Transmission Scheduling for Remote Estimation with Multi-packet Reception under Multi-Sensor Interference

In networked control systems, due to competing demands on bandwidth and energy constraints, sensor scheduling is an important problem for remote estimation and control tasks. Traditionally, a single sensor is scheduled in each resource block to avoid interference or collisions so that the probability of packet loss is reduced. However, receiving multiple packets from different sources under interference is routinely achieved in wireless networks using multi-packet reception techniques. In this work, we explore the problem of sensor scheduling for remote estimation when the estimator is able to simultaneously receive multiple packets. We use the typical signal-to-interference-and-noise-ratio (SINR) based capture model to compute the packet arrival probabilities. Then an optimal scheduling policy is determined by minimizing expected estimation error covariance subject to a constraint on the average number of total transmissions. In the case of two sensors, for a scalar system and for a decoupled two-dimensional system, we show that allowing multiple simultaneous transmissions can improve the quality of the estimation achieving lower energy consumptions and we provide structural results on the optimal policies. Numerical results illustrate the benefits of multi-packet reception in remote estimation. Copyright (C) 2020 The Authors.