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: "is the low complexity mobile relay aided ffr das capable of outperforming the high complexity comp"
  Abstract: The coordinated multipoint transmission/reception aided collocated antenna system (CoMP-CAS) and the mobile relay assisted fractional frequency reuse distributed antenna system (MR-FFR-DAS) constitute a pair of virtual-MIMO-based technical options for achieving high spectral efficiency in interference-limited cellular networks. In practice, both techniques have their respective pros and cons, which are studied in this paper by evaluating the achievable cell-edge performance on the uplink of multicell systems. We show that, assuming the same antenna configuration in both networks, the maximum available cooperative spatial diversity (or the multiplexing gain) inherent in the MR-FFR-DAS is lower than that in the CoMP-CAS. However, when the cell-edge mobile stations (MSs) have a low transmission power, the lower complexity MR-FFR-DAS relying on the simple single-cell processing may outperform the CoMP-CAS by using the proposed soft-combining-based probabilistic data association (SC-PDA) receiver, despite the fact that the latter scheme is more complex and incurs a higher cooperation overhead. Furthermore, the benefits of the SC-PDA receiver may be enhanced by properly selecting the MRs' positions. Additionally, we show that the performance of the cell-edge MSs roaming near the angular direction halfway between two adjacent remote antennas (i.e., the “worst-case direction”) of the MR-FFR-DAS may be more significantly improved than that of the cell-edge MSs of other directions by using multiuser power control, which also improves the fairness among cell-edge MSs. Our simulation results show that, given a moderate MS transmit power, the proposed MR-FFR-DAS architecture employing the SC-PDA receiver is capable of achieving significantly better bit error rate (BER) and effective throughput across the entire cell-edge area, including even the worst-case direction and the cell-edge boundary, than the CoMP-CAS architecture.

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)