Age of Information Analysis of Mobile Edge Computer with Layer-coded HARQ

Age of information (AoI) is a crucial metric to measure the information freshness in the real-time remote monitoring system. This work proposes a novel IoT status update model with the assistance of a mobile edge computer (MEC), which consists of a source (S), an access point (AP), an information receiver (IR), and the MEC with K buffers that are indexed from 1 to K. The status updates at source randomly arrive according to Poisson process of rate λ. The paper employs the layer-code Hybrid Automatic Repeat Request (L-HARQ) protocol to deal with the information freshness. The status update is decoded at the AP first. If the decoding fails, the packets are stored in the MEC buffers according to the order of increasing indexes until a successful feedforward decoding occurs. Then, the MEC performs the backtrack decoding to successively recover previously stored packets by using the L-HARQ framework. If a backtrack decoding failure occurs, the remaining ones are discarded. The backtrack decoding service at MEC follows another Poisson process with rate λ<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">B</inf>. This work employs the stochastic hybrid system (SHS) framework to derive the average AoI. At the same time, since the number of buffers is limited, this work proposes a circle-shift preemption policy to prevent packet overflow, which is the mixing packet in the (K −1)-th buffer is replaced by the one in the K-th buffer, and the new mixing packet is stored in the K-th buffer. The present numerical results validate the derivations and correctness.