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: "low complexity structured precoding for spatially correlated mimo channels"
  Abstract: The focus of this paper is on spatial precoding in correlated multi-antenna channels, where the number of independent data-streams is adapted to trade-off the data- rate with the transmitter complexity. Towards the goal of a low-complexity implementation, a structured precoder is proposed, where the precoder matrix evolves fairly slowly at a rate comparable with the statistical evolution of the channel. Here, the eigenvectors of the precoder matrix correspond to the dominant eigenvectors of the transmit covariance matrix, whereas the power allocation across the modes is fixe d, known at both the ends, and is of low-complexity. A particular case of the proposed scheme (semiunitary precoding), where the spatial modes are excited with equal power, is shown to be near-optimal in matched channels. A matched channel is one where the dominant eigenvalues of the transmit covariance matrix are well-conditioned and their number equals the number of independent data-streams, and the receive covariance matrix is also well-conditioned. In mismatched channels, where the above conditions are not met, it is shown that the loss in performance with semiunitary precoding when compared with a perfect channel information benchmark is substantial. This loss needs to be mitigated via limited feedback techniques that provide partial channel information to the transmitter. More importantly, we develop matching metrics that capture the degree of matching of a channel to the precoder structure continuously, and allow ordering two matrix channels in terms of their mutual information or error probability performance.

Connected through hyperedge HE-1 (induced by source paper "why does the kronecker model result in misleading capacity estimates"):
  with members:
    - "quantized multimode precoding in spatially correlated multiantenna channels"
    - "to code or not to code across time space time coding with feedback"
    - "optimal constellations for the low snr noncoherent mimo block rayleigh fading channel"
    - "on the outage capacity of correlated multiple path mimo channels"

Connected through hyperedge HE-2 (induced by source paper "quantized multimode precoding in spatially correlated multiantenna channels"):
  with members:
    - "why does the kronecker model result in misleading capacity estimates"

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)