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: "bit error rate is convex at high snr"
  Abstract: Motivated by a wide-spread use of convex optimization techniques, convexity properties of bit error rate of the maximum likelihood detector operating in the AWGN channel are studied for arbitrary constellations and bit mappings, which may also include coding under maximum-likelihood decoding. Under this generic setting, the pairwise probability of error and bit error rate are shown to be convex functions of the SNR in the high SNR regime with explicitly-determined boundary. The bit error rate is also shown to be a convex function of the noise power in the low noise/high SNR regime.

Connected through hyperedge HE-1 (induced by source paper "on convexity of error rates in digital communications"):
  with members:
    - "error rates of capacity achieving codes are convex"
    - "error rates of the maximum likelihood detector for arbitrary constellations convex concave behavior and applications"
    - "on node density outage probability tradeoff in wireless networks"
    - "log concavity property of the error probability with application to local bounds for wireless communications"
    - "on optimum power allocation for the v blast"
    - "symbol error rates of maximum likelihood detector convex concave behavior and applications"

Connected through hyperedge HE-2 (induced by source paper "mimo interference alignment over correlated channels with imperfect csi"):
  with members:
    - "cooperative algorithms for mimo interference channels"
    - "on feasibility of interference alignment in mimo interference networks"
    - "on feasibility of interference alignment in mimo interference networks"
    - "the feasibility of interference alignment over measured mimo ofdm channels"
    - "on the achievability of interference alignment in the k user constant mimo interference channel"
    - "opportunistic interference alignment in mimo interference channels"
    - "approaching the capacity of wireless networks through distributed interference alignment"
    - "a layered lattice coding scheme for a class of three user gaussian interference 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)