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 "capacity of the gaussian two hop full duplex relay channel with residual self interference"):
  Abstract: In this paper, we investigate the capacity of the Gaussian two-hop full-duplex (FD) relay channel with residual self-interference. This channel is comprised of a source, an FD relay, and a destination, where a direct source-destination link does not exist and the FD relay is impaired by residual self-interference. We adopt the worst-case linear self-interference model with respect to the channel capacity, and model the residual self-interference as a Gaussian random variable whose variance depends on the amplitude of the transmit symbol of the relay. For this channel, we derive the capacity and propose an explicit capacity-achieving coding scheme. Thereby, we show that the optimal input distribution at the source is Gaussian and its variance depends on the amplitude of the transmit symbol of the relay. On the other hand, the optimal input distribution at the relay is discrete or Gaussian, where the latter case occurs only when the relay-destination link is the bottleneck link. The derived capacity converges to the capacity of the two-hop ideal FD relay channel without self-interference and to the capacity of the two-hop half-duplex (HD) relay channel in the limiting cases when the residual self-interference is zero and infinite, respectively. Our numerical results show that significant performance gains are achieved with the proposed capacity-achieving coding scheme compared to the achievable rates of conventional HD relaying and/or conventional FD relaying.

Includes members:
  Member "all digital self interference cancellation technique for full duplex systems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "state space adaptive nonlinear self interference cancellation for full duplex communication")
  Member "on the capacity of the two hop half duplex relay channel":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "optimal power allocation strategies in full duplex relay networks")
  Member "throughput analysis for full duplex wireless networks with imperfect self interference cancellation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "performance trade off between uplink and downlink in full duplex communications")
  Member "passive self interference suppression for full duplex infrastructure nodes":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "multi objective antenna selection in a full duplex base station")
  Member "widely linear digital self interference cancellation in direct conversion full duplex transceiver":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "full duplex hybrid a d beamforming with reduced complexity multi tap analog cancellation")
  Member "design and characterization of a full duplex multiantenna system for wifi networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "best relay selection in gaussian half duplex diamond networks")
  Member "full duplex transceiver system calculations analysis of adc and linearity challenges":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "state space adaptive nonlinear self interference cancellation for full duplex communication")
  Member "buffer aided relaying with adaptive link selection":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "throughput maximization of mixed fso rf uav aided mobile relaying with a buffer")

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)