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: "exploiting non orthogonal multiple access in downlink coordinated multipoint transmission with the presence of imperfect channel state information"
  Abstract: The downlink coordinated multipoint (CoMP) transmission system with non-orthogonal multiple access (NOMA) is presented to enhance downlink capacity. Since perfect knowledge of a channel is not always available in practice, imperfect channel state information (CSI) needs to be considered in downlink CoMP with NOMA. In this paper, imperfect CSI is modeled with channel estimation error, where a priori of variance of the error estimation is known. Instead of a specific number of coordinated base stations (BSs), a downlink CoMP NOMA with $B$ coordinated BSs is proposed. Further, the ergodic capacity of the cell-center user (CCU), and the cell-edge user (CEU), as well as their sum capacity are analyzed, derived as closed forms, and validated by simulations in both perfect CSI and imperfect CSI with channel estimation error. The result shows that CoMP NOMA outperforms the CoMP orthogonal multiple access (OMA) capacity, where channel estimation error degrades the performance of both CoMP NOMA and CoMP OMA. In CoMP NOMA, it is noted that the impact of channel estimation error is less significant at CEU compared to that at CCU, due to the utilization of the incoming signals from all the coordinated BSs. Additionally, by exploiting non-orthogonal channel, the sum capacity of CoMP NOMA still can be improved with an increase in coordinated BSs. It is also demonstrated that CEU needs to be allocated with much higher power than CCU to maintain their capacity simultaneously. Finally, the performance analysis is successfully validated through the close accordance between the analytical and simulation results.

Connected through hyperedge HE-1 (induced by source paper "virtual user pairing non orthogonal multiple access in downlink coordinated multipoint transmission"):
  with members:
    - "a novel network noma scheme for downlink coordinated three point systems"
    - "a survey on non orthogonal multiple access for 5g networks research challenges and future trends"

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)