Feedback Communication Systems with Limitations on Incremental Redundancy

This paper explores feedback systems using incremental redundancy (IR) with noiseless transmitter confirmation (NTC). For IR-NTC systems based on {\em finite-length} codes (with blocklength $N$) and decoding attempts only at {\em certain specified decoding times}, this paper presents the asymptotic expansion achieved by random coding, provides rate-compatible sphere-packing (RCSP) performance approximations, and presents simulation results of tail-biting convolutional codes. The information-theoretic analysis shows that values of $N$ relatively close to the expected latency yield the same random-coding achievability expansion as with $N = \infty$. However, the penalty introduced in the expansion by limiting decoding times is linear in the interval between decoding times. For binary symmetric channels, the RCSP approximation provides an efficiently-computed approximation of performance that shows excellent agreement with a family of rate-compatible, tail-biting convolutional codes in the short-latency regime. For the additive white Gaussian noise channel, bounded-distance decoding simplifies the computation of the marginal RCSP approximation and produces similar results as analysis based on maximum-likelihood decoding for latencies greater than 200. The efficiency of the marginal RCSP approximation facilitates optimization of the lengths of incremental transmissions when the number of incremental transmissions is constrained to be small or the length of the incremental transmissions is constrained to be uniform after the first transmission. Finally, an RCSP-based decoding error trajectory is introduced that provides target error rates for the design of rate-compatible code families for use in feedback communication systems.Comment: 23 pages, 15 figure

Anthropogenic Impact on Tropical Perennial River in South India: Snapshot of Carbon Dynamics and Bacterial Community Composition

Riverine systems play an important role in the global carbon cycle, and they are considered hotspots for bacterial activities such as organic matter decomposition. However, our knowledge about these processes in tropical or subtropical regions is limited. The aim of this study was to investigate anthropogenically induced changes of water quality, the distribution of selected pharmaceuticals, and the effects of pollution on greenhouse gas concentrations and bacterial community composition along the 800 km long Cauvery river, the main river serving as a potable and irrigation water supply in Southern India. We found that in situ measured pCO₂ and pCH₄ concentrations were supersaturated relative to the atmosphere and ranged from 7.9 to 168.7 µmol L⁻¹ , and from 0.01 to 2.76 µmol L⁻¹ , respectively. Pharmaceuticals like triclosan, carbamazepine, ibuprofen, naproxen, propylparaben, and diclofenac exceeded warning limits along the Cauvery. Proteobacteria was the major phylum in all samples, ranging between 26.1% and 82.2% relative abundance, and it coincided with the accumulation of nutrients in the flowing water. Results emphasized the impact of industrialization and increased population density on changes in water quality, riverine carbon fluxes, and bacterial community structure

Causal effect of plasminogen activator inhibitor type 1 on coronary heart disease

Background--Plasminogen activator inhibitor type 1 (PAI-1) plays an essential role in the fibrinolysis system and thrombosis. Population studies have reported that blood PAI-1 levels are associated with increased risk of coronary heart disease (CHD). However, it is unclear whether the association reflects a causal influence of PAI-1 on CHD risk. Methods and Results--To evaluate the association between PAI-1 and CHD, we applied a 3-step strategy. First, we investigated the observational association between PAI-1 and CHD incidence using a systematic review based on a literature search for PAI-1 and CHD studies. Second, we explored the causal association between PAI-1 and CHD using a Mendelian randomization approach using summary statistics from large genome-wide association studies. Finally, we explored the causal effect of PAI-1 on cardiovascular risk factors including metabolic and subclinical atherosclerosis measures. In the systematic meta-analysis, the highest quantile of blood PAI-1 level was associated with higher CHD risk comparing with the lowest quantile (odds ratio=2.17; 95% CI: 1.53, 3.07) in an age- and sex-adjusted model. The effect size was reduced in studies using a multivariable-adjusted model (odds ratio=1.46; 95% CI: 1.13, 1.88). The Mendelian randomization analyses suggested a causal effect of increased PAI-1 level on CHD risk (odds ratio=1.22 per unit increase of log-transformed PAI-1; 95% CI: 1.01, 1.47). In addition, we also detected a causal effect of PAI-1 on elevating blood glucose and high-density lipoprotein cholesterol. Conclusions--Our study indicates a causal effect of elevated PAI-1 level on CHD risk, which may be mediated by glucose dysfunction

Is feedback a performance equalizer of classic and modern codes

Abstract—It is well known that in general, feedback cannot increase the capacity of a discrete memoryless channel. However, it can help simplify the complexity of encoding and decoding. Schalkwijk and Kailath (1966) developed a class of block codes for Gaussian channels with ideal feedback. They showed that the probability of decoding error decreases as a second-order exponent in block length for rates below capacity. This paper proposes a coding scheme with ideal feedback and is applied to punctured convolutional codes and punctured Turbo codes. Our results seem to indicate that feedback largely equalizes the performance of classic (convolutional) codes and modern (turbo, LDPC) codes. I