7 research outputs found
Performance Analysis of Block Codes over Finite-state Channels in Delay-sensitive Communications
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 dissertation seeks to characterize the performance of block codes over finite-state channels with memory and also evaluate their queueing performance under different encoding/decoding schemes.
In particular, a fading formulation is considered where a discrete channel with correlation over time introduces errors. For carefully selected channel models and arrival processes, a tractable Markov structure composed of queue length and channel state is identified. This facilitates the analysis of the stationary behavior of the system, leading to evaluation criteria such as bounds on the probability of the queue exceeding a threshold. Specifically, this dissertation focuses on system models with scalable arrival profiles based on Poisson processes, and finite-state memory channels. These assumptions permit the rigorous comparison of system performance for codes with arbitrary block lengths and code rates. Based on this characterization, it is possible to optimize code parameters for delay-sensitive applications over various channels. Random codes and BCH codes are then employed as means to study the relationship between code-rate selection and the queueing performance of point-to-point data links. The introduced methodology offers a new perspective on the joint queueing-coding analysis for finite-state channels, and is supported by numerical simulations.
Furthermore, 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. An analysis framework is presented where channel dependencies within and across code words are preserved. The results are subsequently integrated into a queueing formulation. It is shown that for current formulation, the performance analysis based on upper bounds provides a good estimate of both the system performance and the optimum code parameters. Overall, this study offers new insights about the impact of channel correlation on the performance of delay-aware communications and provides novel guidelines to select optimum code rates and block lengths
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
Albuminuria and its correlates in an Iranian type 2 diabetic population
Abstract Objective To study the prevalence and correlates of increased urinary albumin excretion (UAE) in an Iranian type 2 diabetic population. Methods Over a one year period since October 2002, 400 consecutive type 2 diabetic patients referred to an outpatient diabetes clinic, were enrolled in a cross sectional study. Subjects had no history of renal impairment or overt proteinuria. Data concerning demographic characteristics and cardiovascular risk factors were recorded and height, weight and blood pressure were measured. Glucose, cholesterol, HDL-C, LDL-C, triglyceride, apoprotein B, lipoprotein a, creatinine, and HbA1c were measured in fasting blood samples. Overnight twelve-hour UAE were assessed by immunoturbidometry method. Regression analyses were employed to determine the correlates of UAE. Results Out of 400 patients, 156 (40%) subjects had increased UAE (UAE ≥ 30 mg/24 hour). The UAE was higher in males compared to females (145.5 vs. 72.1 mg/day; p Conclusion In this study, increased UAE was considerably frequent among type 2 diabetic patients without any significant history of renal dysfunction. Albuminuria was found to be associated with dyslipidemia (low HDL-C), long duration of diabetes, and uncontrolled glycemia revealed by higher HbA1c.</p