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 "joint resource optimization for multicell networks with wireless energy harvesting relays"):
  Abstract: This paper first considers a multicell network deployment where the base station (BS) of each cell communicates with its cell-edge user with the assistance of an amplify-and-forward (AF) relay node. Equipped with a power splitter and a wireless energy harvester, the self-sustaining relay scavenges radio frequency (RF) energy from the received signals to process and forward the information. Our aim is to develop a resource allocation scheme that jointly optimizes (i) BS transmit powers, (ii) received power splitting factors for energy harvesting and information processing at the relays, and (iii) relay transmit powers. In the face of strong intercell interference and limited radio resources, we formulate three highly-nonconvex problems with the objectives of sum-rate maximization, max-min throughput fairness and sum-power minimization. To solve such challenging problems, we propose to apply the successive convex approximation (SCA) approach and devise iterative algorithms based on geometric programming and difference-of-convex-functions programming. The proposed algorithms transform the nonconvex problems into a sequence of convex problems, each of which is solved very efficiently by the interior-point method. We prove that our algorithms converge to the locally optimal solutions that satisfy the Karush-Kuhn-Tucker conditions of the original nonconvex problems. We then extend our results to the case of decode-and-forward (DF) relaying with variable timeslot durations. We show that our resource allocation solutions in this case offer better throughput than that of the AF counterpart with equal timeslot durations, albeit at a higher computational complexity. Numerical results confirm that the proposed joint optimization solutions substantially improve the network performance, compared with cases where the radio resource parameters are individually optimized.

Includes members:
  Member "wireless powered relays in cooperative communications time switching relaying protocols and throughput analysis":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on maximizing information reliability in wireless powered cooperative networks")
  Member "distributed power splitting for swipt in relay interference channels using game theory":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "rf based energy harvesting in decode and forward relaying systems ergodic and outage capacities")
  Member "cutting last wires for mobile communication by microwave power transfer":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "wirelessly powered data aggregation for iot via over the air functional computation beamforming and power control")
  Member "resource allocation for coordinated multipoint networks with wireless information and power transfer":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "joint moo of transmit precoding and receiver design in a downlink time switching miso swipt system")
  Member "wireless networks with rf energy harvesting a contemporary survey":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "wirelessly powered sensor networks power allocation for channel estimation and energy beamforming")
  Member "power allocation strategies in energy harvesting wireless cooperative networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "on maximizing information reliability in wireless powered cooperative networks")
  Member "what will 5g be":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "5g network slicing using sdn and nfv a survey of taxonomy architectures and future challenges")
  Member "cooperative energy harvesting networks with spatially random users":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "a unified framework for non orthogonal multiple access")

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)