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 "optimal precoder designs for sum utility maximization in swipt enabled multi user mimo cognitive radio networks"):
  Abstract: In this paper, we study a generalized framework that combines the three major techniques for 5G communication systems such as the multi-user multi-input multi-output (MuMIMO) techniques for spectral efficiency enhancement, the cognitive radio (CR) techniques for spectrum sharing, and the simultaneous wireless information and power transfer (SWIPT) techniques for convenient power supplies, which is called a MuMIMO-CR-SWIPT network. In this system, we have one base-station that simultaneously supports multiple information decoding (ID) and energy harvesting users under a condition that interference power to the primary ID (P-ID) receivers stays below a certain threshold. With this scenario, our goal is to design an optimal precoder that maximizes the sum-utility cost function for the ID users while satisfying the transmit power constraint at the BS, the energy requirement at each EH user, and the interference power constraint at each P-ID user. As we consider a general sum-utility cost function that puts together different target utilities in a general MuMIMO-CR-SWIPT environment, the previous works for each of the MuMIMO, CR, and SWIPT systems are casted as particular solutions of our framework. The problem has been considered to be challenging, since the weighted minimum mean-squared error problem transformation no longer resolves the non-convexity of the original problem. In this paper, we settle such an issue by demonstrating that the WMMSE transformation guarantees zero-duality gap between the primal and dual problems. Based on the observation, we attain the optimal precoder by solving the dual problem through the sub-gradient ellipsoid method. We also propose a simplified algorithm for the case of a single ID user, which is shown to achieve the globally optimum. Finally, we demonstrate the optimality and efficiency of the proposed algorithms through numerical simulation results.

Includes members:
  Member "joint optimization of power and data transfer in multiuser mimo systems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "robust energy efficient beamforming in misome swipt systems with proportional secrecy rate")
  Member "wireless powered communication opportunities and challenges":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "wirelessly powered sensor networks power allocation for channel estimation and energy beamforming")
  Member "practical non linear energy harvesting model and resource allocation for swipt systems":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "wirelessly powered sensor networks power allocation for channel estimation and energy beamforming")
  Member "throughput optimization for massive mimo systems powered by wireless energy transfer":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "wirelessly powered sensor networks power allocation for channel estimation and energy beamforming")
  Member "mimo broadcasting for simultaneous wireless information and power transfer weighted mmse approaches":
    also connected through other hyperedges:
      (none)
  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 "multiuser miso beamforming for simultaneous wireless information and power transfer":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "design of an miso swipt aided code index modulated multi carrier m dcsk system for e health iot")
  Member "mimo broadcasting for simultaneous wireless information and power transfer":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "energy efficient hybrid precoding design for integrated multicast unicast millimeter wave communications with swipt")

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)