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: "asymptotic analysis of spatial coupling coding for compute and forward relaying"
  Abstract: Compute-and-forward (CAF) relaying is effective to increase bandwidth efficiency of wireless two-way relay channels. In a CAF scheme, a relay is designed to decode a linear combination composed of transmitted messages from other terminals or relays. Design for error-correcting codes and its decoding algorithms suitable for CAF relaying schemes remain as an important issue to be studied. As described in this paper, we will present an asymptotic performance analysis of LDPC codes over two-way relay channels based on density evolution (DE). Because of the asymmetric characteristics of the channel, we use the population dynamics DE combined with DE formulas for asymmetric channels to obtain BP thresholds. Additionally, we also evaluate the asymptotic performance of spatially coupled LDPC codes for two-way relay channels. The results indicate that the spatial coupling codes yield improvements in the BP threshold compared with corresponding uncoupled codes for two-way relay channels. Finally, we will compare the mutual information rate and rate achievability between the CAF scheme and the MAC separation decoding scheme. We demonstrate the possibility that the CAF scheme has higher reliability in the high-rate region.

Connected through hyperedge HE-1 (induced by source paper "asymptotic analysis on ldpc bicm scheme for compute and forward relaying"):
  with members:
    - "secure computation and forward with linear codes"
    - "an algebraic approach to physical layer network coding"
    - "universal codes for the gaussian mac via spatial coupling"
    - "channel coding and decoding in a relay system operated with physical layer network coding"
    - "can iterative decoding for erasure correlated sources be universal"
    - "compute and forward harnessing interference through structured codes"
    - "density evolution for asymmetric memoryless channels"

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)