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 "low complexity detection in large dimension mimo isi channels using graphical models"):
  Abstract: In this paper, we deal with low-complexity near-optimal detection/equalization in large-dimension multiple-input multiple-output inter-symbol interference (MIMO-ISI) channels using message passing on graphical models. A key contribution in the paper is the demonstration that near-optimal performance in MIMO-ISI channels with large dimensions can be achieved at low complexities through simple yet effective simplifications/approximations, although the graphical models that represent MIMO-ISI channels are fully/densely connected (loopy graphs). These include 1) use of Markov random field (MRF)-based graphical model with pairwise interaction, in conjunction with message damping, and 2) use of factor graph (FG)-based graphical model with Gaussian approximation of interference (GAI). The per-symbol complexities are O(K2nt2) and O(Knt) for the MRF and the FG with GAI approaches, respectively, where K and nt denote the number of channel uses per frame, and number of transmit antennas, respectively. These low-complexities are quite attractive for large dimensions, i.e., for large Knt. From a performance perspective, these algorithms are even more interesting in large-dimensions since they achieve increasingly closer to optimum detection performance for increasing Knt. Also, we show that these message passing algorithms can be used in an iterative manner with local neighborhood search algorithms to improve the reliability/performance of M-QAM symbol detection.

Includes members:
  Member "loopy belief propagation for approximate inference an empirical study":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "analyzing differentiable fuzzy logic operators")
  Member "mimo detection for high order qam based on a gaussian tree approximation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "multi user detection based on expectation propagation for the non coherent simo multiple access channel")
  Member "a hybrid rts bp algorithm for improved detection of large mimo m qam signals":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "fifty years of mimo detection the road to large scale mimos")
  Member "belief propagation based decoding of large non orthogonal stbcs":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "convergence and density evolution of a low complexity mimo detector based on forward backward recursion over a ring")
  Member "high rate space time coded large mimo systems low complexity detection and channel estimation":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "fifty years of mimo detection the road to large scale mimos")
  Member "sufficient conditions for convergence of the sum product algorithm":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "factorized graph representations for semi supervised learning from sparse data")
  Member "improved message passing for inference in densely connected systems":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "capacity optimality of amp in coded systems")
  Member "belief propagation based multi user detection":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "capacity achieving mimo noma iterative lmmse detection")

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)