Low-Complexity Scheduling for Delay Minimization in D2D Communications using Network Coding

Abstract

In this letter, we consider the decoding delay minimizing problem for delivering a frame of packets to a set of user-devices (UDs) using instantly decodable network coding (IDNC). In the considered device-to-device (D2D) network, UDs have limited coverage zones that represent clusters and can speed up the delivery of the requested packets of other UDs by sending IDNC packets. The decoding delay minimization problem is a joint optimization problem of selecting the transmitting UDs and their coding decisions. In this work, we propose a low complexity, yet optimal, solution to the decoding delay minimization problem using graph pruning method. Our proposed innovative method introduces a sequential pruning algorithm that judiciously generates clusters that are certainly contributing to the network while simultaneously designing a new multi-layer IDNC graph. We also prove that the optimal solution to the problem can be achieved by the generated clusters by our proposed algorithm. Numerical results reveal that the proposed solution significantly reduces the computational complexity compared to the existing method with similar decoding delay performance.

Additional Information

© 2021 IEEE. Manuscript received February 20, 2021; revised March 22, 2021 and March 27, 2021; accepted March 28, 2021. Date of publication March 31, 2021; date of current version July 10, 2021. This work was supported by the Discovery Grant of Natural Science and Engineering Research Council (NSERC), Canada. The associate editor coordinating the review of this letter and approving it for publication was R. Aguero.

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