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 "multistage relaying using interference networks"):
  Abstract: Wireless networks with multiple nodes that relay information from a source to a destination are expected to be deployed in many applications. Therefore, understanding their design and performance under practical constraints is important. In this work, we propose and study three multihopping decode and forward (MDF) protocols for multistage half-duplex relay networks with no direct link between the source and destination nodes. In all three protocols, we assume no cooperation across relay nodes for encoding and decoding. Numerical evaluation in illustrative example networks and comparison with cheap relay cut-set bounds for half-duplex networks show that the proposed MDF protocols approach capacity in some ranges of channel gains. The main idea in the design of the protocols is the use of coding in interference networks that are created in different states or modes of a half-duplex network. Our results suggest that multistage half-duplex relaying with practical constraints on cooperation is comparable to point-to-point links and full-duplex relay networks, if there are multiple non-overlapping paths from source to destination and if suitable coding is employed in interference network states.

Includes members:
  Member "on the capacity of the half duplex diamond channel":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "best relay selection in gaussian half duplex diamond networks")
  Member "protocols and performance limits for half duplex relay networks":
    also connected through other hyperedges:
      (none)
  Member "cooperative transmission in a wireless relay network based on flow management":
    also connected through other hyperedges:
      (none)
  Member "dmt of multi hop cooperative networks part i basic results":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "on the capacity of the half duplex diamond channel")
  Member "dmt of multi hop cooperative networks part ii half duplex networks with full duplex performance":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "on the capacity of the half duplex diamond channel")
  Member "approximate capacity of gaussian relay networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "multihop backhaul compression for the uplink of cloud radio access 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)