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 "performance bounds for antenna domain systems"):
  Abstract: In this work, we investigate the so-called antenna domain formation problem, as the optimal assignment of users to antenna domains, in cloud radio access networks. We focus on theoretical aspects of the problem, namely, the finding of lower bounds, on the interference leakage in the network. We formulate the antenna domain formation problem as an integer optimization problem, and propose an iterative algorithm for obtaining a solution. Motivated by the lack of optimality guarantees on such solutions, we opt to find lower bounds on the problem, and the resulting interference leakage in the network. We thus derive the corresponding Dantzig-Wolfe decomposition, formulate the dual problem, and show that the former offers a tighter bound than the latter. We highlight the fact that the bounds in question consist of linear problems with an exponential number of variables, and adapt known methods aimed at solving them. In addition to shedding light on the tightness of the bounds in question, our numerical results show sum-rate gains of at least 200% (over a simple benchmark), in the medium SNR region.

Includes members:
  Member "rrh clustering and transmit precoding for interference limited 5g cran downlink":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "coordination and antenna domain formation in cloud ran systems")
  Member "content centric multicast beamforming in cache enabled cloud radio access networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "caching placement in stochastic wireless caching helper networks channel selection diversity via caching")
  Member "fundamental limits of cooperation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "area spectral efficiency and sinr scaling laws in multi antenna cellular networks")
  Member "optimality properties distributed strategies and measurement based evaluation of coordinated multicell ofdma transmission":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "multiple antenna technologies for beyond 5g")
  Member "user partitioning for less overhead in mimo interference channels":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "distributed long term base station clustering in cellular networks using coalition formation")

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)