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 "multi cell aware opportunistic random access for machine type communications"):
  Abstract: Due to the difficulty of coordination in multi-cell random access, it is a practical challenge how to achieve the optimal throughput with decentralized transmission. In this paper, we propose a decentralized multi-cell-aware opportunistic random access (MA-ORA) protocol that achieves the optimal throughput scaling in an ultra-dense $K$-cell random access network with one access point (AP) and $N$ users in each cell, which is suited for machine-type communications. Unlike opportunistic scheduling for cellular multiple access where users are selected by base stations, under our MA-ORA protocol, each user opportunistically transmits with a predefined physical layer data rate in a decentralized manner if the desired signal power to the serving AP is sufficiently large and the generating interference leakage power to the other APs is sufficiently small (i.e., two threshold conditions are fulfilled). As a main result, it is proved that the aggregate throughput scales as $\frac{K}{e}(1-\epsilon) \log (\textsf{snr} \log N)$ in a high signal-to-noise ratio (SNR) regime if $N$ scales faster than $\textsf{snr}^{\frac{K-1}{1-\delta}}$ for small constants $\epsilon, \delta>0$. Our analytical result is validated by computer simulations. In addition, numerical evaluation confirms that under a practical setting, the proposed MA-ORA protocol outperforms conventional opportunistic random access protocols in terms of throughput.

Includes members:
  Member "opportunistic downlink interference alignment for multi cell mimo networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "sum rate maximization of multicell miso networks with limited information exchange")
  Member "massive machine type communications in 5g physical and mac layer solutions":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "spatio temporal modeling for massive and sporadic access")
  Member "opportunistic interference alignment for random access networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "interference aware opportunistic random access in dense iot networks")
  Member "maximum sum rate of slotted aloha with capture":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "random noma with cross slot successive interference cancellation packet recovery")
  Member "coded slotted aloha a graph based method for uncoordinated multiple access":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "phase transition analysis for covariance based massive random access with massive mimo")
  Member "cooperative slotted aloha for multi base station systems":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "reliability latency performance of frameless aloha with and without feedback")
  Member "scalable synchronization and reciprocity calibration for distributed multiuser mimo":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "amplitude and phase estimation for absolute calibration of massive mimo front ends")
  Member "can one achieve multiuser diversity in uplink multi cell networks":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "opportunistic downlink interference alignment for multi cell mimo networks")

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)