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: "on the performance of optimized dense device to device wireless networks"
  Abstract: We consider a D2D wireless network where $n$ users are densely deployed in a squared planar region and communicate with each other without the help of a wired infrastructure. For this network, we examine the 3-phase hierarchical cooperation (HC) scheme and the 2-phase improved HC scheme based on the concept of {\em network multiple access}. Exploiting recent results on the optimality of treating interference as noise in Gaussian interference channels, we optimize the achievable average per-link rate and not just its scaling law. In addition, we provide further improvements on both the previously proposed hierarchical cooperation schemes by a more efficient use of TDMA and spatial reuse. Thanks to our explicit achievable rate expressions, we can compare HC scheme with multihop routing (MR), where the latter can be regarded as the current practice of D2D wireless networks. Our results show that the improved and optimized HC schemes yield very significant rate gains over MR in realistic conditions of channel propagation exponents, signal to noise ratio, and number of users. This sheds light on the long-standing question about the real advantage of HC scheme over MR beyond the well-known scaling laws analysis. In contrast, we also show that our rate optimization is non-trivial, since when HC is applied with off-the-shelf choice of the system parameters, no significant rate gain with respect to MR is achieved. We also show that for large pathloss exponent the sum rate is a nearly linear function of the number of users $n$ in the range of networks of practical size. This also sheds light on a long-standing dispute on the effective achievability of linear sum rate scaling with HC. Finally, we notice that the achievable sum rate for large $\alpha$ is much larger than for small $\alpha$. This suggests that HC scheme may be a very effective approach for networks operating at mm-waves.

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)