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: "a symbol based estimation technique for inter vehicular communication performance optimization"
  Abstract: The aim of this paper is to enhance the quality of Orthogonal Frequency Division Multiplexing OFDM estimation in dedicated vehicular communication transmission V2X networks. Wireless Access in Vehicular Environment WAVE as also known IEEE 802.11p represents the standard for these networks. Developing a reliable inter-vehicular V2X communication has to focus on optimizing its real performances. In this work, we studied the fact that WAVE transmission uses the channel characteristics designed for indoor and stationary communication terminals in IEEE 802.11a. In this paper, we propose an approach to overcome this mobility problem of terminal communication. The considered solution consists in using pilot estimation technique to reduce the high bit error rate. First, we highlight the impact of rearranging the pilot symbol positions on the quality of transmission QoT. Second, we try to overcome one of the PHY layer estimation constraints by adding two new pilot symbols. By considering pilot symbol aided channel estimation at the transmitter, we focus on Least Square LS and Minimum Mean Square Error MMSE channel estimation on the receiver. A range of simulations is carried out according to ratio between the Bit Error Rate BER and the Signal to Noise Ratio SNR. We demonstrate that rearranging pilot pattern can offer better results than standardized ones. Furthermore, we prove that adding pilots symbols can provide the best performances.

Connected through hyperedge HE-1 (induced by source paper "estimating the relative speed of rf jammers in vanets"):
  with members:
    - "geometry based vehicle to vehicle channel modeling for large scale simulation"

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.NI(Networking and Internet Architecture)