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 "cooperative transmission for wireless relay networks using limited feedback"):
  Abstract: To achieve the available performance gains in half-duplex wireless relay networks, several cooperative schemes have been earlier proposed using either distributed space-time coding or distributed beamforming for the transmitter without and with channel state information (CSI), respectively. However, these schemes typically have rather high implementation and/or decoding complexities, especially when the number of relays is high. In this paper, we propose a simple low-rate feedback-based approach to achieve maximum diversity with a low decoding and implementation complexity. To further improve the performance of the proposed scheme, the knowledge of the second-order channel statistics is exploited to design long-term power loading through maximizing the receiver signal-to-noise ratio (SNR) with appropriate constraints. This maximization problem is approximated by a convex feasibility problem whose solution is shown to be close to the optimal one in terms of the error probability. Subsequently, to provide robustness against feedback errors and further decrease the feedback rate, an extended version of the distributed Alamouti code is proposed. It is also shown that our scheme can be generalized to the differential transmission case, where it can be applied to wireless relay networks with no CSI available at the receiver.

Includes members:
  Member "network beamforming using relays with perfect channel information":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "capitalizing backscatter aided hybrid relay communications with wireless energy harvesting")
  Member "multi group ml decodable collocated and distributed space time block codes":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "construction of block orthogonal stbcs and reducing their sphere decoding complexity")
  Member "distributed space time codes for cooperative networks with partial csi":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "opportunistic relaying for space time coded cooperation with multiple antenna terminals")
  Member "distributed transmit beamforming using feedback control":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "low complexity random rotation based schemes for intelligent reflecting surfaces")

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)