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: "multipair two way half duplex relaying with massive arrays and imperfect csi"
  Abstract: We consider a two-way half-duplex relaying system where multiple pairs of single antenna users exchange information assisted by a multi-antenna relay. Taking into account the practical constraint of imperfect channel estimation, we study the achievable sum spectral efficiency of the amplify-and-forward (AF) and decode-and-forward (DF) protocols, assuming that the relay employs simple maximum ratio processing. We derive an exact closed-form expression for the sum spectral efficiency of the AF protocol and a large-scale approximation for the sum spectral efficiency of the DF protocol when the number of relay antennas, $M$, becomes sufficiently large. In addition, we study how the transmit power scales with $M$ to maintain a desired quality-of-service. In particular, our results show that by using a large number of relay antennas, the transmit powers of the user, relay, and pilot symbol can be scaled down proportionally to $1/M^\alpha$, $1/M^\beta$, and $1/M^\gamma$ for certain $\alpha$, $\beta$, and $\gamma$, respectively. This elegant power scaling law reveals a fundamental tradeoff between the transmit powers of the user/relay and pilot symbol. Finally, capitalizing on the new expressions for the sum spectral efficiency, novel power allocation schemes are designed to further improve the sum spectral efficiency.

Connected through hyperedge HE-1 (induced by source paper "large scale cloud radio access networks with practical constraints asymptotic analysis and its implications"):
  with members:
    - "performance analysis and scaling law of mrc mrt relaying with csi error in massive mimo systems"
    - "a stochastic geometry framework for analyzing pairwise cooperative cellular networks"
    - "spectral efficiency scaling laws in dense random wireless networks with multiple receive antennas"
    - "what will 5g be"
    - "scaling up mimo opportunities and challenges with very large arrays"
    - "asymptotic rate analysis of downlink multi user systems with co located and distributed antennas"
    - "downlink rate distribution in heterogeneous cellular networks under generalized cell selection"
    - "fundamentals of inter cell overhead signaling in heterogeneous cellular networks"

Connected through hyperedge HE-2 (induced by source paper "multi way massive mimo with maximum ratio processing and imperfect csi"):
  with members:
    - "on the performance of zero forcing processing in multi way massive mimo relay networks"
    - "massive mimo with non ideal arbitrary arrays hardware scaling laws and circuit aware design"
    - "multipair full duplex relaying with massive arrays and linear processing"
    - "massive mimo with optimal power and training duration allocation"
    - "massive mimo for next generation wireless systems"
    - "scaling up mimo opportunities and challenges with very large arrays"
    - "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)