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: "low complexity receiver for uplink scma system via expectation propagation"
  Abstract: Sparse code multiple access (SCMA) scheme is considered to be one promising non-orthogonal multiple access technology for the future fifth generation (5G) communications. Due to the sparse nature, message passing algorithm (MPA) has been used as the receiver to achieve close to maximum likelihood (ML) detection performance with much lower complexity. However, the complexity order of MPA is still exponential with the size of codebook and the degree of signal superposition on a given resource element. In this paper, we propose a novel low complexity iterative receiver based on expectation propagation algorithm (EPA), which reduces the complexity order from exponential to linear. Simulation results demonstrate that the proposed EPA receiver achieves nearly the same block error rate (BLER) performance as the conventional message passing algorithm (MPA) receiver with orders less complexity.

Connected through hyperedge HE-1 (induced by source paper "potential key technologies for 6g mobile communications"):
  with members:
    - "6g the next frontier"
    - "enabling large intelligent surfaces with compressive sensing and deep learning"
    - "beyond massive mimo the potential of data transmission with large intelligent surfaces"
    - "the potential of using large antenna arrays on intelligent surfaces"
    - "low density lattice codes"

Connected through hyperedge HE-2 (induced by source paper "multidimensional constellations for uplink scma systems a comparative study"):
  with members:
    - "survey on multi access edge computing for internet of things realization"
    - "a survey on non orthogonal multiple access for 5g networks research challenges and future trends"
    - "modulation and multiple access for 5g networks"
    - "an optimization perspective of the superiority of noma compared to conventional oma"
    - "polar codes for scma systems"
    - "a survey on low latency towards 5g ran core network and caching solutions"
    - "design of non orthogonal multiple access enhanced backscatter communication"
    - "enabling sphere decoding for scma"

Connected through hyperedge HE-3 (induced by source paper "a universal receiver for uplink noma systems"):
  with members:
    - "turbo like iterative multi user receiver design for 5g non orthogonal multiple access"
    - "a survey on non orthogonal multiple access for 5g networks research challenges and future trends"
    - "expectation propagation for approximate bayesian inference"

Connected through hyperedge HE-4 (induced by source paper "signature based non orthogonal multiple access s noma for massive machine type communications in 5g"):
  with members:
    - "massive non orthogonal multiple access for cellular iot potentials and limitations"
    - "non orthogonal random access nora for 5g networks"

Connected through hyperedge HE-5 (induced by source paper "turbo like iterative multi user receiver design for 5g non orthogonal multiple access"):
  with members:
    - "a survey on non orthogonal multiple access for 5g networks research challenges and future trends"
    - "expectation propagation for approximate bayesian inference"

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)