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: "link quality control mechanism for selective and opportunistic af relaying in cooperative arqs a mlsd perspective"
  Abstract: Incorporating relaying techniques into Automatic Repeat reQuest (ARQ) mechanisms gives a general impression of diversity and throughput enhancements. Allowing overhearing among multiple relays is also a known approach to increase the number of participating relays in ARQs. However, when opportunistic amplify-and-forward (AF) relaying is applied to cooperative ARQs, the system design becomes nontrivial and even involved. Based on outage analysis, the spatial and temporal diversities are first found sensitive to the received signal qualities of relays, and a link quality control mechanism is then developed to prescreen candidate relays in order to explore the diversity of cooperative ARQs with a selective and opportunistic AF (SOAF) relaying method. According to the analysis, the temporal and spatial diversities can be fully exploited if proper thresholds are set for each hop along the relaying routes. The SOAF relaying method is further examined from a packet delivery viewpoint. By the principle of the maximum likelihood sequence detection (MLSD), sufficient conditions on the link quality are established for the proposed SOAF-relaying-based ARQ scheme to attain its potential diversity order in the packet error rates (PERs) of MLSD. The conditions depend on the minimum codeword distance and the average signal-to-noise ratio (SNR). Furthermore, from a heuristic viewpoint, we also develop a threshold searching algorithm for the proposed SOAF relaying and link quality method to exploit both the diversity and the SNR gains in PER. The effectiveness of the proposed thresholding mechanism is verified via simulations with trellis codes.

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)