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A computationally efficient node-selection scheme for cooperative beamforming in Cognitive Radio enabled 5G systems

机译:支持认知无线电的5G系统中用于协作波束成形的高效计算节点选择方案

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Cooperative transmit beamforming (CTB) is a practical approach for addressing the challenging problem of spectrum scarcity in broadband 5G wireless communication systems. It is a technique that allows a group of secondary users (SUs), each equipped with a single omni-directional antenna, to collaborate and steer the signal towards the intended receiver. CTB allows SUs to co-exist with primary users in the same spectrum, which helps to significantly improve the efficiency of spectrum utilization. One of the key factors that affect the performance of CTB is the selection of participatory nodes. In this paper, we first formulate the CTB as an optimization problem, and then investigate the impact of different node-selection schemes on the performance of CTB. Our findings illustrate that exhaustive search based optimal node-selection scheme is computationally infeasible for real-time systems, while simple random-selection and highest-channel-state based selection often result in poor performance. Motivated by these findings, we propose a computationally efficient node-selection scheme for CTB that achieves a near-optimal performance. The proposed scheme is based on iterative node-replacement and is computationally scalable to large system size. Results from extensive simulations show that the proposed scheme asymptotically approaches the exhaustive search based optimal system performance. In our example, the performance of the proposed scheme is approximately 98.5% of the optimal system performance while limiting the required computations to only 1.67%.
机译:协作发射波束成形(CTB)是解决宽带5G无线通信系统中频谱稀缺这一具有挑战性问题的实用方法。它是一种技术,它允许一组辅助用户(SU)相互协作并将信号引向预期的接收器,每个辅助用户都配备有单个全向天线。 CTB使SU可以与同一频谱中的主要用户共存,这有助于显着提高频谱利用效率。影响CTB性能的关键因素之一是参与节点的选择。在本文中,我们首先将CTB公式化为一个优化问题,然后研究不同的节点选择方案对CTB性能的影响。我们的发现表明,基于穷举搜索的最佳节点选择方案对于实时系统在计算上是不可行的,而简单的随机选择和基于最高信道状态的选择通常会导致性能不佳。基于这些发现,我们提出了一种计算效率高的CTB节点选择方案,该方案可实现近乎最佳的性能。所提出的方案基于迭代节点替换,并且在计算上可扩展至大系统尺寸。大量仿真结果表明,该方案渐近逼近基于穷举搜索的最优系统性能。在我们的示例中,提出的方案的性能约为最佳系统性能的98.5%,同时将所需的计算限制为仅1.67%。

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