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Low-Complexity Scheduling for Delay Minimization in D2D Communications Using Network Coding
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DOI：10.1109/LCOMM.2021.3069941.png)
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Abstract
En 中文
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.
Keywords:
Delays
Decoding
Device-to-device communication
Minimization
Optimization
Complexity theory
Clustering algorithms
Device-to-device networks
clustering
IDNC graph
maximum weight clique
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