1,058 research outputs found
On the Performance of Short Block Codes over Finite-State Channels in the Rare-Transition Regime
As the mobile application landscape expands, wireless networks are tasked
with supporting different connection profiles, including real-time traffic and
delay-sensitive communications. Among many ensuing engineering challenges is
the need to better understand the fundamental limits of forward error
correction in non-asymptotic regimes. This article characterizes the
performance of random block codes over finite-state channels and evaluates
their queueing performance under maximum-likelihood decoding. In particular,
classical results from information theory are revisited in the context of
channels with rare transitions, and bounds on the probabilities of decoding
failure are derived for random codes. This creates an analysis framework where
channel dependencies within and across codewords are preserved. Such results
are subsequently integrated into a queueing problem formulation. For instance,
it is shown that, for random coding on the Gilbert-Elliott channel, the
performance analysis based on upper bounds on error probability provides very
good estimates of system performance and optimum code parameters. Overall, this
study offers new insights about the impact of channel correlation on the
performance of delay-aware, point-to-point communication links. It also
provides novel guidelines on how to select code rates and block lengths for
real-time traffic over wireless communication infrastructures
A two-level Markov model for packet loss in UDP/IP-based real-time video applications targeting residential users
The packet loss characteristics of Internet paths that include residential broadband links are not well understood, and there are no good models for their behaviour. This compli- cates the design of real-time video applications targeting home users, since it is difficult to choose appropriate error correction and concealment algorithms without a good model for the types of loss observed. Using measurements of residential broadband networks in the UK and Finland, we show that existing models for packet loss, such as the Gilbert model and simple hidden Markov models, do not effectively model the loss patterns seen in this environment. We present a new two-level Markov model for packet loss that can more accurately describe the characteristics of these links, and quantify the effectiveness of this model. We demonstrate that our new packet loss model allows for improved application design, by using it to model the performance of forward error correction on such links
Flow Control in Wireless Ad-hoc Networks
We are interested in maximizing the Transmission Control Protocol (TCP) throughput
between two nodes in a single cell wireless ad-hoc network. For this, we follow a
cross-layer approach by first developing an analytical model that captures the effect
of the wireless channel and the MAC layer to TCP. The analytical model gives the time
evolution of the TCP window size which is described by a stochastic differential equation
driven by a point process. The point process represents the arrival of acknowledgments
sent by the TCP receiver to the sender as part of the self-regulating mechanism of the flow
control protocol. Through this point process we achieve a cross-layer integration between
the physical layer, the MAC layer and TCP. The intervals between successive points describe
how the packet drops at the wireless channel and the delays because of retransmission at
the MAC layer affect the window size at the TCP layer. We fully describe the statistical
behavior of the point process by computing first the p.d.f. for the inter-arrival intervals and
then the compensator and the intensity of the process parametrized by the quantities that describe the MAC layer and the wireless channel.
To achieve analytical tractability we concentrate on the pure (unslotted) Aloha for the
MAC layer and the Gilbert-Elliott model for the channel. Although the Aloha protocol
is simpler than the more popular IEEE 802.11 protocol, it still exhibits the same exponential backoff mechanism which is a key factor for the performance of TCP in a wireless network. Moreover, another reason to study the Aloha protocol is that the protocol and its variants
gain popularity as they are used in many of today's wireless networks.
Using the analytical model for the TCP window size evolution, we try to increase the TCP throughput between two nodes in a single cell network. We want to achieve this by
implicitly informing the TCP sender of the network conditions. We impose this additional
constraint so we can achieve compatibility between the standard TCP and the optimized
version. This allows the operation of both protocol stacks in the same network.
We pose the optimization problem as an optimal stopping problem. For each packet
transmitted by the TCP sender to the network, an optimal time instance has to be
computed in the absence of an acknowledgment for this packet. This time instance
indicates when a timeout has to be declared for the packet. In the absence of an acknowledgment, if the sender waits long for declaring a timeout, the network is
underutilized. If the sender declares a timeout soon, it minimizes the transmission
rate. Because of the analytical intractability of the optimal stopping time problem,
we follow a Markov chain approximation method to solve the problem numerically
A Randomized Algorithm for the Capacity of Finite-State Channels
Inspired by ideas from the field of stochastic approximation, we propose a ran- domized algorithm to compute the capacity of a finite-state channel with a Markovian input. When the mutual information rate of the channel is concave with respect to the chosen parameterization, the proposed algorithm proves to be convergent to the ca- pacity of the channel almost surely with the derived convergence rate. We also discuss the convergence behavior of the algorithm without the concavity assumption.published_or_final_versio
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