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 "interference alignment with analog channel state feedback"):
  Abstract: Interference alignment (IA) is a multiplexing gain optimal transmission strategy for the interference channel. While the achieved sum rate with IA is much higher than previously thought possible, the improvement often comes at the cost of requiring network channel state information at the transmitters. This can be achieved by explicit feedback, a flexible yet potentially costly approach that incurs large overhead. In this paper we propose analog feedback as an alternative to limited feedback or reciprocity based alignment. We show that the full multiplexing gain observed with perfect channel knowledge is preserved by analog feedback and that the mean loss in sum rate is bounded by a constant when signal-to-noise ratio is comparable in both forward and feedback channels. When signal-to-noise ratios are not quite symmetric, a fraction of the multiplexing gain is achieved. We consider the overhead of training and feedback and use this framework to optimize the system's effective throughput. We present simulation results to demonstrate the performance of IA with analog feedback, verify our theoretical analysis, and extend our conclusions on optimal training and feedback length.

Includes members:
  Member "adaptive beamforming in interference networks via bi directional training":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "optimizing the mimo cellular downlink multiplexing diversity or interference nulling")
  Member "cooperative algorithms for mimo interference channels":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "the capacity and optimal signaling for gaussian mimo channels under interference constraints full version")
  Member "interference alignment as a rank constrained rank minimization":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "generalized low rank optimization for topological cooperation in ultra dense networks")
  Member "on feasibility of interference alignment in mimo interference networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "joint optimization of signal design and resource allocation in wireless d2d edge computing")
  Member "interference alignment under limited feedback for mimo interference channels":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "opportunistic downlink interference alignment for multi cell mimo networks")
  Member "interference alignment with limited feedback":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "opportunistic downlink interference alignment for multi cell mimo networks")
  Member "on feasibility of interference alignment in mimo interference networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "joint optimization of signal design and resource allocation in wireless d2d edge computing")
  Member "training and feedback optimization for multiuser mimo downlink":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "artificial noisy mimo systems under correlated scattering rayleigh fading a physical layer security approach")

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)