论文标题
接力辅助MMWave网络中的关联和缓存:从随机几何学角度来看
Association and Caching in Relay-Assisted mmWave Networks: From A Stochastic Geometry Perspective
论文作者
论文摘要
有限的回程带宽和阻塞效应是限制毫米波(MMWave)网络实际部署的两个主要因素。为了解决这些问题,我们研究了继电器和MMWave网络中的可行性。用户关联和继电器(UAR)标准取决于缓存状态和最大偏见接收的功率,这是通过考虑由基站(BSS)(BSS)和继电器节点(RNS)共存引起的空间相关性来提出的。然后制定关节UAR和缓存位置问题,以最大程度地提高回程卸载流量。使用随机几何工具,我们通过分析UAR概率和缓存位置概率之间的关系来解除关节UAR和缓存位置问题。然后,我们通过在一般情况下利用单调特性并在噪声限制的情况下利用凸优化来优化基于多块外部近似的变换的缓存位置问题。因此,我们提出了BS和RN选择算法,其中共同考虑了BSS的缓存状态和最大偏见接收的功率。实验结果表明,使用所提出的算法可以显着提高回程卸载,并表明在MMWave网络中部署更多的RN和增加的高速缓存大小是一种更具成本效益的替代方法,而不是增加BS密度以实现类似的回程卸载性能。
Limited backhaul bandwidth and blockage effects are two main factors limiting the practical deployment of millimeter wave (mmWave) networks. To tackle these issues, we study the feasibility of relaying as well as caching in mmWave networks. A user association and relaying (UAR) criterion dependent on both caching status and maximum biased received power is proposed by considering the spatial correlation caused by the coexistence of base stations (BSs) and relay nodes (RNs). A joint UAR and caching placement problem is then formulated to maximize the backhaul offloading traffic. Using stochastic geometry tools, we decouple the joint UAR and caching placement problem by analyzing the relationship between UAR probabilities and caching placement probabilities. We then optimize the transformed caching placement problem based on polyblock outer approximation by exploiting the monotonic property in the general case and utilizing convex optimization in the noise-limited case. Accordingly, we propose a BS and RN selection algorithm where caching status at BSs and maximum biased received power are jointly considered. Experimental results demonstrate a significant enhancement of backhaul offloading using the proposed algorithms, and show that deploying more RNs and increasing cache size in mmWave networks is a more cost-effective alternative than increasing BS density to achieve similar backhaul offloading performance.