A multi-armed bandit that discretizes and searches non-uniform preamble access probabilities comes within about 5% of an SQP-optimized allocation for high-priority RACH throughput, but its reward scaling depends on the unknown device count.
Modeling and analysis of random access channels with bursty arrivals in OFDMA wireless networks,
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Access Probability Optimization in RACH: A Multi-Armed Bandits Approach
A multi-armed bandit that discretizes and searches non-uniform preamble access probabilities comes within about 5% of an SQP-optimized allocation for high-priority RACH throughput, but its reward scaling depends on the unknown device count.