An Online Approach to D2D Trajectory Utility Maximization Problem

TL;DR

This paper develops an online trajectory optimization algorithm for D2D communication users that balances connectivity and privacy, achieving near-optimal performance with efficient, real-time decision-making.

Contribution

It introduces a novel online algorithm for D2D trajectory planning that accounts for privacy and mobility constraints, with proven sublinear regret and practical efficiency.

Findings

The online algorithm achieves sublinear offline regret.

Numerical tests confirm the algorithm's effectiveness across various scenarios.

The approach balances D2D connectivity, privacy, and mobility constraints effectively.

Abstract

This paper considers the problem of designing the user trajectory in a device-to-device communications setting. We consider a pair of pedestrians connected through a D2D link. The pedestrians seek to reach their respective destinations while using the D2D link for data exchange applications such as file transfer, video calling, and online gaming. In order to enable better D2D connectivity, the pedestrians are willing to deviate from their respective shortest paths, at the cost of reaching their destinations slightly late. A generic trajectory optimization problem is formulated and solved for the case when full information about the problem in known in advance. Motivated by the D2D user's need to keep their destinations private, we also formulate a regularized variant of the problem that can be used to develop a fully online algorithm. The proposed online algorithm is quite efficient, and is shown to achieve a sublinear \emph{offline} regret while satisfying the required mobility constraints exactly. The theoretical results are backed by detailed numerical tests that establish the efficacy of the proposed algorithms under various settings.