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: "short message noisy network coding with a decode forward option"
  Abstract: Short message noisy network coding (SNNC) differs from long message noisy network coding (LNNC) in that one transmits many short messages in blocks rather than using one long message with repetitive encoding. Several properties of SNNC are developed. First, SNNC with backward decoding achieves the same rates as SNNC with offset encoding and sliding window decoding for memoryless networks where each node transmits a multicast message. The rates are the same as LNNC with joint decoding. Second, SNNC enables early decoding if the channel quality happens to be good. This leads to mixed strategies that unify the advantages of decode-forward and noisy network coding. Third, the best decoders sometimes treat other nodes' signals as noise and an iterative method is given to find the set of nodes that a given node should treat as noise sources.

Connected through hyperedge HE-1 (induced by source paper "towards an algebraic network information theory simultaneous joint typicality decoding"):
  with members:
    - "homologous codes for multiple access channels"
    - "gaussian multiple access via compute and forward"
    - "polynomially solvable instances of the shortest and closest vector problems with applications to compute and forward"
    - "an achievable rate region for the three user interference channel based on coset codes"
    - "equivalence of additive combinatorial linear inequalities for shannon entropy and differential entropy"
    - "expanding the compute and forward framework unequal powers signal levels and multiple linear combinations"
    - "secure compute and forward in a bidirectional relay"
    - "distributed decode forward for relay networks"

Connected through hyperedge HE-2 (induced by source paper "flow decomposition for multi user channels part i"):
  with members:
    - "on the optimal compressions in the compress and forward relay schemes"
    - "a greedy omnidirectional relay scheme"

Connected through hyperedge HE-3 (induced by source paper "an information theoretic analysis of the gaussian multicast channel with interactive user cooperation"):
  with members:
    - "enhancing multiuser mimo through opportunistic d2d cooperation"
    - "on the achievable rates of multihop virtual full duplex relay channels"
    - "noisy network coding with partial df"
    - "a survey on device to device communication in cellular networks"
    - "massive mimo multicasting in noncooperative cellular networks"
    - "spectrum sharing for device to device communication in cellular networks"
    - "modeling analysis and optimization of multicast device to device transmissions"
    - "short message noisy network coding with rate splitting"

Connected through hyperedge HE-4 (induced by source paper "on the optimal fronthaul compression and decoding strategies for uplink cloud radio access networks"):
  with members:
    - "fronthaul compression and transmit beamforming optimization for multi antenna uplink c ran"
    - "cloud radio access network virtualizing wireless access for dense heterogeneous systems"
    - "optimized backhaul compression for uplink cloud radio access network"
    - "uplink multicell processing with limited backhaul via per base station successive interference cancellation"
    - "an outer bound for the vector gaussian ceo problem"
    - "robust and efficient distributed compression for cloud radio access networks"
    - "wireless network information flow a deterministic approach"
    - "multiterminal source coding under logarithmic loss"

Connected through hyperedge HE-5 (induced by source paper "distributed decode forward for relay networks"):
  with members:
    - "partial decode forward relaying for the gaussian two hop relay network"
    - "noisy network coding with partial df"
    - "optimized backhaul compression for uplink cloud radio access network"
    - "joint precoding and multivariate backhaul compression for the downlink of cloud radio access networks"
    - "index coding capacity how far can one go with only shannon inequalities"
    - "the approximate sum capacity of the symmetric gaussian k user interference channel"
    - "achieving the capacity of the n relay gaussian diamond network within log n bits"
    - "robust and efficient distributed compression for cloud radio access networks"

Connected through hyperedge HE-6 (induced by source paper "a novel cooperative strategy for wireless multihop backhaul networks"):
  with members:
    - "capacity approximations for gaussian relay networks"
    - "an algebraic approach to physical layer network coding"
    - "multihop backhaul compression for the uplink of cloud radio access networks"
    - "two birds and one stone gaussian interference channel with a shared out of band relay of limited rate"
    - "coding and system design for quantize map and forward relaying"
    - "compute and forward strategies for cooperative distributed antenna systems"
    - "wireless network information flow a deterministic approach"
    - "integer forcing linear receivers"

Connected through hyperedge HE-7 (induced by source paper "coding schemes for discrete memoryless multicast networks with rate limited feedback"):
  with members:
    - "partial decode forward relaying for the gaussian two hop relay network"
    - "the approximate capacity of the gaussian n relay diamond network"
    - "amplify and forward in wireless relay networks"
    - "slepian wolf coding over cooperative relay networks"

Connected through hyperedge HE-8 (induced by source paper "noisy network coding with partial df"):
  with members:
    - "a unified approach for network information theory"
    - "wireless network information flow a deterministic approach"
    - "slepian wolf coding over cooperative relay networks"

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)