Minimum-Latency Scheduling For Partial-Information Multiple Access Schemes

TL;DR

This paper models partial-information multiple access as a POMDP to optimize user scheduling, proposing sub-optimal greedy algorithms that significantly outperform traditional schemes in latency and efficiency.

Contribution

It introduces a POMDP framework for PIMA with correlated user activity and develops greedy algorithms to optimize user scheduling under partial information.

Findings

Substantial performance improvements over traditional OMA schemes.

Greedy algorithms effectively approximate optimal scheduling.

Modeling as POMDP captures correlation in user activity.

Abstract

Partial-information multiple access (PIMA) is an orthogonal multiple access (OMA) uplink scheme where time is divided into frames, each composed of two parts. The first part is used to count the number of users with packets to transmit, while the second has a variable number of allocated slots, each assigned to multiple users to uplink data transmission. We investigate the case of correlated user activations, wherein the correlation is due to the retransmissions of the collided packets, modeling PIMA as a partially observable-Markov decision process. The assignment of users to slots is optimized based on the knowledge of both the number of active users and past successful transmissions and collisions. The scheduling turns out to be a mixed integer nonlinear programming problem, with a complexity exponentially growing with the number of users. Thus, sub-optimal greedy solutions are proposed and evaluated. Our solutions show substantial performance improvements with respect to both traditional OMA schemes and conventional PIMA.