human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "a unified relay framework with both d f and c f relay nodes"
  Abstract: Decode-and-forward (D-F) and compress-and-forward (C-F) are two fundamentally different relay strategies proposed by (Cover and El Gamal, 1979). Individually, either of them has been successfully generalized to multi-relay channels. In this paper, to allow each relay node the freedom of choosing either of the two strategies, we propose a unified framework, where both the D-F and C-F strategies can be employed simultaneously in the network. It turns out that, to fully incorporate the advantages of both the best known D-F and C-F strategies into a unified framework, the major challenge arises as follows: For the D-F relay nodes to fully utilize the help of the C-F relay nodes, decoding at the D-F relay nodes should not be conducted until all the blocks have been finished; However, in the multi-level D-F strategy, the upstream nodes have to decode prior to the downstream nodes in order to help, which makes simultaneous decoding at all the D-F relay nodes after all the blocks have been finished inapplicable. To tackle this problem, nested blocks combined with backward decoding are used in our framework, so that the D-F relay nodes at different levels can perform backward decoding at different frequencies. As such, the upstream D-F relay nodes can decode before the downstream D-F relay nodes, and the use of backward decoding at each D-F relay node ensures the full exploitation of the help of both the other D-F relay nodes and the C-F relay nodes. The achievable rates under our unified relay framework are found to combine both the best known D-F and C-F achievable rates and include them as special cases.

Connected through hyperedge HE-1 (induced by source paper "noncoherent relaying in energy harvesting communication systems"):
  with members:
    - "resource allocation in wireless networks with rf energy harvesting and transfer"
    - "wireless powered communication opportunities and challenges"
    - "wireless powered relays in cooperative communications time switching relaying protocols and throughput analysis"
    - "energy harvesting noncoherent cooperative communications"
    - "wireless networks with rf energy harvesting a contemporary survey"
    - "power allocation strategies in energy harvesting wireless cooperative networks"
    - "simultaneous information and energy transfer in large scale networks with without relaying"
    - "cooperative energy harvesting networks with spatially random users"

Connected through hyperedge HE-2 (induced by source paper "cut set bound is loose for gaussian relay networks"):
  with members:
    - "cover s open problem the capacity of the relay channel"
    - "improving on the cut set bound via geometric analysis of typical sets"
    - "wasserstein continuity of entropy and outer bounds for interference channels"
    - "improved capacity approximations for gaussian relay networks"
    - "achieving the capacity of the n relay gaussian diamond network within log n bits"
    - "wireless network information flow a deterministic approach"
    - "the approximate capacity of the gaussian n relay diamond network"
    - "computation alignment capacity approximation without noise accumulation"

Connected through hyperedge HE-3 (induced by source paper "mixed noisy network coding and cooperative unicasting in wireless networks"):
  with members:
    - "short message noisy network coding with a decode forward option"
    - "compute and forward strategies for cooperative distributed antenna systems"
    - "selective coding strategy for unicast composite networks"
    - "wireless network information flow a deterministic approach"
    - "the degrees of freedom of compute and forward"
    - "short message quantize forward network coding"
    - "slepian wolf coding over cooperative relay networks"
    - "cooperative strategies for simultaneous and broadcast relay channels"

Connected through hyperedge HE-4 (induced by source paper "short message noisy network coding with a decode forward option"):
  with members:
    - "compress and forward scheme for relay networks backword decoding and connection to bisubmodular flows"
    - "mixed noisy network coding and cooperative unicasting in wireless networks"
    - "wireless network information flow a deterministic approach"
    - "on compress forward without wyner ziv binning for relay networks"
    - "short message quantize forward network coding"
    - "slepian wolf coding over cooperative relay networks"
    - "on the optimal compressions in the compress and forward relay schemes"
    - "noisy network coding"

Connected through hyperedge HE-5 (induced by source paper "achieving the capacity of the n relay gaussian diamond network within log n bits"):
  with members:
    - "capacity approximations for gaussian relay networks"
    - "wireless network information flow a deterministic approach"
    - "the approximate capacity of the gaussian n relay diamond network"
    - "computation alignment capacity approximation without noise accumulation"
    - "wireless network simplification the gaussian n relay diamond network"
    - "on the capacity of the half duplex diamond channel"
    - "on the optimal compressions in the compress and forward relay schemes"
    - "a theory of network equivalence parts i and ii"

Question: Please tell me which class the center node 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)