  Interference mitigation is a major design challenge in wireless
systems,especially in the context of ultra-reliable low-latency communication
(URLLC) services. Conventional average-based interference management schemes
are not suitable for URLLC as they do not accurately capture the tail
information of the interference distribution. This letter proposes a novel
interference prediction algorithm that considers the entire interference
distribution instead of only the mean. The key idea is to model the
interference variation as a discrete state space discrete-time Markov chain.
The state transition probability matrix is then used to estimate the state
evolution in time, and allocate radio resources accordingly. The proposed
scheme is found to meet the target reliability requirements in a low-latency
single-shot transmission system considering realistic system assumptions, while
requiring only ~25% more resources than the optimum case with perfect
interference knowledge.
