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 "a systematic approach for interference alignment in csit less relay aided x networks"):
  Abstract: The degrees of freedom (DoF) of an X-network with M transmit and N receive nodes utilizing interference alignment with the support of $J$ relays each equipped with $L_j$ antennas operating in a half-duplex non-regenerative mode is investigated. Conditions on the feasibility of interference alignment are derived using a proper transmit strategy and a structured approach based on a Kronecker-product representation. The advantages of this approach are twofold: First, it extends existing results on the achievable DoF to generalized antenna configurations. Second, it unifies the analysis for time-varying and constant channels and provides valuable insights and interconnections between the two channel models. It turns out that a DoF of $\nicefrac{NM}{M+N-1}$ is feasible whenever the sum of the $L_j^2 \geq [N-1][M-1]$.

Includes members:
  Member "guiding blind transmitters degrees of freedom optimal interference alignment using relays":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "joint optimization of power splitting and allocation for swipt in interference alignment networks")
  Member "the gaussian interference relay channel improved achievable rates and sum rate upperbounds using a potent relay":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "approximate capacity of fast fading interference channels with no instantaneous csit")
  Member "on degrees of freedom region of mimo networks without csit":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "the degrees of freedom region of temporally correlated mimo networks with delayed csit")

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)