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: "belief propagation based multi user detection"
  Abstract: We apply belief propagation (BP) to multi--user detection in a spread spectrum system, under the assumption of Gaussian symbols. We prove that BP is both convergent and allows to estimate the correct conditional expectation of the input symbols. It is therefore an optimal --minimum mean square error-- detection algorithm. This suggests the possibility of designing BP detection algorithms for more general systems. As a byproduct we rederive the Tse-Hanly formula for minimum mean square error without any recourse to random matrix theory.

Connected through hyperedge HE-1 (induced by source paper "capacity achieving mimo noma iterative lmmse detection"):
  with members:
    - "near gaussian multiple access channel capacity detection and decoding"
    - "rigorous dynamics of expectation propagation based signal recovery from unitarily invariant measurements"
    - "hybrid approximate message passing"
    - "gaussian message passing iterative detection for mimo noma systems with massive access"
    - "a general mimo framework for noma downlink and uplink transmission based on signal alignment"
    - "scaling up mimo opportunities and challenges with very large arrays"
    - "achievable rates of mimo systems with linear precoding and iterative lmmse detection"
    - "hybrid approximate message passing"

Connected through hyperedge HE-2 (induced by source paper "capacity achieving iterative lmmse detection for mimo noma systems"):
  with members:
    - "the application of mimo to non orthogonal multiple access"
    - "a low complexity gaussian message passing iterative detector for massive mu mimo systems"
    - "uplink non orthogonal multiple access for 5g wireless networks"
    - "a semiblind two way training method for discriminatory channel estimation in mimo systems"
    - "on the performance of non orthogonal multiple access in 5g systems with randomly deployed users"
    - "scaling up mimo opportunities and challenges with very large arrays"
    - "energy and spectral efficiency of very large multiuser mimo systems"
    - "achievable rates of mimo systems with linear precoding and iterative lmmse detection"

Connected through hyperedge HE-3 (induced by source paper "gaussian message passing iterative detection for mimo noma systems with massive access"):
  with members:
    - "convergence analysis and assurance for gaussian message passing iterative detector in massive mu mimo systems"
    - "capacity achieving iterative lmmse detection for mimo noma systems"
    - "on the performance of non orthogonal multiple access in 5g systems with randomly deployed users"
    - "scaling up mimo opportunities and challenges with very large arrays"
    - "achievable rates of mimo systems with linear precoding and iterative lmmse detection"

Connected through hyperedge HE-4 (induced by source paper "convergence and density evolution of a low complexity mimo detector based on forward backward recursion over a ring"):
  with members:
    - "belief propagation based decoding of large non orthogonal stbcs"
    - "mimo decoding based on stochastic reconstruction from multiple projections"
    - "gaussian belief propagation based multiuser detection"

Connected through hyperedge HE-5 (induced by source paper "a low complexity gaussian message passing iterative detector for massive mu mimo systems"):
  with members:
    - "scaling up mimo opportunities and challenges with very large arrays"
    - "energy and spectral efficiency of very large multiuser mimo systems"

Connected through hyperedge HE-6 (induced by source paper "low complexity mimo detection based on belief propagation over pair wise graphs"):
  with members:
    - "mimo decoding based on stochastic reconstruction from multiple projections"
    - "gaussian belief propagation based multiuser detection"

Connected through hyperedge HE-7 (induced by source paper "belief propagation for weighted b matchings on arbitrary graphs and its relation to linear programs with integer solutions"):
  with members:
    - "map estimation linear programming and belief propagation with convex free energies"
    - "map estimation message passing and perfect graphs"
    - "a new class of upper bounds on the log partition function"
    - "message passing for maximum weight independent set"
    - "max product for maximum weight matching convergence correctness and lp duality"
    - "equivalence of lp relaxation and max product for weighted matching in general graphs"
    - "convergence of the min sum message passing algorithm for quadratic optimization"
    - "on the solution space geometry of random constraint satisfaction problems"

Connected through hyperedge HE-8 (induced by source paper "low complexity detection in large dimension mimo isi channels using graphical models"):
  with members:
    - "loopy belief propagation for approximate inference an empirical study"
    - "mimo detection for high order qam based on a gaussian tree approximation"
    - "a hybrid rts bp algorithm for improved detection of large mimo m qam signals"
    - "belief propagation based decoding of large non orthogonal stbcs"
    - "high rate space time coded large mimo systems low complexity detection and channel estimation"
    - "sufficient conditions for convergence of the sum product algorithm"
    - "improved message passing for inference in densely connected systems"

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)