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 scalable limited feedback design for network mimo using per cell product codebook"
  Abstract: In network MIMO systems, channel state information is required at the transmitter side to multiplex users in the spatial domain. Since perfect channel knowledge is difficult to obtain in practice, \emph{limited feedback} is a widely accepted solution. The {\em dynamic number of cooperating BSs} and {\em heterogeneous path loss effects} of network MIMO systems pose new challenges on limited feedback design. In this paper, we propose a scalable limited feedback design for network MIMO systems with multiple base stations, multiple users and multiple data streams for each user. We propose a {\em limited feedback framework using per-cell product codebooks}, along with a {\em low-complexity feedback indices selection algorithm}. We show that the proposed per-cell product codebook limited feedback design can asymptotically achieve the same performance as the joint-cell codebook approach. We also derive an asymptotic \emph{per-user throughput loss} due to limited feedback with per-cell product codebooks. Based on that, we show that when the number of per-user feedback-bits $B_{k}$ is $\mathcal{O}\big( Nn_{T}n_{R}\log_{2}(\rho g_{k}^{sum})\big)$, the system operates in the \emph{noise-limited} regime in which the per-user throughput is $\mathcal{O} \left( n_{R} \log_{2} \big( \frac{n_{R}\rho g_{k}^{sum}}{Nn_{T}} \big) \right)$. On the other hand, when the number of per-user feedback-bits $B_{k}$ does not scale with the \emph{system SNR} $\rho$, the system operates in the \emph{interference-limited} regime where the per-user throughput is $\mathcal{O}\left( \frac{n_{R}B_{k}}{(Nn_{T})^{2}} \right)$. Numerical results show that the proposed design is very flexible to accommodate dynamic number of cooperating BSs and achieves much better performance compared with other baselines (such as the Givens rotation approach).

Connected through hyperedge HE-1 (induced by source paper "robust regularized zf in cooperative broadcast channel under distributed csit"):
  with members:
    - "on the optimal fronthaul compression and decoding strategies for uplink cloud radio access networks"
    - "network mimo transmitters with no csi can still be very useful"
    - "regularized zf in cooperative broadcast channels under distributed csit a large system analysis"
    - "drone small cells in the clouds design deployment and performance analysis"
    - "linear precoding based on polynomial expansion reducing complexity in massive mimo"
    - "multihop backhaul compression for the uplink of cloud radio access networks"
    - "large system analysis of linear precoding in correlated miso broadcast channels under limited feedback"
    - "completely stale transmitter channel state information is still very useful"

Connected through hyperedge HE-2 (induced by source paper "optimal feedback rate sharing strategy in zero forcing mimo broadcast channels"):
  with members:
    - "an analytical framework for heterogeneous partial feedback design in heterogeneous multicell ofdma networks"
    - "random beamforming with heterogeneous users and selective feedback individual sum rate and individual scaling laws"
    - "multi user diversity vs accurate channel state information in mimo downlink channels"
    - "stochastic control of event driven feedback in multiantenna interference channels"
    - "mode switching for the multi antenna broadcast channel based on delay and channel quantization"
    - "adaptive limited feedback for sum rate maximizing beamforming in cooperative multicell systems"
    - "limited feedback based block diagonalization for the mimo broadcast channel"
    - "antenna combining for the mimo downlink channel"

Connected through hyperedge HE-3 (induced by source paper "interference alignment for partially connected mimo cellular networks"):
  with members:
    - "dynamic interference mitigation for generalized partially connected quasi static mimo interference channel"
    - "on feasibility of interference alignment in mimo interference networks"
    - "downlink interference alignment"
    - "on feasibility of interference alignment in mimo interference networks"
    - "approaching the capacity of wireless networks through distributed interference alignment"

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)