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 "weighted sum rate maximization in multi carrier noma with cellular power constraint"):
  Abstract: Non-orthogonal multiple access (NOMA) has received significant attention for future wireless networks. NOMA outperforms orthogonal schemes, such as OFDMA, in terms of spectral efficiency and massive connectivity. The joint subcarrier and power allocation problem in NOMA is NP-hard to solve in general, due to complex impacts of signal superposition on each users achievable data rates, as well as combinatorial constraints on the number of multiplexed users per sub-carrier to mitigate error propagation. In this family of problems, weighted sum-rate (WSR) is an important objective function as it can achieve different tradeoffs between sum-rate performance and user fairness. We propose a novel approach to solve the WSR maximization problem in multi-carrier NOMA with cellular power constraint. The problem is divided into two polynomial time solvable sub-problems. First, the multi-carrier power control (given a fixed subcarrier allocation) is non-convex. By taking advantage of its separability property, we design an optimal and low complexity algorithm (MCPC) based on projected gradient descent. Secondly, the single-carrier user selection is a non-convex mixed-integer problem that we solve using dynamic programming (SCUS). This work also aims to give an understanding on how each sub-problem's particular structure can facilitate the algorithm design. In that respect, the above MCPC and SCUS are basic building blocks that can be applied in a wide range of resource allocation problems. Furthermore, we propose an efficient heuristic to solve the general WSR maximization problem by combining MCPC and SCUS. Numerical results show that it achieves near-optimal sum-rate with user fairness, as well as significant performance improvement over OMA.

Includes members:
  Member "optimal joint subcarrier and power allocation in noma is strongly np hard":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "non orthogonal multiple access noma how it meets 5g and beyond")
  Member "optimal joint power and subcarrier allocation for mc noma systems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "non orthogonal multiple access noma how it meets 5g and beyond")
  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 "a new noma approach for fair power allocation":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "fundamentals of power allocation strategies for downlink multi user noma with target rates")
  Member "complexity analysis of joint subcarrier and power allocation for the cellular downlink ofdma system":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "optimal joint subcarrier and power allocation in noma is strongly np hard")
  Member "on the complexity of joint subcarrier and power allocation for multi user ofdma systems":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "harq cc enabled noma designs with outage probability constraints")

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)