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 "c ran with hybrid rf fso fronthaul links joint optimization of rf time allocation and fronthaul compression"):
  Abstract: This paper considers the uplink of a cloud radio access network (C-RAN) comprised of several multi-antenna remote radio units (RUs) which compress the signals that they receive from multiple mobile users (MUs) and forward them to a CU via wireless fronthaul links. To enable reliable high rate fronthaul links, we employ a hybrid radio frequency (RF)/free space optical (FSO) system for fronthauling. To strike a balance between complexity and performance, we consider three different quantization schemes at the RUs, namely per-antenna vector quantization (AVQ), per-RU vector quantization (RVQ), and distributed source coding (DSC), and two different receivers at the CU, namely the linear minimum mean square error receiver and the optimal successive interference cancellation receiver. For this network architecture, we investigate the joint optimization of the quantization noise covariance matrices at the RUs and the RF time allocation to the multiple-access and fronthaul links for rate region maximization. To this end, we formulate a unified weighted sum rate maximization problem valid for each possible pair of the considered quantization and detection schemes. To handle the non-convexity of the unified problem, we transform it into a bi-convex problem which facilitates the derivation of an efficient suboptimal solution using alternating convex optimization and golden section search. Our simulation results show that for each pair of the considered quantization and detection schemes, C-RAN with hybrid RF/FSO fronthauling can achieve a considerable sum rate gain compared to conventional systems employing pure FSO fronthauling, especially under unfavorable atmospheric conditions. Moreover, employing a more sophisticated quantization scheme can significantly improve the system performance under adverse atmospheric conditions.

Includes members:
  Member "on the design of matched filters for molecule counting receivers":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "transmitter and receiver architectures for molecular communications a survey on physical design with modulation coding and detection techniques")
  Member "on the optimal fronthaul compression and decoding strategies for uplink cloud radio access networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "integer forcing architectures for uplink cloud radio access networks")
  Member "recent advances in cloud radio access networks system architectures key techniques and open issues":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "multiple antenna technologies for beyond 5g")
  Member "optimal relay selection for the parallel hybrid rf fso relay channel non buffer aided and buffer aided designs":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "generalized optimal two way relays subsets pairings in cloud based region cognitive networks")
  Member "fronthaul compression and transmit beamforming optimization for multi antenna uplink c ran":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "integer forcing architectures for uplink cloud radio access networks")
  Member "fronthaul constrained cloud radio access networks insights and challenges":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "on the capacity regions of cloud radio access networks with limited orthogonal fronthaul")
  Member "hybrid radio free space optical design for next generation backhaul systems":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "6g wireless communication systems applications requirements technologies challenges and research directions")
  Member "optimized backhaul compression for uplink cloud radio access network":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "integer forcing architectures for uplink cloud radio access networks")

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)