TY - GEN
T1 - Delay reduction in persistent erasure channels for generalized instantly decodable network coding
AU - Sorour, Sameh
AU - Aboutorab, Neda
AU - Sadeghi, Parastoo
AU - Karim, Mohammad Shahriar
AU - Al-Naffouri, Tareq Y.
AU - Alouini, Mohamed-Slim
N1 - KAUST Repository Item: Exported on 2020-10-01
PY - 2013/6
Y1 - 2013/6
N2 - In this paper, we consider the problem of minimizing the decoding delay of generalized instantly decodable network coding (G-IDNC) in persistent erasure channels (PECs). By persistent erasure channels, we mean erasure channels with memory, which are modeled as a Gilbert-Elliott two-state Markov model with good and bad channel states. In this scenario, the channel erasure dependence, represented by the transition probabilities of this channel model, is an important factor that could be exploited to reduce the decoding delay. We first formulate the G-IDNC minimum decoding delay problem in PECs as a maximum weight clique problem over the G-IDNC graph. Since finding the optimal solution of this formulation is NP-hard, we propose two heuristic algorithms to solve it and compare them using extensive simulations. Simulation results show that each of these heuristics outperforms the other in certain ranges of channel memory levels. They also show that the proposed heuristics significantly outperform both the optimal strict IDNC in the literature and the channel-unaware G-IDNC algorithms. © 2013 IEEE.
AB - In this paper, we consider the problem of minimizing the decoding delay of generalized instantly decodable network coding (G-IDNC) in persistent erasure channels (PECs). By persistent erasure channels, we mean erasure channels with memory, which are modeled as a Gilbert-Elliott two-state Markov model with good and bad channel states. In this scenario, the channel erasure dependence, represented by the transition probabilities of this channel model, is an important factor that could be exploited to reduce the decoding delay. We first formulate the G-IDNC minimum decoding delay problem in PECs as a maximum weight clique problem over the G-IDNC graph. Since finding the optimal solution of this formulation is NP-hard, we propose two heuristic algorithms to solve it and compare them using extensive simulations. Simulation results show that each of these heuristics outperforms the other in certain ranges of channel memory levels. They also show that the proposed heuristics significantly outperform both the optimal strict IDNC in the literature and the channel-unaware G-IDNC algorithms. © 2013 IEEE.
UR - http://hdl.handle.net/10754/564758
UR - http://ieeexplore.ieee.org/document/6692503/
UR - http://www.scopus.com/inward/record.url?scp=84893579618&partnerID=8YFLogxK
U2 - 10.1109/VTCSpring.2013.6692503
DO - 10.1109/VTCSpring.2013.6692503
M3 - Conference contribution
SN - 9781467363372
BT - 2013 IEEE 77th Vehicular Technology Conference (VTC Spring)
PB - Institute of Electrical and Electronics Engineers (IEEE)
ER -