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Distributed Stochastic Cross-Layer Optimization for Multi-Hop Wireless Networks With Cooperative Communications

机译:具有协作通信的多跳无线网络的分布式随机跨层优化

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Cooperative communication has been shown to have great potential in improving wireless link quality. Incorporating cooperative communications in multi-hop wireless networks has been attracting a growing interest. However, most current research focuses on either centralized solutions or schemes limited to specific network problems. In this paper, we propose a distributed framework that uses Network Utility Maximization (NUM) to optimize the following joint objectives: flow control, routing, scheduling, and relay assignment; for multi-hop wireless cooperative networks with general flow and cooperative relay patterns. We define two special graphs, Hyper Forwarding Graphs (HFG) and Hyper Conflict Graphs (HCG), to represent all possible cooperative routing policies and interference relations among the cooperative relays respectively. Based on HFG and HCG, a stochastic mixed-integer non-linear programming problem is formulated. We then propose lightweight algorithms to solve these in a fully distributed manner, and derive the theoretical performance bounds of these proposed algorithms. Simulation results verify our theoretical analysis and reveal the significant performance gains of our framework, in terms of throughput, flexibility, and scalability. To our knowledge, this is the first distributed cross-layer optimization framework for multi-hop wireless cooperative networks with general flow and cooperative relay patterns.
机译:合作通信已经显示出在改善无线链路质量方面的巨大潜力。在多跳无线网络中集成协作通信引起了越来越多的兴趣。但是,当前大多数研究都集中于集中解决方案或仅限于特定网络问题的方案。在本文中,我们提出了一个分布式框架,该框架使用网络实用程序最大化(NUM)来优化以下联合目标:流控制,路由,调度和中继分配;具有通用流程和协作中继模式的多跳无线协作网络。我们定义了两个特殊的图形,即超前转发图(HFG)和超冲突图(HCG),分别表示所有可能的协作路由策略和协作中继之间的干扰关系。基于HFG和HCG,提出了一种随机混合整数非线性规划问题。然后,我们提出轻量级算法以完全分布式的方式解决这些问题,并推导这些提议算法的理论性能界限。仿真结果验证了我们的理论分析,并揭示了我们的框架在吞吐量,灵活性和可伸缩性方面的显着性能提升。据我们所知,这是第一个具有通用流和协作中继模式的多跳无线协作网络的分布式跨层优化框架。

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