Symbol-Level GRAND for High-Order Modulation over Flat Fading Channels

Guessing random additive noise decoding (GRAND) is a noise-centric decoding method, which is suitable for ultra-reliable low-latency communications, as it supports high-rate error correction codes that generate short-length codewords. GRAND estimates transmitted codewords by guessing the error patterns that altered them during transmission. The guessing process requires the generation and testing of error patterns that are arranged in increasing order of Hamming weight. This approach is fitting for binary transmission over additive white Gaussian noise channels. This letter considers transmission of coded and modulated data over flat fading channels and proposes a variant of GRAND, which leverages information on the modulation scheme and the fading channel. In the core of the proposed variant, referred to as symbol-level GRAND, is an analytical expression that computes the probability of occurrence of an error pattern and determines the order with which error patterns are tested. Simulation results demonstrate that symbol-level GRAND produces estimates of the transmitted codewords notably faster than the original GRAND at the cost of a small increase in memory requirements.Comment: 5 pages, 5 figures, 1 tabl

Symbol-Level Noise-Guessing Decoding with Antenna Sorting for URLLC Massive MIMO

Supporting ultra-reliable and low-latency communication (URLLC) is a challenge in current wireless systems. Channel codes that generate large codewords improve reliability but necessitate the use of interleavers, which introduce undesirable latency. Only short codewords can eliminate the requirement for interleaving and reduce decoding latency. This paper suggests a coding and decoding method which, when combined with the high spectral efficiency of spatial multiplexing, can provide URLLC over a fading channel. Random linear coding and high-order modulation are used to transmit information over a massive multiple-input multiple-output (mMIMO) channel, followed by zero-forcing detection and guessing random additive noise decoding (GRAND) at a receiver. A variant of GRAND, called symbol-level GRAND, originally proposed for single-antenna systems that employ high-order modulation schemes, is generalized to spatial multiplexing. The paper studies the impact of the orthogonality defect of the underlying mMIMO lattice on symbol-level GRAND, and proposes to leverage side-information that comes from the mMIMO channel-state information and relates to the reliability of each receive antenna. This induces an antenna sorting step, which further reduces decoding complexity by over 80\% when compared to bit-level GRAND

URLLC with coded massive MIMO via random linear codes and GRAND

A present challenge in wireless communications is the assurance of ultra-reliable and low-latency communication (URLLC). While the reliability aspect is well known to be improved by channel coding with long codewords, this usually implies using interleavers, which introduce undesirable delay. Using short codewords is a needed change to minimizing the decoding delay. This work proposes the combination of a coding and decoding scheme to be used along with spatial signal processing as a means to provide URLLC over a fading channel. The paper advocates the use of random linear codes (RLCs) over a massive MIMO (mMIMO) channel with standard zero-forcing detection and guessing random additive noise decoding (GRAND). The performance of several schemes is assessed over a mMIMO flat fading channel. The proposed scheme greatly outperforms the equivalent scheme using 5G’s polar encoding and decoding for signal-to-noise ratios (SNR) of interest. While the complexity of the polar code is constant at all SNRs, using RLCs with GRAND achieves much faster decoding times for most of the SNR range, further reducing latency.info:eu-repo/semantics/acceptedVersio

URLLC with Coded Massive MIMO via Random Linear Codes and GRAND

A present challenge in wireless communications is the assurance of ultra-reliable and low-latency communication (URLLC). While the reliability aspect is well known to be improved by channel coding with long codewords, this usually implies using interleavers, which introduce undesirable delay. Using short codewords is a needed change to minimizing the decoding delay. This work proposes the combination of a coding and decoding scheme to be used along with spatial signal processing as a means to provide URLLC over a fading channel. The paper advocates the use of random linear codes (RLCs) over a massive MIMO (mMIMO) channel with standard zero-forcing detection and guessing random additive noise decoding (GRAND). The performance of several schemes is assessed over a mMIMO flat fading channel. The proposed scheme greatly outperforms the equivalent scheme using 5G's polar encoding and decoding for signal-to-noise ratios (SNR) of interest. While the complexity of the polar code is constant at all SNRs, using RLCs with GRAND achieves much faster decoding times for most of the SNR range, further reducing latency

Optimizing positional scoring rules for rank aggregation

Nowadays, several crowdsourcing projects exploit social choice methods for computing an aggregate ranking of alternatives given individual rankings provided by workers. Motivated by such systems, we consider a setting where each worker is asked to rank a fixed (small) number of alternatives and, then, a positional scoring rule is used to compute the aggregate ranking. Among the apparently infinite such rules, what is the best one to use? To answer this question, we assume that we have partial access to an underlying true ranking. Then, the important optimization problem to be solved is to compute the positional scoring rule whose outcome, when applied to the profile of individual rankings, is as close as possible to the part of the underlying true ranking we know. We study this fundamental problem from a theoretical viewpoint and present positive and negative complexity results and, furthermore, complement our theoretical findings with experiments on real-world and synthetic data

Quantifying Acoustic and Pressure Sensing for In-Pipe Leak Detection

Experiments were carried out to study the effectiveness of using inside-pipe measurements for leak detection in plastic pipes. Acoustic and pressure signals due to simulated leaks, opened to air, are measured and studied for designing a detection system to be deployed inside water networks of 100 mm (4 inch) pipe size. Results showed that leaks as small as 2 l/min can be detected using both hydrophone and dynamic pressure transducer under low pipe flow rates. The ratio between pipe flow rate and leak flow rate seems to be more important than the absolute value of leak flow. Increasing this ratio resulted in diminishing and low frequency leak signals. Sensor location and directionality, with respect to the leak, are important in acquiring clean signal.King Fahd University of Petroleum and Mineral

Generalized interfacial energy and size effects in composites

The objective of this contribution is to explain the size effect in composites due to the interfacial energy between the constituents of the underlying microstructure. The generalized interface energy accounts for both jumps of the deformation as well as the stress across the interface. The cohesive zone and elastic interface are only two limit cases of the general interface model. A closed form analytical solution is derived to compute the effective interface-enhanced material response. Our novel analytical solution is in excellent agreement with the numerical results obtained from the finite element method for a broad variety of parameters and dimensions. A remarkable observation is that the notion of size effect is theoretically bounded verified by numerical examples. Thus, the gain or loss via reducing the dimensions of the microstructure is limited to certain ultimate values, immediately relevant for designing nano-composites. © 2017 Elsevier Lt

On the Temporality of Introducing Code Technical Debt

Code Technical Debt (TD) is intentionally or unintentionally created when developers introduce inefficiencies in the codebase. This can be attributed to various reasons such as heavy work-load, tight delivery schedule, unawareness of good practices, etc. To shed light into the context that leads to technical debt accumulation, in this paper we investigate: (a) the temporality of code technical debt introduction in new methods, i.e., whether the introduction of technical debt is stable across the lifespan of the project, or if its evolution presents spikes; and (b) the relation of technical debt introduction and the development team’s workload in a given period. To answer these questions, we perform a case study on twenty-seven Apache projects, and inspect the number of Technical Debt Items introduced in 6-month sliding temporal windows. The results of the study suggest that: (a) overall, the number of Technical Debt Items introduced through new code is a stable metric, although it presents some spikes; and (b) the number of commits performed is not strongly correlated to the number of introduced Technical Debt Items

Interactions of the potent synthetic AT1 antagonist analog BV6 with membrane bilayers and mesoporous silicate matrices

The present work describes the drug:membrane interactions and a drug delivery system of the novel potent AT1 blocker BV6. This designed analog has most of the pharmacological segments of losartan and an additional biphenyltetrazole moiety resulting in increased lipophilicity. We found that BV6:membrane interactions lead to compact bilayers that may in part explain its higher in vitro activity compared to losartan since such environment may facilitate its approach to AT1 receptor. Its high docking score to AT1 receptor stems from more hydrophobic interactions compared to losartan. X-ray powder diffraction (XRPD) and thermogravimetric analysis (TGA) have shown that BV6 has a crystalline form that is not decomposed completely up to 600 °C. These properties are desirable for a drug molecule. BV6 can also be incorporated into a mesoporous silicate drug-delivery matrix SBA-15. The properties of the obtained drug-delivery system have been inspected by XRD, 13C CP/MAS, TGA and nitrogen sorption experiments