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 "on the optimality of opportunistic interference alignment in 3 transmitter mimo interference channels"):
  Abstract: In this paper, we propose opportunistic interference alignment (OIA) for three-transmitter multiple-input multiple-output (MIMO) interference channels (ICs). In the proposed OIA scheme, each transmitter has its own user group that consists of $K$ users, and each transmitter opportunistically selects the user whose received interference signals are most aligned. Thus, three-transmitter MIMO IC is opportunistically constructed by three transmitters and their selected users. Contrary to conventional IA, perfect channel information for all of the interference links is not required at the transmitter. Each user just needs to feed back one scalar value in the proposed OIA scheme. When the number of receive antennas is $N_R$ (with $N_R=2M$) and the number of transmit antennas is $N_T$ (with $N_T\ge M$), we prove that each transmitter can achieve $M$ degrees of freedom (DoF) as the number of users in each group goes to infinity ($K\to\infty$), in comparison with the $\frac{2M}{3}$ DoF known to be achievable in the three-transmitter $M \times 2M$ MIMO IC. We also show that the user scaling $K\propto P^{\alpha M^2}$ enables the network to achieve $M$ DoF per transmitter where $P$ is transmit power, and $\alpha$ is the relative path loss of the interfering channel in decibels. The computational complexity of the proposed OIA scheme is analyzed and compared with conventional user selection schemes.

Includes members:
  Member "from spectrum pooling to space pooling opportunistic interference alignment in mimo cognitive networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "contextual bandit learning for machine type communications in the null space of multi antenna systems")
  Member "degrees of freedom of the k user m times n mimo interference channel":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "noma an information theoretic perspective")
  Member "approaching the capacity of wireless networks through distributed interference alignment":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "fundamental limits of dynamic interference management with flexible message assignments")
  Member "limited feedback based block diagonalization for the mimo broadcast channel":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "mimo amplify and forward precoding for networked control systems")
  Member "gaussian interference channel capacity to within one bit":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "fundamental limits of wireless caching under mixed cacheable and uncacheable traffic")
  Member "interference alignment and the degrees of freedom for the k user interference channel":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "on off switched interference alignment for diversity multiplexing tradeoff improvement in the 2 user x network with two antennas")

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)