Capacity Bounds for the KK-User Gaussian Interference Channel

The capacity region of the $K$-user Gaussian interference channel (GIC) is a long-standing open problem and even capacity outer bounds are little known in general. A significant progress on degrees-of-freedom (DoF) analysis, a first-order capacity approximation, for the $K$-user GIC has provided new important insights into the problem of interest in the high signal-to-noise ratio (SNR) limit. However, such capacity approximation has been observed to have some limitations in predicting the capacity at \emph{finite} SNR. In this work, we develop a new upper-bounding technique that utilizes a new type of genie signal and applies \emph{time sharing} to genie signals at $K$ receivers. Based on this technique, we derive new upper bounds on the sum capacity of the three-user GIC with constant, complex channel coefficients and then generalize to the $K$-user case to better understand sum-rate behavior at finite SNR. We also provide closed-form expressions of our upper bounds on the capacity of the $K$-user symmetric GIC easily computable for \emph{any} $K$. From the perspectives of our results, some sum-rate behavior at finite SNR is in line with the insights given by the known DoF results, while some others are not. In particular, the well-known $K/2$ DoF achievable for almost all constant real channel coefficients turns out to be not embodied as a substantial performance gain over a certain range of the cross-channel coefficient in the $K$-user symmetric real case especially for \emph{large} $K$. We further investigate the impact of phase offset between the direct-channel coefficient and the cross-channel coefficients on the sum-rate upper bound for the three-user \emph{complex} GIC. As a consequence, we aim to provide new findings that could not be predicted by the prior works on DoF of GICs.Comment: Presented in part at ISIT 2015, submitted to IEEE Transactions on Information Theory on July 2015, and revised on January 201

Fundamental Limits in Correlated Fading MIMO Broadcast Channels: Benefits of Transmit Correlation Diversity

We investigate asymptotic capacity limits of the Gaussian MIMO broadcast channel (BC) with spatially correlated fading to understand when and how much transmit correlation helps the capacity. By imposing a structure on channel covariances (equivalently, transmit correlations at the transmitter side) of users, also referred to as \emph{transmit correlation diversity}, the impact of transmit correlation on the power gain of MIMO BCs is characterized in several regimes of system parameters, with a particular interest in the large-scale array (or massive MIMO) regime. Taking the cost for downlink training into account, we provide asymptotic capacity bounds of multiuser MIMO downlink systems to see how transmit correlation diversity affects the system multiplexing gain. We make use of the notion of joint spatial division and multiplexing (JSDM) to derive the capacity bounds. It is advocated in this paper that transmit correlation diversity may be of use to significantly increase multiplexing gain as well as power gain in multiuser MIMO systems. In particular, the new type of diversity in wireless communications is shown to improve the system multiplexing gain up to by a factor of the number of degrees of such diversity. Finally, performance limits of conventional large-scale MIMO systems not exploiting transmit correlation are also characterized.Comment: 29 pages, 8 figure

On the High-SNR Capacity of the Gaussian Interference Channel and New Capacity Bounds

The best outer bound on the capacity region of the two-user Gaussian Interference Channel (GIC) is known to be the intersection of regions of various bounds including genie-aided outer bounds, in which a genie provides noisy input signals to the intended receiver. The Han and Kobayashi (HK) scheme provides the best known inner bound. The rate difference between the best known lower and upper bounds on the sum capacity remains as large as 1 bit per channel use especially around $g^2=P^{-1/3}$, where $P$ is the symmetric power constraint and $g$ is the symmetric real cross-channel coefficient. In this paper, we pay attention to the \emph{moderate interference regime} where $g^2\in (\max(0.086, P^{-1/3}),1)$. We propose a new upper-bounding technique that utilizes noisy observation of interfering signals as genie signals and applies time sharing to the genie signals at the receivers. A conditional version of the worst additive noise lemma is also introduced to derive new capacity bounds. The resulting upper (outer) bounds on the sum capacity (capacity region) are shown to be tighter than the existing bounds in a certain range of the moderate interference regime. Using the new upper bounds and the HK lower bound, we show that $R_\text{sym}^*=\frac{1}{2}\log \big(|g|P+|g|^{-1}(P+1)\big)$ characterizes the capacity of the symmetric real GIC to within $0.104$ bit per channel use in the moderate interference regime at any signal-to-noise ratio (SNR). We further establish a high-SNR characterization of the symmetric real GIC, where the proposed upper bound is at most $0.1$ bit far from a certain HK achievable scheme with Gaussian signaling and time sharing for $g^2\in (0,1]$. In particular, $R_\text{sym}^*$ is achievable at high SNR by the proposed HK scheme and turns out to be the high-SNR capacity at least at $g^2=0.25, 0.5$.Comment: Submitted to IEEE Transactions on Information Theory on June 2015, revised on November 2016, and accepted for publication on Feb. 28, 201

DiffFace: Diffusion-based Face Swapping with Facial Guidance

In this paper, we propose a diffusion-based face swapping framework for the first time, called DiffFace, composed of training ID conditional DDPM, sampling with facial guidance, and a target-preserving blending. In specific, in the training process, the ID conditional DDPM is trained to generate face images with the desired identity. In the sampling process, we use the off-the-shelf facial expert models to make the model transfer source identity while preserving target attributes faithfully. During this process, to preserve the background of the target image and obtain the desired face swapping result, we additionally propose a target-preserving blending strategy. It helps our model to keep the attributes of the target face from noise while transferring the source facial identity. In addition, without any re-training, our model can flexibly apply additional facial guidance and adaptively control the ID-attributes trade-off to achieve the desired results. To the best of our knowledge, this is the first approach that applies the diffusion model in face swapping task. Compared with previous GAN-based approaches, by taking advantage of the diffusion model for the face swapping task, DiffFace achieves better benefits such as training stability, high fidelity, diversity of the samples, and controllability. Extensive experiments show that our DiffFace is comparable or superior to the state-of-the-art methods on several standard face swapping benchmarks.Comment: Project Page: https://hxngiee.github.io/DiffFac

Auxin response factor 2 (ARF2) plays a major role in regulating auxin-mediated leaf longevity

Auxin regulates a variety of physiological and developmental processes in plants. Although auxin acts as a suppressor of leaf senescence, its exact role in this respect has not been clearly defined, aside from circumstantial evidence. It was found here that ARF2 functions in the auxin-mediated control of Arabidopsis leaf longevity, as discovered by screening EMS mutant pools for a delayed leaf senescence phenotype. Two allelic mutations, ore14-1 and 14-2, caused a highly significant delay in all senescence parameters examined, including chlorophyll content, the photochemical efficiency of photosystem II, membrane ion leakage, and the expression of senescence-associated genes. A delay of senescence symptoms was also observed under various senescence-accelerating conditions, where detached leaves were treated with darkness, phytohormones, or oxidative stress. These results indicate that the gene defined by these mutations might be a key regulatory genetic component controlling functional leaf senescence. Map-based cloning of ORE14 revealed that it encodes ARF2, a member of the auxin response factor (ARF) protein family, which modulates early auxin-induced gene expression in plants. The ore14/arf2 mutation also conferred an increased sensitivity to exogenous auxin in hypocotyl growth inhibition, thereby demonstrating that ARF2 is a repressor of auxin signalling. Therefore, the ore14/arf2 lesion appears to cause reduced repression of auxin signalling with increased auxin sensitivity, leading to delayed senescence. Altogether, our data suggest that ARF2 positively regulates leaf senescence in Arabidopsis

Dehydrogenation of homocyclic liquid organic hydrogen carriers (LOHCs) over Pt supported on an ordered pore structure of 3-D cubic mesoporous KIT-6 silica

Pt supported on ordered mesoporous silica (KIT-6) catalyst was examined for the dehydrogenation of homocyclic liquid organic hydrogen carriers (LOHCs, 1: MCH, 2: hydrogenated biphenyl-based eutectic mixture (H-BPDM)) conditions. The longer pore-residence time of the MCH molecules in the 3D bicontinuous pore structure of the Pt/KIT-6 catalyst strongly affected the catalytic activity because a higher MCH concentration was achieved in the vicinity of the Pt active sites. Pt/KIT-6 catalyst exhibited a higher surface area, pore volume, and Pt dispersion with narrower particle size distribution (average Pt particle size: ~1.3 nm). Therefore, higher LOHC conversion with faster hydrogen production occurred, with a higher hydrogen selectivity over Pt/KIT-6 compared with Pt/SiO2 and Pt/Al2O3. Long-term experiment results indicated that the Pt/KIT-6 catalytic activity was stable over the reaction time than that of the other catalysts. No significant structural collapse occurred in KIT-6 during the dehydrogenation. Carbon coking was observed for all three samples

A cooperative biphasic MoOx–MoPx promoter enables a fast-charging lithium-ion battery

The realisation of fast-charging lithium-ion batteries with long cycle lifetimes is hindered by the uncontrollable plating of metallic Li on the graphite anode during high-rate charging. Here we report that surface engineering of graphite with a cooperative biphasic MoOx–MoPx promoter improves the charging rate and suppresses Li plating without compromising energy density. We design and synthesise MoOx–MoPx/graphite via controllable and scalable surface engineering, i.e., the deposition of a MoOx nanolayer on the graphite surface, followed by vapour-induced partial phase transformation of MoOx to MoPx. A variety of analytical studies combined with thermodynamic calculations demonstrate that MoOx effectively mitigates the formation of resistive films on the graphite surface, while MoPx hosts Li+ at relatively high potentials via a fast intercalation reaction and plays a dominant role in lowering the Li+ adsorption energy. The MoOx–MoPx/graphite anode exhibits a fast-charging capability (<10 min charging for 80% of the capacity) and stable cycling performance without any signs of Li plating over 300 cycles when coupled with a LiNi0.6Co0.2Mn0.2O2 cathode. Thus, the developed approach paves the way to the design of advanced anode materials for fast-charging Li-ion batteries. © 2021, The Author(s).1

The RAV1 transcription factor positively regulates leaf senescence in Arabidopsis

Leaf senescence is a developmentally programmed cell death process that constitutes the final step of leaf development and involves the extensive reprogramming of gene expression. Despite the importance of senescence in plants, the underlying regulatory mechanisms are not well understood. This study reports the isolation and functional analysis of RAV1, which encodes a RAV family transcription factor. Expression of RAV1 and its homologues is closely associated with leaf maturation and senescence. RAV1 mRNA increased at a later stage of leaf maturation and reached a maximal level early in senescence, but decreased again during late senescence. This profile indicates that RAV1 could play an important regulatory role in the early events of leaf senescence. Furthermore, constitutive and inducible overexpression of RAV1 caused premature leaf senescence. These data strongly suggest that RAV1 is sufficient to cause leaf senescence and it functions as a positive regulator in this process

Multi-group linear turbo equalization with intercell interference cancellation for MC-CDMA cellular systems.

In this paper, we investigate multi-group linear turbo equalization using single antenna interference cancellation (SAIC) techniques to mitigate the intercell interference for multi-carrier code division multiple access (MC-CDMA) cellular systems. It is important for the mobile station to mitigate the intercell interference as the performance of the users close to cell edge is mainly degraded by the intercell interference. The complexity of the proposed iterative detector and receiver is low as the one-tap minimum mean square error (MMSE) equalizer is employed for mitigating the intracell interference, while a simple group interference canceller is used for suppressing the intercell interference. Simulation results show that the proposed iterative detector and receiver can mitigate the intercell interference effectively through iterations for both uncoded and coded signals