  This letter considers temporal-correlated massive access, where each device,
once activated, is likely to transmit continuously over several consecutive
frames. Motivated by that the device activity at each frame is correlated to
not only its previous frame but also its next frame, we propose a double-sided
information (DSI) aided joint activity detection and channel estimation
algorithm based on the approximate message passing (AMP) framework. The DSI is
extracted from the estimation results in a sliding window that contains the
target detection frame and its previous and next frames. The proposed algorithm
demonstrates superior performance over the state-of-the-art methods.
