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: "precoding via approximate message passing with instantaneous signal constraints"
  Abstract: This paper proposes a low complexity precoding algorithm based on the recently proposed Generalized Least Square Error (GLSE) scheme with generic penalty and support. The algorithm iteratively constructs the transmit vector via Approximate Message Passing (AMP). Using the asymptotic decoupling property of GLSE precoders, we derive closed form fixed point equations to tune the parameters in the proposed algorithm for a general set of instantaneous signal constraints. The tuning strategy is then utilized to construct transmit vectors with restricted peak-to-average power ratios and to efficiently select a subset of transmit antennas. The numerical investigations show that the proposed algorithm tracks the large-system performance of GLSE precoders even for a moderate number of antennas.

Connected through hyperedge HE-1 (induced by source paper "joint user selection and precoding in multiuser mimo systems via group lasso"):
  with members:
    - "secure regularized zero forcing for multiuser mimome channels"
    - "on robustness of massive mimo systems against passive eavesdropping under antenna selection"
    - "glse precoders for massive mimo systems analysis and applications"
    - "theoretical bounds on map estimation in distributed sensing networks"
    - "nonlinear precoders for massive mimo systems with general constraints"
    - "asymptotics of nonlinear lse precoders with applications to transmit antenna selection"
    - "generalized approximate message passing for estimation with random linear mixing"
    - "consistency of the group lasso and multiple kernel learning"

Connected through hyperedge HE-2 (induced by source paper "papr limited precoding in massive mimo systems with reflect and transmit array antennas"):
  with members:
    - "glse precoders for massive mimo systems analysis and applications"
    - "scalable and energy efficient millimeter massive mimo architectures reflect array and transmit array antennas"
    - "nonlinear precoders for massive mimo systems with general constraints"
    - "asymptotics of nonlinear lse precoders with applications to transmit antenna selection"
    - "alternating minimization algorithms for hybrid precoding in millimeter wave mimo systems"
    - "hybrid beamforming for massive mimo a survey"
    - "spatially sparse precoding in millimeter wave mimo systems"

Connected through hyperedge HE-3 (induced by source paper "rls recovery with asymmetric penalty fundamental limits and algorithmic approaches"):
  with members:
    - "maximum a posteriori signal recovery with prior information applications to compressive sensing"
    - "the replica symmetric prediction for compressed sensing with gaussian matrices is exact"
    - "rsb decoupling property of map estimators"
    - "analysis of regularized ls reconstruction and random matrix ensembles in compressed sensing"
    - "statistical mechanics of map estimation general replica ansatz"
    - "support recovery with sparsely sampled free random matrices"
    - "asymptotic analysis of map estimation via the replica method and applications to compressed sensing"
    - "support driven reweighted ell_1 minimization"

Connected through hyperedge HE-4 (induced by source paper "optimal transmit antenna selection for massive mimo wiretap channels"):
  with members:
    - "asymptotics of nonlinear lse precoders with applications to transmit antenna selection"
    - "asymptotics of transmit antenna selection impact of multiple receive antennas"
    - "on secrecy performance of antenna selection aided mimo systems against eavesdropping"
    - "a survey on wireless security technical challenges recent advances and future trends"
    - "hybrid digital and analog beamforming design for large scale antenna arrays"
    - "secure massive mimo transmission with an active eavesdropper"
    - "physical layer security for massive mimo an overview on passive eavesdropping and active attacks"
    - "energy efficient antenna selection and power allocation for large scale multiple antenna systems with hybrid energy supply"

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)