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 achievable rate of the fading dirty paper channel with imperfect csit"
  Abstract: The problem of dirty paper coding (DPC) over the (multi-antenna) fading dirty paper channel (FDPC) Y = H(X + S) + Z is considered when there is imperfect knowledge of the channel state information H at the transmitter (CSIT). The case of FDPC with positive definite (p.d.) input covariance matrix was studied by the authors in a recent paper, and here the more general case of positive semi-definite (p.s.d.) input covariance is dealt with. Towards this end, the choice of auxiliary random variable is modified. The algorithms for determination of inflation factor proposed in the p.d. case are then generalized to the case of p.s.d. input covariance. Subsequently, the largest DPC-achievable high-SNR (signal-to-noise ratio) scaling factor over the no-CSIT FDPC with p.s.d. input covariance matrix is derived. This scaling factor is seen to be a non-trivial generalization of the one achieved for the p.d. case. Next, in the limit of low SNR, it is proved that the choice of all-zero inflation factor (thus treating interference as noise) is optimal in the 'ratio' sense, regardless of the covariance matrix used. Further, in the p.d. covariance case, the inflation factor optimal at high SNR is obtained when the number of transmit antennas is greater than the number of receive antennas, with the other case having been already considered in the earlier paper. Finally, the problem of joint optimization of the input covariance matrix and the inflation factor is dealt with, and an iterative numerical algorithm is developed.

Connected through hyperedge HE-1 (induced by source paper "on the fast fading multiple antenna gaussian broadcast channel with confidential messages and partial csit"):
  with members:
    - "on secrecy rate analysis of mimo wiretap channels driven by finite alphabet input"
    - "cognitive radio with partial channel state information at the transmitter"
    - "secure communication in the low snr regime"
    - "discrete memoryless interference and broadcast channels with confidential messages secrecy rate regions"
    - "the secrecy capacity of the mimo wiretap channel"

Connected through hyperedge HE-2 (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"
    - "writing on dirty paper with resizing and its application to quasi static fading broadcast channels"
    - "a lattice based mimo broadcast precoder for multi stream transmission"
    - "on the fading paper achievable region of the fading mimo broadcast channel"
    - "shannon meets wiener ii on mmse estimation in successive decoding schemes"

Connected through hyperedge HE-3 (induced by source paper "cognitive radio with partial channel state information at the transmitter"):
  with members:
    - "dirty paper coding for the mimo cognitive radio 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"
    - "cognitive radio an information theoretic perspective"

Connected through hyperedge HE-4 (induced by source paper "a large system analysis of the imperfect csit gaussian broadcast channel with a dpc based transmission strategy"):
  with members:
    - "dirty paper coding for fading channels with partial transmitter side information"
    - "the degrees of freedom regions of mimo broadcast interference and cognitive radio channels with no csit"
    - "mimo broadcast channels with finite rate feedback"

Connected through hyperedge HE-5 (induced by source paper "dirty paper coding for the mimo cognitive radio channel with imperfect csit"):
  with members:
    - "dirty paper coding for fading channels with partial transmitter side information"
    - "on the capacity of a class of mimo cognitive radios"
    - "adaptive sum power iterative waterfilling for mimo cognitive radio channels"
    - "cognitive radio an information theoretic perspective"

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)