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Data Freshness Optimization in Relaying Network Operating with Finite Blocklength Codes

Xiaopeng Yuan, Yao Zhu, Hao Jiang, Yulin Hu, Anke Schmeink

20212021 IEEE Global Communications Conference (GLOBECOM)16 citationsDOI

Abstract

In this paper, we focus on a relaying network working with a decode-and-forward (DF) principle. A source reports latency-critical information updates to the destination with the help of the relay under periodic request, while this two-hop transmission is operating with finite blocklength (FBL) codes. To evaluate the data freshness at destination, we characterize the average age-of-information (AoI) of the two-hop relaying. Based on the characterization, we consider a problem minimizing the average AoI by jointly optimizing the blocklengths allocated to both hops. To address this non-convex problem, we construct a tight convex approximation for the average AoI at a feasible local point (values of the two blocklengths). Then, we propose an efficient algorithm which iteratively applies the convex approximation, solves the approximated convex problem and updates the local point until a convergence to a suboptimum. Via numerical results, we validate the convergence of the proposed iterative algorithm and confirm the high performance and high efficiency of the proposed solution. The performance advantage of relaying in improving the data freshness is also shown in comparison to direct transmission.

Topics & Concepts

Computer scienceRelayConvex optimizationMathematical optimizationConvergence (economics)Hop (telecommunications)Focus (optics)Regular polygonTransmission (telecommunications)Optimization problemIterative methodAlgorithmComputer networkMathematicsTelecommunicationsOpticsEconomic growthGeometryQuantum mechanicsPower (physics)EconomicsPhysicsAge of Information OptimizationIoT Networks and ProtocolsAdvanced MIMO Systems Optimization