human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "distributed user clustering and resource allocation for imperfect noma in heterogeneous networks"):
  Abstract: In this paper, we propose a distributed cluster formation (CF) and resource allocation (RA) framework for non-ideal non-orthogonal multiple access (NOMA) schemes in heterogeneous networks. The imperfection of the underlying NOMA scheme is due to the receiver sensitivity and interference residue from non-ideal successive interference cancellation (SIC), which is generally characterized by a fractional error factor (FEF). Our analytical findings first show that several factors have a significant impact on the achievable NOMA gain. Then, we investigate fundamental limits on NOMA cluster size as a function of FEF levels, cluster bandwidth, and quality of service (QoS) demands of user equipments (UEs). Thereafter, a clustering algorithm is developed by taking feasible cluster size and channel gain disparity of UEs into account. Finally, we develop a distributed alpha-fair RA framework where alpha governs the trade-off between maximum throughput and proportional fairness objectives. Based on the derived closed-form optimal power levels, the proposed distributed solution iteratively updates bandwidths, clusters, and UEs' transmission powers. Numerical results demonstrate that proposed solutions deliver a higher spectral and energy efficiency than traditionally adopted basic NOMA cluster size of two. We also show that an imperfect NOMA cannot always provide better performance than orthogonal multiple access under certain conditions. Finally, our numerical investigations reveal that NOMA gain is maximized under downlink/uplink decoupled (DUDe) UE association.

Includes members:
  Member "distributed cluster formation and power bandwidth allocation for imperfect noma in dl hetnets":
    also connected through other hyperedges:
      (none)
  Member "optimal resource allocation for power efficient mc noma with imperfect channel state information":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "joint trajectory and resource allocation design for energy efficient secure uav communication systems")
  Member "dynamic user clustering and power allocation for uplink and downlink non orthogonal multiple access noma systems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "non orthogonal multiple access with orthogonal time frequency space signal transmission")
  Member "power and channel allocation for non orthogonal multiple access in 5g systems tractability and computation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "non orthogonal multiple access noma how it meets 5g and beyond")
  Member "non orthogonal multiple access noma for downlink multiuser mimo systems user clustering beamforming and power allocation":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "optical rate splitting multiple access for visible light communications")
  Member "why to decouple the uplink and downlink in cellular networks and how to do it":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "performance of network assisted full duplex for cell free massive mimo")

Question: Please tell me which class the source paper 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)