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: "a lattice based mimo broadcast precoder for multi stream transmission"
  Abstract: Precoding with block diagonalization is an attractive scheme for approaching sum capacity in multiuser multiple input multiple output (MIMO) broadcast channels. This method requires either global channel state information at every receiver or an additional training phase, which demands additional system planning. In this paper we propose a lattice based multi-user precoder that uses block diagonalization combined with pre-equalization and perturbation for the multiuser MIMO broadcast channel. An achievable sum rate of the proposed scheme is derived and used to show that the proposed technique approaches the achievable sum rate of block diagonalization with water-filling but does not require the additional information at the receiver. Monte Carlo simulations with equal power allocation show that the proposed method provides better bit error rate and diversity performance than block diagonalization with a zero-forcing receiver. Additionally, the proposed method shows similar performance to the maximum likelihood receiver but with much lower receiver complexity.

Connected through hyperedge HE-1 (induced by source paper "filter and nested lattice code design for mimo fading channels with side information"):
  with members:
    - "dirty paper coding for fading channels with partial transmitter side information"
    - "on the achievable rate of the fading dirty paper channel with imperfect csit"
    - "writing on dirty paper with resizing and its application to quasi static fading broadcast channels"
    - "on the fading paper achievable region of the fading mimo broadcast channel"
    - "shannon meets wiener ii on mmse estimation in successive decoding schemes"

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)