  In linear wireless networked control systems whose control is based on the
system state's noisy and delayed observations, an accurate functional
relationship is derived between the estimation error and the observations'
freshness and precision. The proposed functional relationship is then applied
to formulate and solve the problem of scheduling among different wireless links
from multiple noisy sensors, where a sliding window algorithm is further
proposed. The algorithm's simulation results show significant performance gain
over existing policies, even in scenarios that require high freshness or
precision of observations.
