human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "on low complexity lattice reduction algorithms for large scale mimo detection the blessing of sequential reduction"):
  Abstract: Lattice reduction is a popular preprocessing strategy in multiple-input multiple-output (MIMO) detection. In a quest for developing a low-complexity reduction algorithm for large-scale problems, this paper investigates a new framework called sequential reduction (SR), which aims to reduce the lengths of all basis vectors. The performance upper bounds of the strongest reduction in SR are given when the lattice dimension is no larger than 4. The proposed new framework enables the implementation of a hash-based low-complexity lattice reduction algorithm, which becomes especially tempting when applied to large-scale MIMO detection. Simulation results show that, compared to other reduction algorithms, the hash-based SR algorithm exhibits the lowest complexity while maintaining comparable error performance.

Includes members:
  Member "on the kz reduction":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "improved upper bounds on the hermite and kz constants")
  Member "boosted kz and lll algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "steepest gradient based orthogonal precoder for integer forcing mimo")
  Member "gfclll a greedy selection based approach for fixed complexity lll reduction":
    also connected through other hyperedges:
      (none)
  Member "on the geometric ergodicity of metropolis hastings algorithms for lattice gaussian sampling":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "deterministic sampling decoding where sphere decoding meets lattice gaussian distribution")
  Member "success probability of the babai estimators for box constrained integer linear models":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "an optimal condition of robust low rank matrices recovery")
  Member "scaling up mimo opportunities and challenges with very large arrays":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "downlink secrecy rate of one bit massive mimo system with active eavesdropping")
  Member "on the proximity factors of lattice reduction aided decoding":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "deterministic sampling decoding where sphere decoding meets lattice gaussian distribution")
  Member "decoding by sampling a randomized lattice algorithm for bounded distance decoding":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "deterministic sampling decoding where sphere decoding meets lattice gaussian distribution")

Question: Please tell me which class the source paper 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)