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 effect of blockage objects in dense mimo swipt networks"
  Abstract: Simultaneous information and power transfer (SWIPT) is characterised by the ambiguous role of multi-user interference. In short, the beneficial effect of multi-user interference on RF energy harvesting is obtained at the price of a reduced link capacity, thus originating nontrivial trade-offs between the achievable information rate and the harvestable energy. Arguably, in indoor environments, this trade-off might be affected by the propagation loss due to blockage objects like walls. Hence, a couple of fundamental questions arise. How much must the network elements be densified to counteract the blockage attenuation? Is blockage always detrimental on the achievable rate-energy trade-off? In this paper, we analyse the performance of an indoor multiple-input multiple-output (MIMO) SWIPT-enabled network in the attempt to shed a light of those questions. The effects of the obstacles are examined with the help of a stochastic approach in which energy transmitters (also referred to as power heads) are located by using a Poisson Point Process and walls are generated through a Manhattan Poisson Line Process. The stochastic behaviour of the signal attenuation and the multi-user interference is studied to obtain the Joint Complementary Cumulative Distribution Function (J-CCDF) of information rate and harvested power. Theoretical results are validated through Monte Carlo simulations. Eventually, the rate-energy trade-off is presented as a function of the frequency of walls to emphasise the cross-dependences between the deployment of the network elements and the topology of the venue.

Connected through hyperedge HE-1 (induced by source paper "swipt based real time mobile computing systems a stochastic geometry perspective"):
  with members:
    - "a stochastic geometry analysis of energy harvesting in large scale wireless networks"
    - "system level modeling and optimization of the energy efficiency in cellular networks a stochastic geometry framework"
    - "computation rate maximization for wireless powered mobile edge computing with binary computation offloading"
    - "a survey on mobile edge computing the communication perspective"
    - "joint offloading and computing optimization in wireless powered mobile edge computing systems"
    - "a fundamental tradeoff between computation and communication in distributed computing"
    - "mimo cellular networks with simultaneous wireless information and power transfer"
    - "wireless networks with rf energy harvesting a contemporary survey"

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)