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 "on information flow and feedback in relay networks"):
  Abstract: We consider wireless relay networks where a source node communicates to a destination node with the help of multiple intermediate relay nodes. In wireless, if a node can send information to another node, typically it can also receive information from that node. Therefore, there are inherently a lot of opportunities for feeding back information in such networks. However, transmissions are not isolated and usually subject to broadcast and interference. #R##N#In this paper, we ask the following question: Can the information transfer in both directions of a link be critical to maximizing the end-to-end communication rate in such networks? Equivalently, could one of the directions in each bidirected link (and more generally at least one of the links forming a cycle) be shut down and the capacity of the network still be approximately maintained? Our main result is to show that in any arbitrary Gaussian relay network with bidirected edges and cycles, we can always identify a directed acyclic subnetwork that approximately maintains the capacity of the original network. The edges of this subnetwork can be identified as the information carrying links, and the remaining links as feedback, which can only provide limited contribution to capacity.

Includes members:
  Member "on the impact of a single edge on the network coding capacity":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a local perspective on the edge removal problem")
  Member "improved capacity approximations for gaussian relay networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "cut set bound is loose for gaussian relay networks")
  Member "efficient capacity computation and power optimization for relay networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "polynomial time capacity calculation and scheduling for half duplex 1 2 1 networks")
  Member "wireless network information flow a deterministic approach":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "best relay selection in gaussian half duplex diamond networks")
  Member "wireless network simplification the gaussian n relay diamond network":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "best relay selection in gaussian half duplex diamond networks")
  Member "approximately optimal wireless broadcasting":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "hybrid data sharing and compression strategy for downlink cloud radio access network")
  Member "feedback capacity of the gaussian interference channel to within 2 bits":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "capacity limits of full duplex cellular network")
  Member "a theory of network equivalence parts i and ii":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "scalable capacity bounding models for wireless networks")

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)