In this paper, we focus on the achievable sum-rate optimization problem of a multi-user, multi-hop relay network. We analyze the joint relay selection and power control in the presence of interference such that the achievable sum-rate is maximized. First, we evaluate the achievable sum-rate under five relay selection strategies when the transmit power is fixed. We show that the dynamic programming based max-min relay selection with the objective of maximizing the minimum signal-to-noise-ratio results in the highest achievable sum-rate gain for larger networks. Next, we combine the relay selection problem using the max-min relay selection and the power control problem using a tight lower bound approximation and propose a novel iterative algorithm, which maximizes the achievable sum-rate. We also provide a comprehensive comparison of the proposed algorithm with respect to existing resource allocation techniques, and observe that our proposed algorithm provides significant sum-rate gains. Finally, we prove that for the special case of two-user networks, binary power allocation is optimum for at least two transmitting nodes. Extensive numerical examples are provided to illustrate the accuracy of our results.
翻译:在本文中,我们侧重于多用户、多跳点中继网络的可实现的超速优化问题。 我们分析在干扰情况下联合中继选择和电源控制,以便实现可实现的超速。 首先,我们评估在5个中继选择战略下,在传输电源固定的情况下,在5个中继选择战略下可实现的超速率。 我们显示,基于最大中继选择的动态编程结果,目的是为更大的网络最大限度地实现最起码的信号到噪点的可实现的总和增益。 其次,我们结合使用最大中继选择和电源控制问题,使用紧凑的下限近似值,提出新的迭代方算法,使可实现的超速率最大化。 我们还对拟议的算法与现有资源分配技术进行全面比较,并指出,我们提议的算法提供了巨大的超速率收益。 最后,我们证明,对于两个用户网络的特殊案例,至少两个传输节点的二元能力分配是最佳的。 我们提供了广泛的数字例子,以说明我们结果的准确性。