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: "reduced complexity sphere decoding for square qam via a new lattice representation"
  Abstract: Sphere decoding (SD) is a low complexity maximum likelihood (ML) detection algorithm, which has been adapted for different linear channels in digital communications. The complexity of the SD has been shown to be exponential in some cases, and polynomial in others and under certain assumptions. The sphere radius and the number of nodes visited throughout the tree traversal search are the decisive factors for the complexity of the algorithm. The radius problem has been addressed and treated widely in the literature. In this paper, we propose a new structure for SD, which drastically reduces the overall complexity. The complexity is measured in terms of the floating point operations per second (FLOPS) and the number of nodes visited throughout the algorithm tree search. This reduction in the complexity is due to the ability of decoding the real and imaginary parts of each jointly detected symbol independently of each other, making use of the new lattice representation. We further show by simulations that the new approach achieves 80% reduction in the overall complexity compared to the conventional SD for a 2x2 system, and almost 50% reduction for the 4x4 and 6x6 cases, thus relaxing the requirements for hardware implementation.

Connected through hyperedge HE-1 (induced by source paper "full diversity precoding design of bit interleaved coded multiple beamforming with orthogonal frequency division multiplexing"):
  with members:
    - "diversity analysis of bit interleaved coded multiple beamforming with orthogonal frequency division multiplexing"
    - "multiple beamforming with perfect coding"
    - "bit interleaved coded multiple beamforming with perfect coding"
    - "constellation precoded beamforming"
    - "constellation precoded multiple beamforming"
    - "bit interleaved coded multiple beamforming with constellation precoding"
    - "diversity analysis of bit interleaved coded multiple beamforming"

Connected through hyperedge HE-2 (induced by source paper "multiple beamforming with perfect coding"):
  with members:
    - "reduced complexity decoding for bit interleaved coded multiple beamforming with constellation precoding"
    - "constellation precoded beamforming"
    - "constellation precoded multiple beamforming"
    - "reduced complexity sphere decoding"
    - "bit interleaved coded multiple beamforming with constellation precoding"
    - "diversity analysis of bit interleaved coded multiple beamforming"
    - "fast maximum likelihood decoding of the golden code"
    - "perfect space time codes with minimum and non minimum delay for any number of antennas"

Connected through hyperedge HE-3 (induced by source paper "reduced complexity decoding for bit interleaved coded multiple beamforming with constellation precoding"):
  with members:
    - "reduced complexity sphere decoding"
    - "bit interleaved coded multiple beamforming with constellation precoding"
    - "diversity analysis of bit interleaved coded multiple beamforming"

Connected through hyperedge HE-4 (induced by source paper "golden coded multiple beamforming"):
  with members:
    - "constellation precoded beamforming"
    - "fast maximum likelihood decoding of the golden code"
    - "perfect space time codes with minimum and non minimum delay for any number of antennas"

Connected through hyperedge HE-5 (induced by source paper "constellation precoded multiple beamforming"):
  with members:
    - "augmented lattice reduction for mimo decoding"
    - "constellation precoded beamforming"
    - "diversity analysis of bit interleaved coded multiple beamforming"
    - "a near maximum likelihood decoding algorithm for mimo systems based on semi definite programming"

Connected through hyperedge HE-6 (induced by source paper "high rate space time coded large mimo systems low complexity detection and channel estimation"):
  with members:
    - "asymptotic analysis of the performance of las algorithm for large mimo detection"
    - "large mimo detection a low complexity detector at high spectral efficiencies"
    - "performance analysis of iterative channel estimation and multiuser detection in multipath ds cdma channels"

Connected through hyperedge HE-7 (induced by source paper "reduced complexity sphere decoding"):
  with members:
    - "reduced complexity decoding for bit interleaved coded multiple beamforming with constellation precoding"
    - "constellation precoded multiple beamforming"
    - "bit interleaved coded multiple beamforming with constellation precoding"

Connected through hyperedge HE-8 (induced by source paper "asymptotic analysis of the performance of las algorithm for large mimo detection"):
  with members:
    - "belief propagation based decoding of large non orthogonal stbcs"
    - "low complexity near ml decoding of large non orthogonal stbcs using reactive tabu search"
    - "high rate space time coded large mimo systems low complexity detection and channel estimation"
    - "large mimo detection a low complexity detector at high spectral efficiencies"
    - "belief propagation based multi user detection"

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)