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 "efficient solutions for weighted sum rate maximization in multicellular networks with channel uncertainties"):
  Abstract: The important problem of weighted sum rate maximization (WSRM) in a multicellular environment is intrinsically sensitive to channel estimation errors. In this paper, we study ways to maximize the weighted sum rate in a linearly precoded multicellular downlink system where the receivers are equipped with a single antenna. With perfect channel information available at the base stations, we first present a novel fast converging algorithm that solves the WSRM problem. Then, the assumption is relaxed to the case where the error vectors in the channel estimates are assumed to lie in an uncertainty set formed by the intersection of finite ellipsoids. As our main contributions, we present two procedures to solve the intractable nonconvex robust designs based on the worst case principle. The proposed iterative algorithms solve semidefinite programs in each of their steps and provably converge to a locally optimal solution of the robust WSRM problem. The proposed solutions are numerically compared against each other and known approaches in the literature to ascertain their robustness towards channel estimation imperfections. The results clearly indicate the performance gain compared to the case when channel uncertainties are ignored in the design process. For certain scenarios, we also quantify the gap between the proposed approximations and exact solutions.

Includes members:
  Member "an analytical framework for heterogeneous partial feedback design in heterogeneous multicell ofdma networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a distributed optimization framework for multi channel multi user small cell networks")
  Member "fast converging algorithm for weighted sum rate maximization in multicell miso downlink":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "resource allocation in intelligent reflecting surface assisted noma systems")
  Member "robust monotonic optimization framework for multicell miso systems":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "robust resource allocation for pd noma based miso heterogeneous networks with comp technology")
  Member "achieving global optimality for weighted sum rate maximization in the k user gaussian interference channel with multiple antennas":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "mixed monotonic programming for fast global optimization")
  Member "robust linear precoder design for multi cell downlink transmission":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "non orthogonal unicast and broadcast transmission via joint beamforming and ldm in cellular networks")
  Member "cooperative interference management with miso beamforming":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "intelligent reflecting surface aided multiple access capacity region and deployment strategy")
  Member "gaussian interference channel capacity to within one bit":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "fundamental limits of wireless caching under mixed cacheable and uncacheable traffic")

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.IT(Information Theory)