A heuristic for fair dynamic resource allocation in overloaded OFDMA systems

Abstract

OFDMA is a popular coding scheme for mobile wireless communications. In OFDMA, one must allocate the available resources (bandwidth and power) dynamically, as user requests arrive and depart in a stochastic manner. Several exact and heuristic methods exist to do this, but they all perform poorly in the "over-loaded" case, in which the user demand is close to or exceeds the system capacity. To address this case, we present a dynamic local search heuristic. A particular feature of our heuristic is that it takes fairness into consideration. Simulations on realistic data show that our heuristic is fast enough to be used in real-time, and consistently delivers allocations of good quality.

Speech Dialogue System-Based Environmental Resource Allocation and Online English Teaching and IoT Applications

“…The voice dialogue system and online English teaching are not perfect, and this type of teaching method has not been widely popularized. Most of them use conventional teaching methods [11][12][13]. At this stage, more conventional teaching methods include teaching methods based on deep learning, integrating teaching resources by using deep learning related technologies, establishing the relationship between teaching resources and disciplines by using learning methods with the characteristics of fragmentation, miniaturization and multitasking, and obtaining accurate teaching through repeated extraction and iteration of teaching resources to realize personalized learning.…”