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: "conic quadratic formulations for wireless communications design"
  Abstract: As a wide class of resource management problems in wireless communications are nonconvex and even NP-hard in many cases, finding globally optimal solutions to these problems is of little practical interest. Towards more pragmatic approaches, there is a rich literature on iterative methods aiming at finding a solution satisfying necessary optimality conditions to these problems. These approaches have been derived under several similar mathematical frameworks such as inner approximation algorithm, concave-convex procedure, majorization-minimization algorithm, and successive convex approximation (SCA). However, a large portion of existing algorithms arrive at a relatively generic program at each iteration, which is less computationally efficient compared to a more standard convex formulation. This paper proposes \emph{numerically efficient} transformations and approximations for SCA-based methods to deal with nonconvexity in wireless communications design. More specifically, the central goal is to show that various nonconvex problems in wireless communications can be iteratively solved by conic quadratic optimization. We revisit various examples to demonstrate the advantages of the proposed approximations. Theoretical complexity analysis and numerical results show the superior efficiency in terms of computational cost of our proposed solutions compared to the existing ones.

Connected through hyperedge HE-1 (induced by source paper "energy efficient multicell multigroup multicasting with joint beamforming and antenna selection"):
  with members:
    - "distributed optimization for coordinated beamforming in multicell multigroup multicast systems power minimization and sinr balancing"
    - "energy efficient joint unicast and multicast beamforming with multi antenna user terminals"
    - "energy efficient beam coordination strategies with rate dependent processing power"
    - "content centric sparse multicast beamforming for cache enabled cloud ran"
    - "multicast multigroup precoding and user scheduling for frame based satellite communications"
    - "weighted fair multicast multigroup beamforming under per antenna power constraints"
    - "optimal design of energy efficient multi user mimo systems is massive mimo the answer"
    - "coordinated multicast beamforming in multicell networks"

Connected through hyperedge HE-2 (induced by source paper "non orthogonal multiple access assisted multi region geocast"):
  with members:
    - "robust beamforming techniques for non orthogonal multiple access systems with bounded channel uncertainties"
    - "secrecy sum rate maximization in non orthogonal multiple access"
    - "optimal joint power and subcarrier allocation for full duplex multicarrier non orthogonal multiple access systems"
    - "energy efficient transmission design in non orthogonal multiple access"
    - "a minorization maximization method for optimizing sum rate in the downlink of non orthogonal multiple access systems"
    - "fairness for non orthogonal multiple access in 5g systems"
    - "a general mimo framework for noma downlink and uplink transmission based on signal alignment"
    - "weighted fair multicast multigroup beamforming under per antenna power constraints"

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)