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: "sphere decoding complexity exponent for decoding full rate codes over the quasi static mimo channel"
  Abstract: In the setting of quasi-static multiple-input multiple-output (MIMO) channels, we consider the high signal-to-noise ratio (SNR) asymptotic complexity required by the sphere decoding (SD) algorithm for decoding a large class of full rate linear space-time codes. With SD complexity having random fluctuations induced by the random channel, noise and codeword realizations, the introduced SD complexity exponent manages to concisely describe the computational reserves required by the SD algorithm to achieve arbitrarily close to optimal decoding performance. Bounds and exact expressions for the SD complexity exponent are obtained for the decoding of large families of codes with arbitrary performance characteristics. For the particular example of decoding the recently introduced threaded cyclic division algebra (CDA) based codes -- the only currently known explicit designs that are uniformly optimal with respect to the diversity multiplexing tradeoff (DMT) -- the SD complexity exponent is shown to take a particularly concise form as a non-monotonic function of the multiplexing gain. To date, the SD complexity exponent also describes the minimum known complexity of any decoder that can provably achieve a gap to maximum likelihood (ML) performance which vanishes in the high SNR limit.

Connected through hyperedge HE-1 (induced by source paper "deterministic sampling decoding where sphere decoding meets lattice gaussian distribution"):
  with members:
    - "lattice gaussian sampling by markov chain monte carlo bounded distance decoding and trapdoor sampling"
    - "on the geometric ergodicity of metropolis hastings algorithms for lattice gaussian sampling"
    - "discrete gaussian sampling reduces to cvp and svp"
    - "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"
    - "massive mimo for next generation wireless systems"
    - "decoding by embedding correct decoding radius and dmt optimality"
    - "scaling up mimo opportunities and challenges with very large arrays"

Connected through hyperedge HE-2 (induced by source paper "lossless size reduction for integer least squares with application to sphere decoding"):
  with members:
    - "circular sphere decoding a low complexity detection for mimo systems with general two dimensional signal constellations"

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"
    - "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"
    - "on the limitations of the naive lattice decoding"

Connected through hyperedge HE-4 (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-5 (induced by source paper "an error event sensitive tradeoff between rate and coding gain in mimo mac"):
  with members:
    - "dmt optimality of lr aided linear decoders for a general class of channels lattice designs and system models"
    - "remarks on the criteria of constructing mimo mac dmt optimal codes"
    - "performance of mmse mimo receivers a large n analysis for correlated channels"
    - "on the decay of the determinants of multiuser mimo lattice codes"
    - "distributed space time block codes for the mimo multiple access channel"
    - "maximal orders in the design of dense space time lattice codes"
    - "diversity multiplexing tradeoff in selective fading multiple access mimo channels"
    - "optimal space time codes for the mimo amplify and forward cooperative channel"

Connected through hyperedge HE-6 (induced by source paper "performance complexity analysis for mac ml based decoding with user selection"):
  with members:
    - "achieving a vanishing snr gap to exact lattice decoding at a subexponential complexity"
    - "minimizing the complexity of fast sphere decoding of stbcs"
    - "dmt optimality of lr aided linear decoders for a general class of channels lattice designs and system models"
    - "lr aided mmse lattice decoding is dmt optimal for all approximately universal codes"
    - "approximately universal optimality over several dynamic and non dynamic cooperative diversity schemes for wireless networks"

Connected through hyperedge HE-7 (induced by source paper "achieving a vanishing snr gap to exact lattice decoding at a subexponential complexity"):
  with members:
    - "on the proximity factors of lattice reduction aided decoding"
    - "efficient soft input soft output tree detection via an improved path metric"
    - "decoding by sampling a randomized lattice algorithm for bounded distance decoding"
    - "faster recursions in sphere decoding"
    - "finite snr diversity multiplexing tradeoff via asymptotic analysis of large mimo systems"
    - "mimo detection for high order qam based on a gaussian tree approximation"
    - "dmt optimality of lr aided linear decoders for a general class of channels lattice designs and system models"
    - "soft input soft output single tree search sphere decoding"

Connected through hyperedge HE-8 (induced by source paper "time varying space only codes for coded mimo"):
  with members:
    - "precoding for outage probability minimization on block fading channels"
    - "space time coding techniques with bit interleaved coded modulations for mimo block fading channels"
    - "a tight lower bound to the outage probability of discrete input block fading 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)