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 fair power allocation approach to noma in multiuser siso systems"
  Abstract: A nonorthogonal multiple access (NOMA) approach that always outperforms orthogonal multiple access (OMA) called Fair-NOMA is introduced. In Fair-NOMA, each mobile user is allocated its share of the transmit power such that its capacity is always greater than or equal to the capacity that can be achieved using OMA. For any slow-fading channel gains of the two users, the set of possible power allocation coefficients is derived. For the infimum and supremum of this set, the individual capacity gains and the sum-rate capacity gain are derived. It is shown that the ergodic sum-rate capacity gain approaches 1 b/s/Hz when the transmit power increases for the case when pairing two random users with independent identically distributed channel gains. The outage probability of this approach is derived and shown to be better than OMA. The Fair-NOMA approach is applied to the case of pairing a near base-station user and a cell-edge user and the ergodic capacity gap is derived as a function of total number of users in the cell at high SNR. This is then compared to the conventional case of fixed-power NOMA with user pairing. Finally, Fair-NOMA is extended to   $K$   users and it is proven that the capacity can always be improved for each user, while using less than the total transmit power required to achieve OMA capacities per user.

Connected through hyperedge HE-1 (induced by source paper "performance analysis of ssk noma"):
  with members:
    - "derivation of the closed form ber expressions for dl noma over nakagami m fading channels"
    - "spatial modulation assisted multi antenna non orthogonal multiple access"
    - "power domain non orthogonal multiple access noma in 5g systems potentials and challenges"
    - "resource allocation for downlink noma systems key techniques and open issues"
    - "relay selection for cooperative noma"
    - "power and channel allocation for non orthogonal multiple access in 5g systems tractability and computation"
    - "non orthogonal multiple access in multi cell networks theory performance and practical challenges"
    - "fairness for non orthogonal multiple access in 5g systems"

Connected through hyperedge HE-2 (induced by source paper "fundamentals of power allocation strategies for downlink multi user noma with target rates"):
  with members:
    - "leveraging edge caching in noma systems with qos requirements"
    - "on the power allocation limits for downlink multi user noma with qos"
    - "joint beamforming and power allocation in downlink noma multiuser mimo networks"
    - "joint power allocation and beamforming for non orthogonal multiple access noma in 5g millimeter wave communications"
    - "on optimal power allocation for downlink non orthogonal multiple access systems"
    - "a fair individual rate comparison between mimo noma and mimo oma"
    - "capacity comparison between mimo noma and mimo oma with multiple users in a cluster"
    - "a new noma approach for fair power allocation"

Connected through hyperedge HE-3 (induced by source paper "leveraging edge caching in noma systems with qos requirements"):
  with members:
    - "a new noma approach for fair power allocation"
    - "caching at the edge a green perspective for 5g networks"
    - "living on the edge the role of proactive caching in 5g wireless networks"

Connected through hyperedge HE-4 (induced by source paper "on the power allocation limits for downlink multi user noma with qos"):
  with members:
    - "downlink non orthogonal multiple access with limited feedback"
    - "a new noma approach for fair power allocation"
    - "on the performance of non orthogonal multiple access in 5g systems with randomly deployed users"

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)