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 "bit error rate analysis of cooperative beamforming for transmitting individual data streams"):
  Abstract: Cooperative beamforming (CB) has been proposed as a special case of coordinated multi-point techniques in wireless communications. In wireless sensor networks, CB can enable low power communication by allowing a collection of sensor nodes to transmit data simultaneously to a distant fusion center in one hop. Besides the traditional CB approach where all nodes need to share and transmit the same data, a more recent technique allows each node to transmit its own data while still achieving the benefits of cooperation. However, the intricacies of varying beamforming gains in the direct sequence spread spectrum with binary frequency shift keying multiple access scheme used in this context need to be taken into account when evaluating the performance of this beamforming technique. In this paper, we take the first step towards a more comprehensive understanding of this individual-data CB technique by proposing a best suited decoding scheme and analyzing its bit error rate (BER) performance over an additive white Gaussian noise channel. Through analytical expressions and simulation results BER curves are drawn and the achieved performance improvement offered by the CB gain is quantified.

Includes members:
  Member "cooperative beamforming for wireless ad hoc networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "performance analysis of a cross layer collaborative beamforming approach in the presence of channel and phase errors")
  Member "collaborative beamforming for distributed wireless ad hoc sensor networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (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)