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 "multi hop cooperative wireless networks diversity multiplexing tradeoff and optimal code design"):
  Abstract: We consider single-source single-sink (ss-ss) multi-hop relay networks, with slow-fading links and single-antenna#R##N#half-duplex relay nodes. While two-hop cooperative relay networks have been studied in great detail in terms of#R##N#the diversity-multiplexing tradeoff (DMT), few results are available for more general networks. In this paper, we#R##N#identify two families of networks that are multi-hop generalizations of the two-hop network: K-Parallel-Path (KPP)networks and layered networks.KPP networks, can be viewed as the union of K node-disjoint parallel relaying paths, each of length greater than one. KPP networks are then generalized to KPP(I) networks, which permit interference between paths and to KPP(D) networks, which possess a direct link from source to sink. We characterize the DMT of these families of networks completely for K > 3. Layered networks are networks comprising of layers of relays with edges existing only between adjacent layers, with more than one relay in each layer. We prove that a linear DMT between the maximum diversity dmax and the maximum multiplexing gain of 1 is achievable for single-antenna fully-connected layered networks. This is shown to be equal to the optimal DMT if the number of relaying layers is less than 4.For multiple-antenna KPP and layered networks, we provide an achievable DMT, which is significantly better than known lower bounds for half duplex networks.For arbitrary multi-terminal wireless networks with multiple source-sink pairs, the maximum achievable diversity is shown to be equal to the min-cut between the corresponding source and the sink, irrespective of whether the network has half-duplex or full-duplex relays. For arbitrary ss-ss single-antenna directed acyclic networks with full-duplex relays, we prove that a linear tradeoff between maximum diversity and maximum multiplexing gain is achievable.Along the way, we derive the optimal DMT of a generalized parallel channel and derive lower bounds for the DMT of triangular channel matrices, which are useful in DMT computation of various protocols. We also give#R##N#alternative and often simpler proofs of several existing results and show that codes achieving full diversity on a#R##N#MIMO Rayleigh fading channel achieve full diversity on arbitrary fading channels. All protocols in this paper are#R##N#explicit and use only amplify-and-forward (AF) relaying. We also construct codes with short block-lengths based#R##N#on cyclic division algebras that achieve the optimal DMT for all the proposed schemes.Two key implications of the results in the paper are that the half-duplex constraint does not entail any rate loss for a large class of cooperative networks and that simple AF protocols are often sufficient to attain the optimal DMT

Includes members:
  Member "diversity and degrees of freedom of cooperative wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "dmt of multi hop cooperative networks part i basic results")
  Member "a deterministic approach to wireless relay networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "on the deterministic sum capacity of the multiple access wiretap channel")
  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 "optimum diversity multiplexing tradeoff in the multiple relays network":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "on the diversity multiplexing tradeoff in multiple relay network")
  Member "diversity multiplexing tradeoff of asynchronous cooperative diversity in wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "asynchronous interference alignment")
  Member "towards the optimal amplify and forward cooperative diversity scheme":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "relay pair selection in buffer aided successive opportunistic relaying using a multi antenna source")
  Member "d mg tradeoff and optimal codes for a class of af and df cooperative communication protocols":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "a trellis coded modulation scheme for the fading relay channel")
  Member "optimal space time codes for the mimo amplify and forward cooperative channel":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "unmanned aerial vehicle assisted cellular communication")

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)