The IEEE 802.16j standard has been proposed to triumph over the shadow fading and path attenuation problems in IEEE 802.16e networks by employing the multihop relay (MR) technology. Taking path selection and spatial reuse into account, numerous dynamic/heuristic scheduling algorithms have been presented for MR networks. Unfortunately, although these scheduling schemes can achieve high efficiency of resource utilization, almost all of their low time complexities considerably rely on expensive operations and sophisticated data structures. To maintain the simplicity and low time complexity of fixed-assignment scheduling while guaranteeing high resource utilization, this paper proposes a repacking and borrowing-based resource scheduling algorithm, RBRS, for IEEE 802.16j MR networks. In the repacking phase, a connection that is served via a direct path can be handed off to a cooperative path to release a part of its allocated base station (BS) resources. Since BS resources are shared by all connections within the BS coverage, repacking can increase the amount of available BS resources to serve the connection attempts that arrive at relay stations (RSs) currently under resource starvation. To complement repacking and further enhance the performance of RBRS, borrowing is applied. In the borrowing phase, over-loaded RSs are capable of borrowing resources from under-loaded RSs, further improving the resource utilization. Our main contributions are twofold: (1) to the best of our knowledge, this paper is the first effort in the literature to investigate the performance enhancement of repacking and borrowing operations for MR networks (including IEEE 802.16j); (2) both analytic and simulation models are developed to validate against each other and to study the performance of RBRS. The simulation results indicate that RBRS requires a low computational time which is comparable to that of fixed-assignment scheduling. Furthermore, by increasing available BS resources and balancing RS resources, RBRS shows near-optimal system capacity and throughput performance at the same time.