Average Age in Coordinate Decision-Making Wireless Systems Operating with FBL Codes

Computing, Communications and IoT Applications (ComComAp)

Abstract

Future Internet of Things (IoT) networks are expected to support low-latency communications, where transmissions are usually operating with finite blocklength (FBL) codes to satisfy the latency requirements. In such FBL regime, the packet decoding error probability becomes nonnegligible even if the coding rate is lower than the Shannon capacity, which requires a random number of retransmissions to achieve the reliability requirement. This actually introduces random (re)transmission delays to the packets, which makes the age/delay model characterization of such networks becomes interesting and challenging, especially for networks using the data packets for latency-sensitive decision-making. In this work, we consider an M/M/1/M update-and-decide system with two independent sources and estimate the timeliness of those received packets used for decisions. We measure the freshness (i.e., the age) of the received updates at decision epochs by using the age upon decisions (AuD). For multi-source system, coordinate decisions would be made based on the AuDs of updates from each source. Under the First-come-First-served (FCFS) policy, we derive the closed form expression for average AuD of each source and the average ages of coordinate decisions. We show that the average AuD of each source is large when its arrive rate is relatively large or small, and will be larger with the increasing of another source's packets generation rate. We also show that the age of coordinate decisions will achieve the minimum, when the total arrive rate of the system is approximately equal to the service rate. Our obtained results are also validated by Monte Carlo results.

Authors 5

1. Zhiwei Bao Aachen ISEK Research Area

   Wuhan University · RWTH Aachen University

   Affiliation as printed

   ISEK Research Area, RWTH, Aachen, Germany

   School of Electronic Information, Wuhan University, China

2. Yao Lin Zhu Aachen ISEK Research Area

   Wuhan University · RWTH Aachen University

   Affiliation as printed

   ISEK Research Area, RWTH, Aachen, Germany

   School of Electronic Information, Wuhan University, China

3. Yulin Hu Aachen ISEK Research Area

   Wuhan University · RWTH Aachen University

   Affiliation as printed

   ISEK Research Area, RWTH, Aachen, Germany

   School of Electronic Information, Wuhan University, China

4. Yunquan Dong

   Nanjing University of Information Science and Technology

   Affiliation as printed

   Nanjing University of Information Science & Technology, Nanjing, China

   Technology, Nanjing, China

5. Anke Schmeink Aachen ISEK Research Area

   RWTH Aachen University

   Affiliation as printed

   ISEK Research Area, RWTH, Aachen, Germany