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: "soft decoding based strategies for relay and interference channels analysis and achievable rates using ldpc codes"
  Abstract: We provide a rigorous mathematical analysis of two communication strategies: soft decode-and-forward (soft-DF) for relay channels and soft partial interference-cancelation (soft-IC) for interference channels. Both strategies involve soft estimation, which assists the decoding process. We consider LDPC codes, not because of their practical benefits, but because of their analytic tractability, which enables an asymptotic analysis similar to random coding methods of information theory. Unlike some works on the closely-related demodulate-and-forward, we assume non-memoryless, code-structure-aware estimation. With soft-DF, we develop simultaneous density evolution to bound the decoding error probability at the destination. This result applies to erasure relay channels. In one variant of soft-DF, the relay applies Wyner-Ziv coding to enhance its communication with the destination, borrowing from compress-and-forward. To analyze soft-IC, we adapt existing techniques for iterative multiuser detection, and focus on binary-input additive white Gaussian noise interference channels. We prove that optimal point-to-point codes are unsuitable for soft-IC, as well as for all strategies that apply partial decoding to improve upon single-user detection and multiuser detection, including Han-Kobayashi.

Connected through hyperedge HE-1 (induced by source paper "a new coding paradigm for the primitive relay channel"):
  with members:
    - "capacity achieving rate compatible polar codes"
    - "asymmetric error correction and flash memory rewriting using polar codes"
    - "capacity of a class of state dependent orthogonal relay channels"
    - "polar coding for the broadcast channel with confidential messages a random binning analogy"
    - "how to achieve the capacity of asymmetric channels"
    - "universal polar codes"
    - "wireless network information flow a deterministic approach"
    - "nested polar codes for wiretap and relay channels"

Connected through hyperedge HE-2 (induced by source paper "on communication through a gaussian channel with an mmse disturbance constraint"):
  with members:
    - "interference as noise friend or foe"
    - "on the two user interference channel with lack of knowledge of the interference codebook at one receiver"
    - "analysis of mismatched estimation errors using gradients of partition functions"
    - "mmse of bad codes"
    - "statistical physics of signal estimation in gaussian noise theory and examples of phase transitions"
    - "estimation in gaussian noise properties of the minimum mean square error"
    - "a new outer bound and the noisy interference sum rate capacity for gaussian interference channels"
    - "capacity bounds for the gaussian interference channel"

Connected through hyperedge HE-3 (induced by source paper "interference as noise friend or foe"):
  with members:
    - "on the two user interference channel with lack of knowledge of the interference codebook at one receiver"
    - "real interference alignment exploiting the potential of single antenna systems"
    - "on discrete alphabets for the two user gaussian interference channel with one receiver lacking knowledge of the interfering codebook"
    - "approximate sum capacity of k user cognitive interference channels with cumulative message sharing"
    - "the approximate sum capacity of the symmetric gaussian k user interference channel"
    - "wireless network information flow a deterministic approach"
    - "interference alignment from degrees of freedom to constant gap capacity approximations"
    - "k user interference channels general outer bound and sum capacity for certain gaussian channels"

Connected through hyperedge HE-4 (induced by source paper "on the two user interference channel with lack of knowledge of the interference codebook at one receiver"):
  with members:
    - "on discrete alphabets for the two user gaussian interference channel with one receiver lacking knowledge of the interfering codebook"
    - "wireless network information flow a deterministic approach"
    - "a coordinate system for gaussian networks"
    - "the two user gaussian interference channel a deterministic view"
    - "gaussian interference channel capacity to within one bit"

Connected through hyperedge HE-5 (induced by source paper "mmse of bad codes"):
  with members:
    - "communication with disturbance constraints"
    - "interference networks with point to point codes"
    - "sub optimality of treating interference as noise in the cellular uplink"
    - "k user interference channels general outer bound and sum capacity for certain gaussian channels"
    - "statistical physics of signal estimation in gaussian noise theory and examples of phase transitions"
    - "estimation in gaussian noise properties of the minimum mean square error"
    - "on mmse properties and i mmse implications in parallel mimo gaussian channels"
    - "to decode the interference or to consider it as noise"

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)