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arXiv 2102.06916cs.ITeess.SPmath.IT
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云无线接入网下行链路平滑无约束近似波束形成器设计

Beamformer Design with Smooth Constraint-Free Approximation in Downlink Cloud Radio Access Networks

Fehmi Emre Kadan, Ali Özgür Yılmaz

摘要:

已知标准蜂窝网络中的数据率由于小区间干扰而受到限制。解决这一问题的有效方法是采用多小区协作的思想。在作为5G及更高版本中的候选解决方案的云无线电接入网络中,通过连接到具有有限容量前传链路的简单远程无线电头端的中央处理器(CP)来应用协作。在这项研究中,我们考虑了下行链路的情况下,旨在通过设计波束形成器,以最大限度地减少总功耗。我们考虑的情况下,完美的信道状态信息是不可用的CP。原问题包括具有许多约束条件的不连续项。我们提出了一种新的方法,将问题转化为一个光滑的无约束的形式和解决方案是由梯度下降的方法。作为比较,我们考虑的最优方法解决了大量的凸子问题,一个已知的启发式搜索算法和一些稀疏的解决方案技术。启发式搜索方法通过求解所有可能的凸子问题的子集来找到解。稀疏技术应用一些范数近似($\ell_0/\ell_1, \ell_0/\ell_2$)或凸近似来使目标函数更易处理。我们还推导出一个理论上的性能界限,以观察当运行最佳方法是禁止的,由于计算复杂性,所提出的方法执行了多远的最佳方法。仿真结果表明,该方法的性能接近最优解,且优于其他方法。

英文摘要:

It is known that data rates in standard cellular networks are limited due to inter-cell interference. An effective solution of this problem is to use the multi-cell cooperation idea. In Cloud Radio Access Network, which is a candidate solution in 5G and beyond, cooperation is applied by means of central processors (CPs) connected to simple remote radio heads with finite capacity fronthaul links. In this study, we consider a downlink scenario and aim to minimize total power spent by designing beamformers. We consider the case where perfect channel state information is not available in the CP. The original problem includes discontinuous terms with many constraints. We propose a novel method which transforms the problem into a smooth constraint-free form and a solution is found by the gradient descent approach. As a comparison, we consider the optimal method solving an extensive number of convex sub-problems, a known heuristic search algorithm and some sparse solution techniques. Heuristic search methods find a solution by solving a subset of all possible convex sub-problems. Sparse techniques apply some norm approximation ($\ell_0/\ell_1, \ell_0/\ell_2$) or convex approximation to make the objective function more tractable. We also derive a theoretical performance bound in order to observe how far the proposed method performs off the optimal method when running the optimal method is prohibitive due to computational complexity. Detailed simulations show that the performance of the proposed method is close to the optimal one, and it outperforms other methods analyzed.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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