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 "to code or not to code in multi hop relay channels"):
  Abstract: Multi-hop relay channels use multiple relay stages, each with multiple relay nodes, to facilitate communication between a source and destination. Previously, distributed space-time coding was used to maximize diversity gain. Assuming a low-rate feedback link from the destination to each relay stage and the source, this paper proposes end-to-end antenna selection strategies as an alternative to distributed space-time coding. One-way (where only the source has data for destination) and two-way (where the destination also has data for the source) multi-hop relay channels are considered with both the full-duplex and half duplex relay nodes. End-to-end antenna selection strategies are designed and proven to achieve maximum diversity gain by using a single antenna path (using single antenna of the source, each relay stage and the destination) with the maximum signal-to-noise ratio at the destination. For the half-duplex case, two single antenna paths with the two best signal-to-noise ratios in alternate time slots are used to overcome the rate loss with half-duplex nodes, with a small diversity gain penalty. Finally to answer the question, whether to code (distributed space-time code) or not (the proposed end-to-end antenna selection strategy) in a multi-hop relay channel, end-to-end antenna selection strategy and distributed space-time coding is compared with respect to several important performance metrics.

Includes members:
  Member "multi hop cooperative wireless networks diversity multiplexing tradeoff and optimal code design":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "multiplexing gain of amplify forward relaying in wireless multi antenna relay networks")
  Member "relay subset selection in wireless networks using partial decode and forward transmission":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "generalized optimal two way relays subsets pairings in cloud based region cognitive networks")
  Member "diversity of mimo multihop relay channels":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "cooperation and underlay mode selection in cognitive radio network")
  Member "performance bounds for bi directional coded cooperation protocols":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "integer forcing and forward transceiver design for mimo multipair two way relaying")
  Member "a simple cooperative diversity method based on network path selection":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "dynwalks global topology and recent changes awareness dynamic network embedding")
  Member "optimal space time codes for the mimo amplify and forward cooperative channel":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "unmanned aerial vehicle assisted cellular communication")
  Member "approximately universal codes over slow fading channels":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "space time signal design for multilevel polar coding in slow fading broadcast channels")

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)