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: "polar codes and polar lattices for independent fading channels"
  Abstract: In this paper, we design polar codes and polar lattices for i.i.d. fading channels when the channel state information is only available to the receiver. For the binary input case, we propose a new design of polar codes through single-stage polarization to achieve the ergodic capacity. For the non-binary input case, polar codes are further extended to polar lattices to achieve the egodic Poltyrev capacity, i.e., the capacity without power limit. When the power constraint is taken into consideration, we show that polar lattices with lattice Gaussian shaping achieve the egodic capacity of fading channels. The coding and shaping are both explicit, and the overall complexity of encoding and decoding is $O(N \log^2 N)$.

Connected through hyperedge HE-1 (induced by source paper "markov chain monte carlo methods for lattice gaussian sampling convergence analysis and enhancement"):
  with members:
    - "boosted kz and lll algorithms"
    - "lattice gaussian sampling by markov chain monte carlo bounded distance decoding and trapdoor sampling"
    - "sensitivity gains by mismatched probabilistic shaping for optical communication systems"
    - "on probabilistic shaping of quadrature amplitude modulation for the nonlinear fiber channel"
    - "achieving secrecy capacity of the gaussian wiretap channel with polar lattices"
    - "fifty years of mimo detection the road to large scale mimos"
    - "on the geometric ergodicity of metropolis hastings algorithms for lattice gaussian sampling"
    - "optimized markov chain monte carlo for signal detection in mimo systems an analysis of the stationary distribution and mixing time"

Connected through hyperedge HE-2 (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"
    - "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"
    - "decoding by sampling part ii derandomization and soft output decoding"

Connected through hyperedge HE-3 (induced by source paper "on the separability of ergodic fading mimo channels a lattice coding approach"):
  with members:
    - "lattice coding and decoding for multiple antenna ergodic fading channels"
    - "almost universal codes achieving ergodic mimo capacity within a constant gap"
    - "precoded integer forcing universally achieves the mimo capacity to within a constant gap"
    - "dispersion analysis of infinite constellations in ergodic fading channels"
    - "integer forcing linear receivers"
    - "compute and forward harnessing interference through structured codes"

Connected through hyperedge HE-4 (induced by source paper "polar codes over fading channels with power and delay constraints"):
  with members:
    - "polar coding for block fading channels"
    - "an interleaver design for polar codes over slow fading channels"
    - "ber performance of polar coded ofdm in multipath fading"
    - "a comparative study of polar code constructions for the awgn channel"
    - "optimum power control at finite blocklength"
    - "polar coding for fading channels binary and exponential channel cases"
    - "list decoding of polar codes"
    - "how to construct polar codes"

Connected through hyperedge HE-5 (induced by source paper "lattice coding and decoding for multiple antenna ergodic fading channels"):
  with members:
    - "almost universal codes achieving ergodic mimo capacity within a constant gap"
    - "precoded integer forcing universally achieves the mimo capacity to within a constant gap"
    - "dispersion analysis of infinite constellations in ergodic fading channels"
    - "the approximate sum capacity of the symmetric gaussian k user interference channel"
    - "lattice codes for the gaussian relay channel decode and forward and compress and forward"
    - "integer forcing linear receivers"
    - "compute and forward harnessing interference through structured codes"

Connected through hyperedge HE-6 (induced by source paper "multilevel code construction for compound fading channels"):
  with members:
    - "algebraic lattice codes achieve the capacity of the compound block fading channel"
    - "almost universal codes achieving ergodic mimo capacity within a constant gap"
    - "precoded integer forcing universally achieves the mimo capacity to within a constant gap"
    - "polar coding for fading channels binary and exponential channel cases"
    - "universal polar codes"
    - "spatially coupled ensembles universally achieve capacity under belief propagation"

Connected through hyperedge HE-7 (induced by source paper "algebraic lattice codes for linear fading channels"):
  with members:
    - "lattice coding and decoding for multiple antenna ergodic fading channels"
    - "almost universal codes achieving ergodic mimo capacity within a constant gap"
    - "division algebra codes achieve mimo block fading channel capacity within a constant gap"
    - "precoded integer forcing universally achieves the mimo capacity to within a constant gap"

Connected through hyperedge HE-8 (induced by source paper "polar coding for block fading channels"):
  with members:
    - "polar coding for fading channels binary and exponential channel cases"

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)