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Autonomous algorithms for centralized and distributed interference coordination: a virtual layer-based approach

机译:集中式和分布式干扰协调的自主算法:基于虚拟层的方法

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摘要

Interference mitigation techniques are essential for improving the performance of interference limited wireless networks. In this paper, we introduce novel interference mitigation schemes for wireless cellular networks with space division multiple access (SDMA). The schemes are based on a virtual layer that captures and simplifies the complicated interference situation in the network and that is used for power control. We show how optimization in this virtual layer generates gradually adapting power control settings that lead to autonomous interference minimization. Thereby, the granularity of control ranges from controlling frequency sub-band power via controlling the power on a per-beam basis, to a granularity of only enforcing average power constraints per beam. In conjunction with suitable short-term scheduling, our algorithms gradually steer the network towards a higher utility. We use extensive system-level simulations to compare three distributed algorithms and evaluate their applicability for different user mobility assumptions. In particular, it turns out that larger gains can be achieved by imposing average power constraints and allowing opportunistic scheduling instantaneously, rather than controlling the power in a strict way. Furthermore, we introduce a centralized algorithm, which directly solves the underlying optimization and shows fast convergence, as a performance benchmark for the distributed solutions. Moreover, we investigate the deviation from global optimality by comparing to a branch-and-bound-based solution.
机译:干扰缓解技术对于提高受干扰限制的无线网络的性能至关重要。在本文中,我们介绍了具有空分多址(SDMA)的无线蜂窝网络的新型干扰缓解方案。该方案基于虚拟层,该虚拟层捕获并简化了网络中复杂的干扰情况,并用于功率控制。我们展示了此虚拟层中的优化如何逐步生成适应性强的功率控制设置,从而导致自主干扰最小化。从而,控制的粒度范围从通过基于每个波束的功率控制频率子带功率到仅对每个波束实施平均功率约束的粒度。结合适当的短期调度,我们的算法逐渐将网络引向更高的效用。我们使用广泛的系统级仿真来比较三种分布式算法,并评估它们在不同用户移动性假设下的适用性。特别地,事实证明,通过施加平均功率约束并允许瞬时机会调度而不是严格地控制功率,可以实现更大的增益。此外,我们引入了一种集中式算法,可以直接解决底层优化并显示出快速收敛性,以此作为分布式解决方案的性能基准。此外,我们通过与基于分支定界的解决方案进行比较来研究与全局最优性的偏差。

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