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: "generalised sphere decoding for spatial modulation"
  Abstract: In this paper, Sphere Decoding (SD) algorithms for Spatial Modulation (SM) are developed to reduce the computational complexity of Maximum-Likelihood (ML) detectors. Two SDs specifically designed for SM are proposed and analysed in terms of Bit Error Ratio (BER) and computational complexity. Using Monte Carlo simulations and mathematical analysis, it is shown that by carefully choosing the initial radius the proposed sphere decoder algorithms offer the same BER as ML detection, with a significant reduction in the computational complexity. A tight closed form expression for the BER performance of SM-SD is derived in the paper, along with an algorithm for choosing the initial radius which provides near to optimum performance. Also, it is shown that none of the proposed SDs are always superior to the others, but the best SD to use depends on the target spectral efficiency. The computational complexity trade-off offered by the proposed solutions is studied via analysis and simulation, and is shown to validate our findings. Finally, the performance of SM-SDs are compared to Spatial Multiplexing (SMX) applying ML decoder and applying SD. It is shown that for the same spectral efficiency, SM-SD offers up to 84% reduction in complexity compared to SMX-SD, with up to 1 dB better BER performance than SMX-ML decoder.

Connected through hyperedge HE-1 (induced by source paper "a survey on spatial modulation in emerging wireless systems research progresses and applications"):
  with members:
    - "spatial modulation assisted multi antenna non orthogonal multiple access"
    - "adaptive spatial modulation based visible light communications ser analysis and optimization"
    - "two high performance schemes of transmit antenna selection for secure spatial modulation"
    - "receive spatial modulation for massive mimo systems"
    - "polarization shift keying polarsk system scheme and performance analysis"
    - "space time channel modulation"
    - "on the achievable spectral efficiency of spatial modulation aided downlink non orthogonal multiple access"
    - "spectral efficient analog precoding for generalized spatial modulation aided mmwave mimo"

Connected through hyperedge HE-2 (induced by source paper "double sparsity learning based channel and signal estimation in massive mimo with generalized spatial modulation"):
  with members:
    - "bilinear recovery using adaptive vector amp"
    - "super resolution blind channel and signal estimation for massive mimo with arbitrary array geometry"
    - "complete dictionary recovery over the sphere i overview and the geometric picture"
    - "bayes optimal joint channel and data estimation for massive mimo with low precision adcs"
    - "parametric bilinear generalized approximate message passing"
    - "generalized spatial modulation in large scale multiuser mimo systems"
    - "bilinear generalized approximate message passing part i derivation"
    - "optimal design of energy efficient multi user mimo systems is massive mimo the answer"

Connected through hyperedge HE-3 (induced by source paper "on the secrecy rate of spatial modulation based indoor visible light communications"):
  with members:
    - "adaptive spatial modulation for visible light communications with an arbitrary number of transmitters"
    - "adaptive spatial modulation based visible light communications ser analysis and optimization"
    - "physical layer security for indoor visible light communications secrecy capacity analysis"
    - "what will 5g be"
    - "on the capacity of free space optical intensity channels"

Connected through hyperedge HE-4 (induced by source paper "optimum low complexity decoder for spatial modulation"):
  with members:
    - "index modulation techniques for 5g wireless networks"
    - "solutions to integrals involving the marcum q function and applications"
    - "what will 5g be"

Connected through hyperedge HE-5 (induced by source paper "spatial coded modulation"):
  with members:
    - "generalized spatial modulation in large scale multiuser mimo systems"
    - "what will 5g be"

Connected through hyperedge HE-6 (induced by source paper "downlink macro diversity precoding aided spatial modulation"):
  with members:
    - "new signal designs for enhanced spatial modulation"
    - "index modulation techniques for 5g wireless networks"
    - "5g wireless backhaul networks challenges and research advances"
    - "diversity of mimo linear precoding"
    - "on the achievable improvement by the linear minimum mean square error detector"

Connected through hyperedge HE-7 (induced by source paper "complex quadrature spatial modulation"):
  with members:
    - "index modulation techniques for 5g wireless networks"

Connected through hyperedge HE-8 (induced by source paper "compressive sensing based multiuser detector for the large scale sm mimo uplink"):
  with members:
    - "scaling up mimo opportunities and challenges with very large arrays"
    - "practical implementation of spatial modulation"
    - "structured compressed sensing from theory to applications"
    - "subspace pursuit for compressive sensing signal reconstruction"

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)