TY - GEN
T1 - Delivery delay analysis of network coded wireless broadcast schemes
AU - Fu, Amy
AU - Sadeghi, Parastoo
AU - Médard, Muriel
PY - 2012
Y1 - 2012
N2 - In this paper we study in-order packet delivery delay of two recently proposed network coded transmission schemes with applications in wireless broadcast. Unlike previous works where asymptotic behaviour of decoding or delivery delay was presented, we provide a general analysis of the three conditions under which in-order packet delivery is possible at a receiver: by 1) catching up with the sender, 2) receiving while a leader, and 3) chance decoding. We use a Markov model to represent the difference between the knowledge space of the sender and a receiver. For the first condition, we calculate the expected distribution of decoding cycle lengths under the Markov model. For the second condition, we propose to use a simplifying independent Markov model among receivers to shed light on the factors that determine the probability of receiving while a leader. Finally, we compare the chance decoding probabilities of two transmission schemes and a baseline random transmission algorithm to show that surprisingly (and fortunately) the probability of chance decoding is significant in one of the transmission schemes. We verify our analysis by extensive simulations and discuss the usefulness of our study for understanding and design of better transmission algorithms.
AB - In this paper we study in-order packet delivery delay of two recently proposed network coded transmission schemes with applications in wireless broadcast. Unlike previous works where asymptotic behaviour of decoding or delivery delay was presented, we provide a general analysis of the three conditions under which in-order packet delivery is possible at a receiver: by 1) catching up with the sender, 2) receiving while a leader, and 3) chance decoding. We use a Markov model to represent the difference between the knowledge space of the sender and a receiver. For the first condition, we calculate the expected distribution of decoding cycle lengths under the Markov model. For the second condition, we propose to use a simplifying independent Markov model among receivers to shed light on the factors that determine the probability of receiving while a leader. Finally, we compare the chance decoding probabilities of two transmission schemes and a baseline random transmission algorithm to show that surprisingly (and fortunately) the probability of chance decoding is significant in one of the transmission schemes. We verify our analysis by extensive simulations and discuss the usefulness of our study for understanding and design of better transmission algorithms.
UR - http://www.scopus.com/inward/record.url?scp=84864356883&partnerID=8YFLogxK
U2 - 10.1109/WCNC.2012.6214165
DO - 10.1109/WCNC.2012.6214165
M3 - Conference contribution
SN - 9781467304375
T3 - IEEE Wireless Communications and Networking Conference, WCNC
SP - 2236
EP - 2241
BT - 2012 IEEE Wireless Communications and Networking Conference, WCNC 2012
T2 - 2012 IEEE Wireless Communications and Networking Conference, WCNC 2012
Y2 - 1 April 2012 through 4 April 2012
ER -