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: "a family of likelihood ascent search multiuser detectors an upper bound of bit error rate and a lower bound of asymptotic multiuser efficiency"
  Abstract: In this paper, the bit error performance of a family of likelihood ascent search (LAS) multiuser detectors is analyzed. An upper bound on the BER of any LAS detector is obtained by bounding the fixed point region with the worst initial detector. The concept of indecomposable errors developed by Verdu is applied to tighten the upper bound. In a special instance, the upper bound is reduced to that for all the local maximum likelihood detectors. The upper bound is comparable with that of the optimum detector obtained by Verdu. A lower bound on the asymptotic multiuser efficiency (AME) is then obtained. It is shown that there are nontrivial CDMA channels such that a LAS detector can achieve unit AME regardless of user number. The AME lower bound provides a means for further seeking a good set of spreading sequences and power distribution for spectral and power efficient CDMA.

Connected through hyperedge HE-1 (induced by source paper "massive mimo and waveform design for 5th generation wireless communication systems"):
  with members:
    - "achievable rates of fdd massive mimo systems with spatial channel correlation"
    - "filter bank multicarrier for massive mimo"
    - "pilot decontamination in cmt based massive mimo networks"
    - "massive mimo for next generation wireless systems"
    - "what will 5g be"
    - "blind pilot decontamination"
    - "modulation formats and waveforms for the physical layer of 5g wireless networks who will be the heir of ofdm"
    - "generalized design of low complexity block diagonalization type precoding algorithms for multiuser mimo systems"

Connected through hyperedge HE-2 (induced by source paper "quasi large sparse sequence cdma approach to single user bound by linearly complex las detectors"):
  with members:
    - "a family of likelihood ascent search multiuser detectors approach to single user performance via quasi large random sequence cdma"
    - "analysis of belief propagation for non linear problems the example of cdma or how to prove tanaka s formula"

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)