Stochastic Optimization in Cooperative Relay Networks for Revenue Maximization

来源 :Journal of Shanghai Jiaotong University(Science) | 被引量 : 0次 | 上传用户:wuchuanmiao
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In cellular networks, cooperative relaying is an economic and promising way to enlarge the network capacity and coverage. In the case that multiple users and multiple relays are taken into account, efficient resource allocation is important in such networks. In this paper, we consider the joint relay power control with amplify-and-forward(AF) strategy and dynamic pricing for uplink cellular networks in order to maximize the network administrator’s system revenue. The system revenue is associated with pricing strategies and mobile users’ random data request, which is supported by the relay assisted transmission. To deal with the problem of the coupling in pricing and relay resource allocation, we utilize Lyapunov optimization techniques to design online pricing and relay power control without any statistic information of random events in networks. Theoretical analysis shows that the proposed algorithm can achieve a near-optimal performance and simulation results also validate its effectiveness and robustness. In cellular networks, cooperative relaying is an economic and promising way to enlarge the network capacity and coverage. In this case that multiple users and multiple relays are taken into account, efficient resource allocation is important in such networks. In this paper, we consider the joint relay power control with amplify-and-forward (AF) strategy and dynamic pricing for uplink cellular networks in order to maximize the network administrator’s system revenue. The system revenue is associated with pricing strategies and mobile users’ random data request, which is supported by the relay assisted transmission. To deal with the problem of the coupling in pricing and relay resource allocation, we utilize Lyapunov optimization techniques to design online pricing and relay power control without any statistic information of random events in networks. algorithm can achieve a near-optimal performance and simulation results also validate its effect iveness and robustness.
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