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: "advanced channel coding for space mission telecommand links"
  Abstract: We investigate and compare different options for updating the error correcting code currently used in space mission telecommand links. Taking as a reference the solutions recently emerged as the most promising ones, based on Low-Density Parity-Check codes, we explore the behavior of alternative schemes, based on parallel concatenated turbo codes and soft-decision decoded BCH codes. Our analysis shows that these further options can offer similar or even better performance.

Connected through hyperedge HE-1 (induced by source paper "efficient error correcting codes in the short blocklength regime"):
  with members:
    - "low complexity joint channel estimation and list decoding of short codes"
    - "low latency short packet transmissions fixed length or harq"
    - "design of polar codes in 5g new radio"
    - "joint design of convolutional code and crc under serial list viterbi decoding"
    - "on the error probability of short concatenated polar and cyclic codes with interleaving"
    - "short packets over block memoryless fading channels pilot assisted or noncoherent transmission"
    - "polar code construction for list decoding"
    - "ultra sparse non binary ldpc codes for probabilistic amplitude shaping"

Connected through hyperedge HE-2 (induced by source paper "code design for short blocks a survey"):
  with members:
    - "coded random access applying codes on graphs to design random access protocols"
    - "reliability output decoding of tail biting convolutional codes"
    - "five disruptive technology directions for 5g"
    - "list decoding of polar codes"
    - "threshold saturation via spatial coupling why convolutional ldpc ensembles perform so well over the bec"
    - "multiple bases belief propagation decoding of high density cyclic codes"
    - "accumulate repeat accumulate codes capacity achieving ensembles of systematic codes for the erasure channel with bounded complexity"
    - "channel coding the road to channel capacity"

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)