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 "unequal error protection in coded slotted aloha"):
  Abstract: We analyze the performance of coded slotted ALOHA systems for a scenario where users have different error protection requirements and correspondingly can be divided into user classes. The main goal is to design the system so that the requirements for each class are satisfied. To that end, we derive analytical error floor approximations of the packet loss rate for each class in the finite frame length regime, as well as the density evolution in the asymptotic case. Based on this analysis, we propose a heuristic approach for the optimization of the degree distributions to provide the required unequal error protection. In addition, we analyze the decoding delay for users in different classes and show that better protected users experience a smaller average decoding delay.

Includes members:
  Member "prioritized random mac optimization via graph based analysis":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "random multiple access for m2m communications with qos guarantees")
  Member "coded slotted aloha a graph based method for uncoordinated multiple access":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "phase transition analysis for covariance based massive random access with massive mimo")
  Member "broadcast coded slotted aloha for vehicular communications a finite frame length analysis":
    also connected through other hyperedges:
      (none)
  Member "broadcast coded slotted aloha a finite frame length analysis":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "finite length analysis of irregular repetition slotted aloha in the waterfall region")
  Member "aloha random access that operates as a rateless code":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "online estimation and adaptation for random access with successive interference cancellation")
  Member "coded slotted aloha with varying packet loss rate across users":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "prioritized random mac optimization via graph based analysis")
  Member "high throughput random access via codes on graphs coded slotted aloha":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "random access for massive machine type communications")

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)