Online Network Coding for Time-Division Duplexing
We study an online random linear network coding approach for time division duplexing (TDD) channels under Poisson arrivals. We model the system as a bulk-service queue with variable bulk size and with feedback, i.e., when a set of packets are serviced at a given time, they might be reintroduced...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
Institute of Electrical and Electronics Engineers
2010
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| Online Access: | http://hdl.handle.net/1721.1/60309 https://orcid.org/0000-0003-4059-407X |
| Summary: | We study an online random linear network coding
approach for time division duplexing (TDD) channels under
Poisson arrivals. We model the system as a bulk-service queue
with variable bulk size and with feedback, i.e., when a set of
packets are serviced at a given time, they might be reintroduced
to the queue to form part of the next service batch. We show
that there is an optimal number of coded data packets that
the sender should transmit back-to-back before stopping to
wait for an acknowledgement from the receiver. This number
depends on the latency, probability of packet erasure, degrees
of freedom at the receiver, the size of the coding window, and
the arrival rate of the Poisson process. Random network coding
is performed across a moving window of packets that depends
on the packets in the queue, design constraints on the window
size, and the feedback sent from the receiver. We study the
mean time between generating a packet at the source and it
being “seen”, but not necessarily decoded, at the receiver. We
also analyze the mean time between a decoding event and the
next, defined as the decoding of all the packets that have been
previously “seen” and those packets involved in the current
window of packets. Inherently, a decoding event implies an inorder
decoding of a batch of data packets. We present numerical
results illustrating the trade-off between mean delay and mean
time between decoding events. |
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