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: "achieving max min fairness for mu miso with partial csit a multicast assisted transmission"
  Abstract: We address the max-min fairness design problem for a MU-MISO system with partial Channel State Information (CSI) at the Base Station (BS), consisting of an imperfect channel estimate and statistical knowledge of the estimation error, and perfect CSI at the receivers. The objective is to maximize the minimum Average Rate (AR) among users subject to a transmit power constraint. An unconventional transmission scheme is adopted where the Base Station (BS) transmits a common message in addition to the conventional private messages. In situations where the CSIT is not accurate enough to perform interference nulling, individual rates are assisted by allocating parts of the common message to different users according to their needs. The AR problem is transformed into an augmented Average Weighted Mean Square Error (AWMSE) problem, solved using Alternating Optimization (AO). The benefits of incorporating the common message are demonstrated through simulations.

Connected through hyperedge HE-1 (induced by source paper "sum rate maximization for linearly precoded downlink multiuser miso systems with partial csit a rate splitting approach"):
  with members:
    - "miso networks with imperfect csit a topological rate splitting approach"
    - "robust transmission in downlink multiuser miso systems a rate splitting approach"
    - "a rate splitting strategy for massive mimo with imperfect csit"
    - "sum rate maximization for mu miso with partial csit using joint multicasting and broadcasting"
    - "rate analysis of two receiver miso broadcast channel with finite rate feedback a rate splitting approach"
    - "optimal multiuser transmit beamforming a difficult problem with a simple solution structure"
    - "ammse optimization for multiuser miso systems with imperfect csit and perfect csir"
    - "transmit designs for the mimo broadcast channel with statistical csi"

Connected through hyperedge HE-2 (induced by source paper "robust transmission in downlink multiuser miso systems a rate splitting approach"):
  with members:
    - "sum rate maximization for linearly precoded downlink multiuser miso systems with partial csit a rate splitting approach"
    - "a rate splitting approach to robust multiuser miso transmission"
    - "a rate splitting strategy for massive mimo with imperfect csit"
    - "sum rate maximization for mu miso with partial csit using joint multicasting and broadcasting"
    - "rate analysis of two receiver miso broadcast channel with finite rate feedback a rate splitting approach"
    - "aligned image sets under channel uncertainty settling a conjecture by lapidoth shamai and wigger on the collapse of degrees of freedom under finite precision csit"
    - "degrees of freedom of time correlated miso broadcast channel with delayed csit"
    - "linear transceiver design for a mimo interfering broadcast channel achieving max min fairness"

Connected through hyperedge HE-3 (induced by source paper "a rate splitting approach to robust multiuser miso transmission"):
  with members:
    - "a rate splitting strategy for massive mimo with imperfect csit"
    - "sum rate maximization for mu miso with partial csit using joint multicasting and broadcasting"
    - "rate analysis of two receiver miso broadcast channel with finite rate feedback a rate splitting approach"
    - "degrees of freedom of time correlated miso broadcast channel with delayed csit"
    - "linear transceiver design for a mimo interfering broadcast channel achieving max min fairness"
    - "robust linear precoder design for multi cell downlink transmission"
    - "multiuser mimo achievable rates with downlink training and channel state feedback"
    - "mimo broadcast channels with finite rate feedback"

Connected through hyperedge HE-4 (induced by source paper "rate analysis of two receiver miso broadcast channel with finite rate feedback a rate splitting approach"):
  with members:
    - "sum rate maximization for linearly precoded downlink multiuser miso systems with partial csit a rate splitting approach"
    - "sum rate maximization for mu miso with partial csit using joint multicasting and broadcasting"
    - "tomlinson harashima precoding for multiuser mimo systems with quantized csi feedback and user scheduling"
    - "aligned image sets under channel uncertainty settling a conjecture by lapidoth shamai and wigger on the collapse of degrees of freedom under finite precision csit"
    - "quantized csi based tomlinson harashima precoding in multiuser mimo systems"
    - "optimal dof region of the two user miso bc with general alternating csit"
    - "miso broadcast channel with imperfect and un matched csit in the frequency domain dof region and transmission strategies"
    - "degrees of freedom region of miso ofdma broadcast channel with imperfect csit"

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)