On the Effect of Channel Fading on Greedy Scheduling
Akula Aneesh Reddy, Sujay Sanghavi, Sanjay Shakkottai

TL;DR
This paper investigates how channel fading impacts the efficiency of greedy scheduling in wireless networks, revealing that fading can both improve or worsen GMS performance depending on network conditions.
Contribution
It introduces the Fading Local Pooling factor (F-LPF) to precisely characterize GMS throughput under fading and provides bounds demonstrating the variable impact of fading.
Findings
Fading can either improve or degrade GMS performance.
F-LPF exactly characterizes GMS throughput in fading environments.
Bounds on F-LPF help understand the conditions affecting GMS efficiency.
Abstract
Greedy Maximal Scheduling (GMS) is an attractive low-complexity scheme for scheduling in wireless networks. Recent work has characterized its throughput for the case when there is no fading/channel variations. This paper aims to understand the effect of channel variations on the relative throughput performance of GMS vis-a-vis that of an optimal scheduler facing the same fading. The effect is not a-priori obvious because, on the one hand, fading could help by decoupling/precluding global states that lead to poor GMS performance, while on the other hand fading adds another degree of freedom in which an event unfavourable to GMS could occur. We show that both these situations can occur when fading is adversarial. In particular, we first define the notion of a {\em Fading Local Pooling factor (F-LPF)}, and show that it exactly characterizes the throughput of GMS in this setting. We also…
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Taxonomy
TopicsAdvanced Wireless Network Optimization · Cooperative Communication and Network Coding · Advanced MIMO Systems Optimization
