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: "base station cooperation with feedback optimization a large system analysis"
  Abstract: In this paper, we study feedback optimization problems that maximize the users' signal to interference plus noise ratio (SINR) in a two-cell MIMO broadcast channel. Assuming the users learn their direct and interfering channels perfectly, they can feed back this information to the base stations (BSs) over the uplink channels. The BSs then use the channel information to design their transmission scheme. Two types of feedback are considered: analog and digital. In the analog feedback case, the users send their unquantized and uncoded CSI over the uplink channels. In this context, given a user's fixed transmit power, we investigate how he/she should optimally allocate it to feed back the direct and interfering (or cross) CSI for two types of base station cooperation schemes, namely, Multi-Cell Processing (MCP) and Coordinated Beamforming (CBf). In the digital feedback case, the direct and cross link channel vectors of each user are quantized separately, each using RVQ, with different size codebooks. The users then send the index of the quantization vector in the corresponding codebook to the BSs. Similar to the feedback optimization problem in the analog feedback, we investigate the optimal bit partitioning for the direct and interfering link for both types of cooperation. We focus on regularized channel inversion precoding structures and perform our analysis in the large system limit in which the number of users per cell ($K$) and the number of antennas per BS ($N$) tend to infinity with their ratio $\beta=\frac{K}{N}$ held fixed.

Connected through hyperedge HE-1 (induced by source paper "provisioning energy efficiency and qos for multi carrier comp with limited feedback"):
  with members:
    - "performance analysis and optimization for interference alignment over mimo interference channels with limited feedback"
    - "what will 5g be"
    - "interference coordination random clustering and adaptive limited feedback"
    - "group sparse beamforming for green cloud ran"
    - "five disruptive technology directions for 5g"
    - "scaling up mimo opportunities and challenges with very large arrays"
    - "fundamental limits of cooperation"
    - "downlink sdma with limited feedback in interference limited wireless networks"

Connected through hyperedge HE-2 (induced by source paper "coordinated regularized zero forcing precoding for multicell miso systems with limited feedback"):
  with members:
    - "linear precoding based on polynomial expansion large scale multi cell mimo systems"
    - "large system analysis of cooperative multi cell downlink transmission via regularized channel inversion with imperfect csit"
    - "optimal power allocation and user loading for multiuser miso channels with regularized channel inversion"
    - "large system analysis of linear precoding in correlated miso broadcast channels under limited feedback"
    - "adaptive limited feedback for sum rate maximizing beamforming in cooperative multicell systems"
    - "adaptive spatial intercell interference cancellation in multicell wireless networks"
    - "mimo broadcast channels with finite rate feedback"
    - "on the user selection for mimo broadcast channels"

Connected through hyperedge HE-3 (induced by source paper "optimal power allocation and user loading for multiuser miso channels with regularized channel inversion"):
  with members:
    - "network mimo with linear zero forcing beamforming large system analysis impact of channel estimation and reduced complexity scheduling"
    - "performance analysis of optimum zero forcing beamforming with greedy user selection"
    - "large system analysis of linear precoding in correlated miso broadcast channels under limited feedback"
    - "multi mode transmission for the mimo broadcast channel with imperfect channel state information"
    - "achievable throughput of multi mode multiuser mimo with imperfect csi constraints"
    - "estimation diversity and energy efficiency in distributed sensing"

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)