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: "massive mimo with multi antenna users when are additional user antennas beneficial"
  Abstract: We analyze the performance of massive MIMO systems with $N$-antenna users. The benefit is that $N$ streams can be multiplexed per user, at the price of increasing the channel estimation overhead linearly with $N$. Uplink and downlink spectral efficiency (SE) expressions are derived for any $N$, and these are achievable using estimated channels and per-user-basis MMSE-SIC detectors. Large-system approximations of the SEs are obtained. This analysis shows that MMSE-SIC has similar asymptotic SE as linear MMSE detectors, indicating that the SE increase from having multi-antenna users can be harvested using linear detectors. We generalize the power scaling laws for massive MIMO to handle arbitrary $N$, and show that one can reduce the multiplication of the pilot power and payload power as $\frac{1}{M}$ where $M$ is the number of BS antennas, and still notably increase the SE with $M$ before reaching a non-zero asymptotic limit. Simulations testify our analysis and show that the SE increases with $N$. We also note that the same improvement can be achieved by serving $N$ times more single-antenna users instead, thus the additional user antennas are particular beneficial for SE enhancement when there are few active users in the system.

Connected through hyperedge HE-1 (induced by source paper "massive mimo with multi antenna users under jointly correlated ricean fading"):
  with members:
    - "massive mimo with spatially correlated rician fading channels"
    - "energy and spectral efficiency of very large multiuser mimo systems"

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)