Real-Time Dual-Process Remote Estimation With Integrated Multiaccess and HARQ

We propose real-time remote estimation of a dual-process status update system for mission-critical applications using nonorthogonal multiaccess (NOMA) and orthogonal multiaccess (OMA) techniques. We consider the finite block length regime so that, with OMA, the status updates of each process are transmitted using time slot sharing. Meanwhile, with NOMA, we use a power domain packet combining to allow simultaneous status updates of each process in each time slot. To compensate for the reliability loss due to short packet lengths and multiaccess, we utilize packet retransmission with hybrid automatic repeat request (HARQ). Specifically, we propose OMA-HARQ and NOMA-HARQ transmission control policies, where multiaccess resource sharing is jointly designed with HARQ. We propose dynamic and static scheduling policies by optimizing time-sharing or power-sharing ratios between sensors over time. The dynamic policy utilizes higher flexibility to optimize the reliability under restricted Age-of-Information (AoI), leading to the best estimation mean-squared-error (MSE) performance. We formulate and solve policy optimization problems, where both long-term average MSE and its variance minimization are the targets. We obtain optimal policies to minimize the composite objective function of costs of each process using the Markov decision process (MDP) framework and relative value iteration algorithm. An intensive simulation study shows significant performance improvement over existing approaches.