An SMDP Approach to Optimal PHY Configuration in Wireless Networks

TL;DR

This paper models the optimal physical layer configuration in wireless networks using an SMDP framework, deriving policies that adapt to network states and channel conditions to optimize performance.

Contribution

It introduces an SMDP-based approach for dynamic PHY configuration, including analytical proof of threshold policies for exponential transmission times.

Findings

Optimal policies have a threshold structure for exponential transmission times.

Numerical results confirm the threshold policy structure.

Multi-threshold policies are effective for time-varying channels.

Abstract

In this work, we study the optimal configuration of the physical layer in wireless networks by means of Semi-Markov Decision Process (SMDP) modeling. In particular, assume the physical layer is characterized by a set of potential operating points, with each point corresponding to a rate and reliability pair; for example, these pairs might be obtained through a now-standard diversity-vs-multiplexing tradeoff characterization. Given the current network state (e.g., buffer occupancies), a Decision Maker (DM) needs to dynamically decide which operating point to use. The SMDP problem formulation allows us to choose from these pairs an optimal selection, which is expressed by a decision rule as a function of the number of awaiting packets in the source's finite queue, channel state, size of the packet to be transmitted. We derive a general solution which covers various model configurations, including packet size distributions and varying channels. For the specific case of exponential transmission time, we analytically prove the optimal policy has a threshold structure. Numerical results validate this finding, as well as depict muti-threshold policies for time varying channels such as the Gilber-Elliott channel.