energy efficient fashion. However, the process of making available the same message to all collaborating nodes introduces delays. In this paper, a MAC-PHY cross-layer scheme is proposed that enables collaborative beamforming at significantly reduced collaboration overhead. It consists of two phases. In the first phase, nodes transmit locally in a random access time-slotted fashion. Simultaneous transmissions from multiple source nodes are viewed as linear mixtures of all transmitted packets. In the second phase, a set of collaborating nodes, acting as a distributed antenna system, beamform the received analog waveform to one or more faraway destinations. This step requires multiplication of the received analog waveform by a complex weight, which is independently computed by each cooperating node, and which allows packets bound to the same destination to add coherently at the destination node. Assuming that each node has access to location information, the proposed scheme can achieve high throughput, which in certain cases exceeds one. An analysis of the symbol error probability corresponding to the proposed scheme is provided.

Connected through hyperedge HE-1 (induced by source paper "bit error rate analysis of cooperative beamforming for transmitting individual data streams"):
  with members:
    - "collaborative beamforming for distributed wireless ad hoc sensor networks"

Connected through hyperedge HE-2 (induced by source paper "performance analysis of a cross layer collaborative beamforming approach in the presence of channel and phase errors"):
  with members:
    - "collaborative beamforming for distributed wireless ad hoc sensor networks"

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)