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: "optimal power allocation scheme for non orthogonal multiple access with alpha fairness"
  Abstract: This paper investigates the optimal power allocation scheme for sum throughput maximization of non-orthogonal multiple access (NOMA) system with $\alpha$-fairness. In contrast to the existing fairness NOMA models, $\alpha$-fairness can only utilize a single scalar to achieve different user fairness levels. Two different channel state information at the transmitter (CSIT) assumptions are considered, namely, statistical and perfect CSIT. For statistical CSIT, fixed target data rates are predefined, and the power allocation problem is solved for sum throughput maximization with $\alpha$-fairness, through characterizing several properties of the optimal power allocation solution. For perfect CSIT, the optimal power allocation is determined to maximize the instantaneous sum rate with $\alpha$-fairness, where user rates are adapted according to the instantaneous channel state information (CSI). In particular, a simple alternate optimization (AO) algorithm is proposed, which is demonstrated to yield the optimal solution. Numerical results reveal that, at the same fairness level, NOMA significantly outperforms the conventional orthogonal multiple access (MA) for both the scenarios with statistical and perfect CSIT.

Connected through hyperedge HE-1 (induced by source paper "on the performance of network noma in uplink comp systems a stochastic geometry approach"):
  with members:
    - "impact of non orthogonal multiple access on the offloading of mobile edge computing"
    - "poisson cox point processes for vehicular networks"
    - "an analytical framework for coverage in cellular networks leveraging vehicles"
    - "power domain non orthogonal multiple access noma in 5g systems potentials and challenges"
    - "resource allocation for downlink noma systems key techniques and open issues"
    - "a survey on non orthogonal multiple access for 5g networks research challenges and future trends"
    - "coverage analysis of a vehicular network modeled as cox process driven by poisson line process"
    - "noma meets finite resolution analog beamforming in massive mimo and millimeter wave networks"

Connected through hyperedge HE-2 (induced by source paper "asymptotic performance analysis of gsvd noma systems with a large scale antenna array"):
  with members:
    - "a survey on non orthogonal multiple access for 5g networks research challenges and future trends"
    - "optimal joint power and subcarrier allocation for full duplex multicarrier non orthogonal multiple access systems"
    - "non orthogonal multiple access noma for downlink multiuser mimo systems user clustering beamforming and power allocation"
    - "the application of mimo to non orthogonal multiple access"
    - "uplink non orthogonal multiple access for 5g wireless networks"
    - "on the performance of non orthogonal multiple access in 5g systems with randomly deployed users"

Connected through hyperedge HE-3 (induced by source paper "a survey on non orthogonal multiple access for 5g networks research challenges and future trends"):
  with members:
    - "exploiting multiple antenna techniques for non orthogonal multiple access"
    - "achievable rate region of non orthogonal multiple access systems with wireless powered decoder"
    - "a new view of multi user hybrid massive mimo non orthogonal angle division multiple access"
    - "on non orthogonal multiple access with finite alphabet inputs in z channels"
    - "spectrum and energy efficient beamspace mimo noma for millimeter wave communications using lens antenna array"
    - "practical power balanced non orthogonal multiple access"
    - "noma based random access with multichannel aloha"
    - "on optimal power allocation for downlink non orthogonal multiple access systems"

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)