Dijkstra-Based Joint Path Selection and Channel Assignment for In-Band Full-Duplex Multi-Hop CR-IoT Networks

Abstract

Shortage in frequency spectrum and high data rate requirements are two major challenges facing Internet of Things (IoT) applications. Cognitive radio (CR) and in-band full-duplex (IBFD) technologies proved efficient in addressing these challenges. In this paper, we address the problem of path selection and channel assignment in multi-hop wireless IoT networks equipped with CR and IBFD capabilities. The approach followed by most research works in the literature is to formulate the problem as a mathematical program whose objective and constraints aim at selecting a path and assigning CR channels over hops of the path in a way that enables utilizing the IBFD capabilities of nodes. This widely used approach suffers a number of shortcomings; First, it suffers high computational complexity, as many formulations are NP hard. Second, it suffers high dimensionality, since many formulations involve large number of decision variables and constraints. Third, it suffers the infeasibility problem, since an infeasible instance of the formulated problem will lead to zero end-to-end throughput. In this paper, we address these challenges by proposing the multi-mode full-duplex Dijkstra (MMFDD) algorithm for path selection/channel assignment over multihop IBFD CR-IoT networks. By employing the well established Dijkstra algorithm in the proposed solution, we circumvent the complexity and high dimensionality issues. Further, the proposed algorithm solves the infeasibility problem employing mode duality. Through simulation experiments, we demonstrate significant performance gains achieved by the proposed dual-mode algorithm compared to existing algorithms in the literature.