Hybrid Scheduling in Heterogeneous Half- and Full-Duplex Wireless Networks
Hybrid Scheduling in Heterogeneous Half- and Full-Duplex Wireless Networks
复制标题
DOI：
10.1109/tnet.2020.2973371
复制
发表时间：
2020-03
期刊：
影响因子：
--
通讯作者：
Tingjun Chen;Jelena Diakonikolas;Javad Ghaderi;G. Zussman
中科院分区：
文献类型：
--
作者：
Tingjun Chen;Jelena Diakonikolas;Javad Ghaderi;G. Zussman
全双工(FD)无线是一种极具吸引力的通信模式，在提高网络容量和降低无线网络时延方面具有很大潜力。尽管在物理层开发方面取得了重大进展，但为由传统半双工(HD)和新兴FD设备组成的异类网络开发媒体访问控制(MAC)协议所面临的挑战尚未完全解决。因此，我们重点研究了基于基础设施的异质HD-FD网络(由HD和FD用户组成)调度算法的设计和性能评估。我们首先证明了集中式贪婪最大调度(GMS)在异质HD-FD网络中是吞吐量最优的。我们提出了混合GMS(H-GMS)算法，这是GMS的一种分布式实现，它结合了GMS和基于队列的随机访问机制。我们证明了H-GMS是吞吐量最优的。此外，我们通过推导平均队列长度的下界来分析H-GMS的时延性能。我们进一步展示了将HD节点升级到FD节点在单个节点和整个网络的吞吐量提升方面的优势。最后，我们通过大量的仿真从吞吐量、时延以及FD和HD用户之间的公平性等方面评估了H-GMS及其变种的性能。结果表明，与完全分散的Q-CSMA算法相比，H-GMS在异质HD-FD网络中获得了16-30倍的延迟性能，HD和FD用户之间的公平性提高了50%。
Full-duplex (FD) wireless is an attractive communication paradigm with high potential for improving network capacity and reducing delay in wireless networks. Despite significant progress on the physical layer development, the challenges associated with developing medium access control (MAC) protocols for heterogeneous networks composed of both legacy half-duplex (HD) and emerging FD devices have not been fully addressed. Therefore, we focus on the design and performance evaluation of scheduling algorithms for infrastructure-based heterogeneous HD-FD networks (composed of HD and FD users). We first show that centralized Greedy Maximal Scheduling (GMS) is throughput-optimal in heterogeneous HD-FD networks. We propose the Hybrid-GMS (H-GMS) algorithm, a distributed implementation of GMS that combines GMS and a queue-based random-access mechanism. We prove that H-GMS is throughput-optimal. Moreover, we analyze the delay performance of H-GMS by deriving lower bounds on the average queue length. We further demonstrate the benefits of upgrading HD nodes to FD nodes in terms of throughput gains for individual nodes and the whole network. Finally, we evaluate the performance of H-GMS and its variants in terms of throughput, delay, and fairness between FD and HD users via extensive simulations. We show that in heterogeneous HD-FD networks, H-GMS achieves 16– $30\times $ better delay performance and improves fairness between HD and FD users by up to 50% compared with the fully decentralized Q-CSMA algorithm.