Backhaul-Capacity-Aware Interference Mitigation Framework in 6G Cellular Internet of Things

Abstract

To meet the increasing demands for wide-band communications and network densification, a new paradigm of millimeter-wave (mmWave)-enabled integrated access and backhaul (IAB) is urgently needed in the sixth-generation (6G) cellular Internet-of-Things (IoT) network. However, the mmWave-enabled IAB technology brings new challenges on network capacity in terms of the differentiated backhaul capacities of small-cell base stations and the various interferences among access links in the 6G cellular IoT network. Therefore, this article proposes a joint traffic load-balancing and interference mitigation framework to maximize the network capacity for 6G cellular IoT services. A novel two-step resource allocation scheme is designed by optimizing the user equipment association and the transmit power allocation (PA), iteratively. Moreover, to minimize both the backhaul burden and the interference, a novel backhaul capacity and interference-aware matching utility function using the many-to-many matching model is designed to measure the interference penalty and the backhaul capacity. By transforming the nonconvex PA subproblem into a convex problem using the successive convex approximation method, both upper and lower bounds of the optimal transmit power are theoretically achieved. Simulation results prove that the proposed algorithms can significantly improve the network sum rate by 71.9% compared to the conventional algorithms, and the successful transmission probability can be well guaranteed.