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: "on the limitations of the naive lattice decoding"
  Abstract: In this paper, the inherent drawbacks of the naive lattice decoding for MIMO fading systems is investigated. We show that using the naive lattice decoding for MIMO systems has considerable deficiencies in terms of the rate-diversity trade-off. Unlike the case of maximum-likelihood decoding, in this case, even the perfect lattice space-time codes which have the non-vanishing determinant property can not achieve the optimal rate-diversity trade-off. Indeed, we show that in the case of naive lattice decoding, when we fix the underlying lattice, all the codes based on full-rate lattices have the same rate-diversity trade-off as V-BLAST. Also, we drive a lower bound on the symbol error probability of the naive lattice decoding for the fixed-rate MIMO systems (with equal numbers of receive and transmit antennas). This bound shows that asymptotically, the naive lattice decoding has an unbounded loss in terms of the required SNR, compared to the maximum likelihood decoding.

Connected through hyperedge HE-1 (induced by source paper "markov chain monte carlo methods for lattice gaussian sampling lattice reduction and decoding optimization"):
  with members:
    - "boosted kz and lll algorithms"
    - "polar codes and polar lattices for independent fading channels"
    - "scan order in gibbs sampling models in which it matters and bounds on how much"
    - "achieving secrecy capacity of the gaussian wiretap channel with polar lattices"
    - "optimized markov chain monte carlo for signal detection in mimo systems an analysis of the stationary distribution and mixing time"
    - "markov chain monte carlo algorithms for lattice gaussian sampling"
    - "semantically secure lattice codes for the gaussian wiretap channel"
    - "decoding by embedding correct decoding radius and dmt optimality"

Connected through hyperedge HE-2 (induced by source paper "closed form word error rate analysis for successive interference cancellation decoders"):
  with members:
    - "effects of some lattice reductions on the success probability of the zero forcing decoder"
    - "success probability of the babai estimators for box constrained integer linear models"
    - "effects of the lll reduction on the success probability of the babai point and on the complexity of sphere decoding"
    - "column reordering for box constrained integer least squares problems"
    - "lll reduction achieves the receive diversity in mimo decoding"

Connected through hyperedge HE-3 (induced by source paper "asymptotic analysis of random lattices in high dimensions"):
  with members:
    - "fifty years of mimo detection the road to large scale mimos"
    - "effects of the lll reduction on the success probability of the babai point and on the complexity of sphere decoding"
    - "sphere decoding complexity exponent for decoding full rate codes over the quasi static mimo channel"
    - "faster recursions in sphere decoding"
    - "finite snr diversity multiplexing tradeoff via asymptotic analysis of large mimo systems"
    - "asymptotic performance of linear receivers in mimo fading channels"

Connected through hyperedge HE-4 (induced by source paper "hardware architecture of complex k best mimo decoder"):
  with members:
    - "fixed point realization of iterative lr aided soft mimo decoding algorithm"
    - "an improved lr aided k best algorithm for mimo detection"
    - "dmt optimality of lr aided linear decoders for a general class of channels lattice designs and system models"

Connected through hyperedge HE-5 (induced by source paper "gfclll a greedy selection based approach for fixed complexity lll reduction"):
  with members:
    - "success probability of the babai estimators for box constrained integer linear models"
    - "effects of the lll reduction on the success probability of the babai point and on the complexity of sphere decoding"

Connected through hyperedge HE-6 (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-7 (induced by source paper "fixed point realization of iterative lr aided soft mimo decoding algorithm"):
  with members:
    - "an improved lr aided k best algorithm for mimo detection"
    - "dmt optimality of lr aided linear decoders for a general class of channels lattice designs and system models"

Connected through hyperedge HE-8 (induced by source paper "shifted inverse determinant sums and new bounds for the dmt of space time lattice codes"):
  with members:
    - "a new design criterion for spherically shaped division algebra based space time codes"
    - "inverse determinant sums and connections between fading channel information theory and algebra"
    - "an error probability approach to mimo wiretap channels"
    - "approximately universal codes over slow fading channels"

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)