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 "gdof of the k user symmetric miso bc bridging the gap between finite precision and perfect csit"):
  Abstract: We characterize the sum GDoF of the $K $ user symmetric MISO BC where the direct channels have strengths $\sim SNR$, cross channels have strengths $\sim SNR^{\alpha}$, and the channel estimation error terms have strengths $\sim SNR^{-\beta}$. This is a step towards the ultimate goal of unifying recent advances which focus exclusively on either the diversity of channel strengths ($\alpha$) or the channel uncertainty ($\beta$) aspect, and bridging the gap between the divergent extremes studied thus far where 1) cross-channels are either assumed to be as strong as direct channels ($\alpha=1$, as in DoF studies) or so weak (small $\alpha$) that they can be optimally treated as noise (TIN); or 2) where channel knowledge is assumed to be either absent $(\beta=0)$ or essentially perfect (large $\beta$). Restricting $\alpha\in[0,1]$ and without loss of generality $\beta\in[0,\alpha]$, it is shown that the $K$ user symmetric MISO BC has $(\alpha-\beta)+K(1-(\alpha-\beta))$ GDoF. A useful interpretation is that the power levels effectively split into a fraction $(\alpha-\beta)$ where CSIT is essentially absent (GDoF $=1$ per power level dimension), and the remaining $1-(\alpha-\beta)$ fraction where CSIT is essentially perfect (GDoF $=K$ per power level dimension). For $K=2$ users with arbitrary $\beta_{kl}$ parameters, the GDoF are shown to be $2-\alpha+\min_{k,l} \beta_{kl}$. Remarkably, the roles of $\alpha$ and $\beta$ counter each other on equal terms so that only their difference matters.

Includes members:
  Member "topological interference management through index coding":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on the separability of parallel miso broadcast channels under partial csit a degrees of freedom region perspective")
  Member "aligned image sets under channel uncertainty settling a conjecture by lapidoth shamai and wigger on the collapse of degrees of freedom under finite precision csit":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "secure degrees of freedom of one hop wireless networks with no eavesdropper csit")
  Member "optimal use of current and outdated channel state information degrees of freedom of the miso bc with mixed csit":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "achievable dof regions of three user mimo broadcast channel with delayed csit")
  Member "on the capacity of fading mimo broadcast channels with imperfect transmitter side information":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "on the separability of parallel miso broadcast channels under partial csit a degrees of freedom region perspective")

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)