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: "blind detection with polar codes"
  Abstract: In blind detection, a set of candidates has to be decoded within a strict time constraint, to identify which transmissions are directed at the user equipment. Blind detection is an operation required by the 3GPP LTE/LTE-Advanced standard, and it will be required in the 5th generation wireless communication standard (5G) as well. We propose a blind detection scheme based on polar codes, where the radio network temporary identifier (RNTI) is transmitted instead of some of the frozen bits. A low-complexity decoding stage decodes all candidates, selecting a subset that is decoded by a high-performance algorithm. Simulations results show good missed detection and false alarm rates, that meet the system specifications. We also propose an early stopping criterion for the second decoding stage that can reduce the number of operations performed, improving both average latency and energy consumption. The detection speed is analyzed and different system parameter combinations are shown to meet the stringent timing requirements, leading to various implementation trade-offs.

Connected through hyperedge HE-1 (induced by source paper "on the decoding of polar codes on permuted factor graphs"):
  with members:
    - "belief propagation decoding of polar codes on permuted factor graphs"
    - "partitioned list decoding of polar codes analysis and improvement of finite length performance"
    - "fast and flexible successive cancellation list decoders for polar codes"
    - "llr based successive cancellation list decoding of polar codes"
    - "list decoding of polar codes"
    - "performance of polar codes for channel and source coding"

Connected through hyperedge HE-2 (induced by source paper "design and implementation of a polar codes blind detection scheme"):
  with members:
    - "symbol decision successive cancellation list decoder for polar codes"
    - "llr based successive cancellation list decoding of polar codes"
    - "fast polar decoders algorithm and implementation"
    - "list decoding of polar codes"

Connected through hyperedge HE-3 (induced by source paper "on the computational complexity of blind detection of binary linear codes"):
  with members:
    - "design and implementation of a polar codes blind detection scheme"
    - "blind detection of polar codes"

Connected through hyperedge HE-4 (induced by source paper "blind detection of polar codes"):
  with members:
    - "fast list decoders for polar codes"
    - "flexible and low complexity encoding and decoding of systematic polar codes"
    - "llr based successive cancellation list decoding of polar codes"
    - "fast polar decoders algorithm and implementation"
    - "list decoding of polar codes"
    - "how to construct polar codes"
    - "channel polarization a method for constructing capacity achieving codes for symmetric binary input 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)