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: "the papr problem in ofdm transmission new directions for a long lasting problem"
  Abstract: Energy efficiency matters in future mobile communications networks. The key driving factor is the growing energy cost of network operations that can make up as much as 50% of the total operational cost today [1]. In the context of green information and communication technology (ICT), this has led to many global initiatives such as the Green Touch consortium.

Connected through hyperedge HE-1 (induced by source paper "bound on peak to average power ratio with moment and reduction method"):
  with members:
    - "moment based bound on peak to average power ratio and reduction with unitary matrix"
    - "stochastic gradient descent for non smooth optimization convergence results and optimal averaging schemes"

Connected through hyperedge HE-2 (induced by source paper "application of the method of conditional expectations for reduction of papr and cubic metric of ofdm signals"):
  with members:
    - "on the properties of cubic metric for ofdm signals"

Connected through hyperedge HE-3 (induced by source paper "a generic complementary sequence encoder"):
  with members:
    - "novel 16 qam and 64 qam near complementary sequences with low pmepr in ofdm systems"

Connected through hyperedge HE-4 (induced by source paper "capacity and degree of freedom of ofdm channels with amplitude constraint"):
  with members:
    - "capacity bounds for discrete time amplitude constrained additive white gaussian noise channels"
    - "on the peak to average power ratio reduction problem for orthogonal transmission schemes"

Connected through hyperedge HE-5 (induced by source paper "multicarrier papr reduction by iteratively shifting and concentrating the probability measure"):
  with members:
    - "5gnow challenging the lte design paradigms of orthogonality and synchronicity"
    - "on the concentration of the crest factor for ofdm signals"

Connected through hyperedge HE-6 (induced by source paper "overshooting and l 1 norms of a class of nyquist filters"):
  with members:
    - "sparse signal processing concepts for efficient 5g system design"

Connected through hyperedge HE-7 (induced by source paper "sparse signal processing concepts for efficient 5g system design"):
  with members:
    - "self calibration and biconvex compressive sensing"
    - "robust iterative interference alignment for cellular networks with limited feedback"
    - "characterization of coded random access with compressive sensing based multi user detection"
    - "the achievable performance of convex demixing"
    - "a stability result for sparse convolutions"
    - "fundamentals of throughput maximization with random arrivals for m2m communications"
    - "five disruptive technology directions for 5g"
    - "simultaneously structured models with application to sparse and low rank matrices"

Connected through hyperedge HE-8 (induced by source paper "system approximations and generalized measurements in modern sampling theory"):
  with members:
    - "signal and system approximation from general measurements"
    - "phase retrieval via structured modulations in paley wiener spaces"
    - "phaseless signal recovery in infinite dimensional spaces using structured modulations"
    - "phase retrieval from low rate samples"
    - "phaselift exact and stable signal recovery from magnitude measurements via convex programming"
    - "phase retrieval via matrix completion"
    - "recovering signals from lowpass data"
    - "beyond bandlimited sampling nonlinearities smoothness and sparsity"

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)