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In this paper, we consider the problem of minimizing the multicast decodingdelay of generalized instantly decodable network coding (G-IDNC) overpersistent forward and feedback erasure channels with feedback intermittence.In such an environment, the sender does not always receive acknowledgement fromthe receivers after each transmission. Moreover, both the forward and feedbackchannels are subject to persistent erasures, which can be modelled by a twostate (good and bad states) Markov chain known as Gilbert-Elliott channel(GEC). Due to such feedback imperfections, the sender is unable to determinesubsequent instantly decodable packets combination for all receivers. Giventhis harsh channel and feedback model, we first derive expressions for theprobability distributions of decoding delay increments and then employ theseexpressions in formulating the minimum decoding problem in such environment asa maximum weight clique problem in the G-IDNC graph. We also show that theproblem formulations in simpler channel and feedback models are special casesof our generalized formulation. Since this problem is NP-hard, we design agreedy algorithm to solve it and compare it to blind approaches proposed inliterature. Through extensive simulations, our adaptive algorithm is shown tooutperform the blind approaches in all situations and to achieve significantimprovement in the decoding delay, especially when the channel is highlypersistent

Delay Minimization for Instantly Decodable Network Coding in Persistent Channels with Feedback Intermittence