Abstract:
Traditional studies on Instantly Decodable Network Coding (IDNC) focus on optimizing IDNC metrics, i.e., completion time or decoding delay, in broadcast scenarios in whic...Show MoreMetadata
Abstract:
Traditional studies on Instantly Decodable Network Coding (IDNC) focus on optimizing IDNC metrics, i.e., completion time or decoding delay, in broadcast scenarios in which all user-devices (UDs) want the same files. The problem of joint optimization over two interdependent parameters, i.e., transmitting user-devices (UDs) and IDNC was traditionally tackled by finding the set of feasible cooperation between UDs. This, however, requires high computational complexity, which is not feasible. This work, instead, develops low complexity, yet optimal, solution to the problem using graph theory in practical multicast scenarios where UDs are interested in different subsets of files. Specifically, the proposed method studies the condition for generating important UDs’ feasible cooperation that can minimize the IDNC metric under investigation while considering the effect of unwanted files on the performance of IDNC schemes for multicast sessions. Numerical results show that the proposed method outperforms the benchmark method in terms of completion time and decoding delay with significant reduction in the computational complexity.
Published in: IEEE Wireless Communications Letters ( Volume: 10, Issue: 11, November 2021)