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Max-Min Lifetime Optimization for Cooperative Communications in Multi-Channel Wireless Networks

机译:多通道无线网络中协作通信的最大-最小生命周期优化

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Cooperative communication (CC) has been proposed for achieving spatial diversity without requiring multiple antennas on the same node. Many efforts in exploiting the benefits of CC focus on improving the performance in terms of outage probability or channel capacity. However, the energy efficiency of CC, which is critical for the applications with energy constraints, has been little studied. In this paper, we study the lifetime maximization problem for multiple source-destination pairs using CC in multi-channel wireless networks by an optimal dynamic allocation of resources in terms of power, channel, cooperative relay, and transmission time fraction. We prove it NP-hard and formulate it as a mixed-integer nonlinear programming (MINLP) problem, which is then transformed into a mixed-integer linear programming (MILP) problem using linearization and reformulation techniques. By exploiting several problem-specific characteristics, a time-efficient branch-and-bound algorithm is proposed to solve the MILP problem. Extensive simulations are conducted to show that the proposed algorithm can significantly improve the performance of energy efficiency over existing solutions.
机译:已经提出了用于实现空间分集的协作通信(CC),而无需在同一节点上使用多个天线。利用CC好处的许多努力都集中在提高中断概率或信道容量方面的性能。然而,对于具有能量限制的应用而言至关重要的CC的能量效率尚未得到研究。在本文中,我们通过在功率,信道,协作中继和传输时间分数方面优化动态分配资源,研究了在多信道无线网络中使用CC的多个源-目标对的寿命最大化问题。我们证明它为NP-hard,并将其公式化为一个混合整数非线性规划(MINLP)问题,然后使用线性化和重构技术将其转换为一个混合整数线性规划(MILP)问题。通过利用一些特定问题的特征,提出了一种时效高效的分支定界算法来解决MILP问题。进行了广泛的仿真,结果表明,与现有解决方案相比,该算法可以显着提高能效性能。

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