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: "high rate space time coded large mimo systems low complexity detection and channel estimation"
  Abstract: In this paper, we present a low-complexity algorithm for detection in high-rate, non-orthogonal space-time block coded (STBC) large-multiple-input multiple-output (MIMO) systems that achieve high spectral efficiencies of the order of tens of bps/Hz. We also present a training-based iterative detection/channel estimation scheme for such large STBC MIMO systems. Our simulation results show that excellent bit error rate and nearness-to-capacity performance are achieved by the proposed multistage likelihood ascent search (M-LAS) detector in conjunction with the proposed iterative detection/channel estimation scheme at low complexities. The fact that we could show such good results for large STBCs like 16×16 and 32×32 STBCs from Cyclic Division Algebras (CDA) operating at spectral efficiencies in excess of 20 bps/Hz (even after accounting for the overheads meant for pilot based training for channel estimation and turbo coding) establishes the effectiveness of the proposed detector and channel estimator. We decode perfect codes of large dimensions using the proposed detector. With the feasibility of such a low-complexity detection/channel estimation scheme, large-MIMO systems with tens of antennas operating at several tens of bps/Hz spectral efficiencies can become practical, enabling interesting high data rate wireless applications.

Connected through hyperedge HE-1 (induced by source paper "fifty years of mimo detection the road to large scale mimos"):
  with members:
    - "large scale mimo detection for 3gpp lte algorithms and fpga implementations"
    - "an esprit based approach for 2 d localization of incoherently distributed sources in massive mimo systems"
    - "massive mimo for next generation wireless systems"
    - "what will 5g be"
    - "approximate bayesian probabilistic data association aided iterative detection for mimo systems using arbitrary m ary modulation"
    - "channel hardening exploiting message passing chemp receiver in large scale mimo systems"
    - "five disruptive technology directions for 5g"
    - "scaling up mimo opportunities and challenges with very large arrays"

Connected through hyperedge HE-2 (induced by source paper "adaptive reduced rank receive processing based on minimum symbol error rate criterion for large scale multiple antenna systems"):
  with members:
    - "iterative detection and decoding algorithms for mimo systems in block fading channels using ldpc codes"
    - "robust adaptive beamforming using a low complexity shrinkage based mismatch estimation algorithm"
    - "massive mimo systems signal processing challenges and research trends"
    - "scaling up mimo opportunities and challenges with very large arrays"
    - "adaptive reduced rank lcmv beamforming algorithms based on joint iterative optimization of filters design and analysis"

Connected through hyperedge HE-3 (induced by source paper "generalised sphere decoding for spatial modulation"):
  with members:
    - "performance of spatial modulation using measured real world channels"
    - "practical implementation of spatial modulation"
    - "sphere decoding for spatial modulation systems with arbitrary nt"
    - "space shift keying ssk mimo with practical channel estimates"
    - "low complexity maximum likelihood detection in spatial modulation systems"
    - "massive mimo how many antennas do we need"

Connected through hyperedge HE-4 (induced by source paper "channel hardening exploiting message passing chemp receiver in large scale mimo systems"):
  with members:
    - "scaling up mimo opportunities and challenges with very large arrays"
    - "sumis near optimal soft in soft out mimo detection with low and fixed complexity"
    - "low complexity detection in large dimension mimo isi channels using graphical models"
    - "mimo detection for high order qam based on a gaussian tree approximation"

Connected through hyperedge HE-5 (induced by source paper "adaptive reduced rank equalization algorithms based on alternating optimization design techniques for multi antenna systems"):
  with members:
    - "adaptive alternating minimization algorithms"

Connected through hyperedge HE-6 (induced by source paper "ultra low complexity soft output detector for non binary ldpc coded large mimo systems"):
  with members:
    - "near capacity approaching for large mimo systems by non binary ldpc codes with mmse detection"
    - "massive mimo how many antennas do we need"
    - "mimo detection for high order qam based on a gaussian tree approximation"

Connected through hyperedge HE-7 (induced by source paper "low complexity detection in large dimension mimo isi channels using graphical models"):
  with members:
    - "loopy belief propagation for approximate inference an empirical study"
    - "mimo detection for high order qam based on a gaussian tree approximation"
    - "a hybrid rts bp algorithm for improved detection of large mimo m qam signals"
    - "belief propagation based decoding of large non orthogonal stbcs"
    - "sufficient conditions for convergence of the sum product algorithm"
    - "improved message passing for inference in densely connected systems"
    - "belief propagation based multi user detection"

Connected through hyperedge HE-8 (induced by source paper "a hybrid rts bp algorithm for improved detection of large mimo m qam signals"):
  with members:
    - "near optimal detection in mimo systems using gibbs sampling"
    - "low complexity near ml decoding of large non orthogonal stbcs using reactive tabu search"
    - "near ml signal detection in large dimension linear vector channels using reactive tabu search"

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)