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 "transmit power minimization in small cell networks under time average qos constraints"):
  Abstract: We consider a small cell network (SCN) consisting of    $N$   cells, with the small cell base stations (SCBSs) equipped with    $N_t \geq 1$   antennas each, serving    $K$   single antenna user terminals (UTs) per cell. Under this set up, we address the following question: given certain time average quality of service (QoS) targets for the UTs, what is the minimum transmit power expenditure with which they can be met? Our motivation to consider time average QoS constraint comes from the fact that modern wireless applications such as file sharing, multi-media etc. allow some flexibility in terms of their delay tolerance. Time average QoS constraints can lead to greater transmit power savings as compared to instantaneous QoS constraints since it provides the flexibility to dynamically allocate resources over the fading channel states. We formulate the problem as a stochastic optimization problem whose solution is the design of the downlink beamforming vectors during each time slot. We solve this problem using the approach of Lyapunov optimization and characterize the performance of the proposed algorithm. With this algorithm as the reference, we present two main contributions that incorporate practical design considerations in SCNs. First, we analyze the impact of delays incurred in information exchange between the SCBSs. Second, we impose channel state information (CSI) feedback constraints, and formulate a joint CSI feedback and beamforming strategy. In both cases, we provide performance bounds of the algorithm in terms of satisfying the QoS constraints and the time average power expenditure. Our simulation results show that solving the problem with time average QoS constraints provide greater savings in the transmit power as compared to the instantaneous QoS constraints.

Includes members:
  Member "open vs closed access femtocells in the uplink":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a game theoretical approach for qos provisioning in heterogeneous networks")
  Member "dynamic resource allocation in cognitive radio networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "joint power control and passive beamforming in irs assisted spectrum sharing")
  Member "femto macro cellular interference control with subband scheduling and interference cancelation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "small cell traffic balancing over licensed and unlicensed bands")
  Member "stability and delay of zero forcing sdma with limited feedback":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "an overview on resource allocation techniques for multi user mimo systems")
  Member "training and feedback optimization for multiuser mimo downlink":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "artificial noisy mimo systems under correlated scattering rayleigh fading a physical layer security approach")
  Member "delay optimal power and precoder adaptation for multi stream mimo systems":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "dynamic partial cooperative mimo system for delay sensitive applications with limited backhaul capacity")
  Member "on peak versus average interference power constraints for protecting primary users in cognitive radio networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "transmit power policy and ergodic multicast rate analysis of cognitive radio networks in generalized fading")

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)