Cross Z-Complementary Pairs for Optimal Training in Spatial Modulation Over Frequency Selective Channels

The contributions of this article are twofold: Firstly, we introduce a novel class of sequence pairs, called “cross Z-complementary pairs (CZCPs),” each displaying zero-correlation zone (ZCZ) properties for both their aperiodic autocorrelation sums and crosscorrelation sums. Systematic constructions of perfect CZCPs based on selected Golay complementary pairs (GCPs) are presented. Secondly, we point out that CZCPs can be utilized as a key component in designing training sequences for broadband spatial modulation (SM) systems. We show that our proposed SM training sequences derived from CZCPs lead to optimal channel estimation performance over frequency-selective channels

Recent progress in Ti-based nanocomposite anodes for lithium ion batteries

Studying on the anode materials with high energy densities for next-generation lithium-ion batteries (LIBs) is the key for the wide application for electrochemical energy storage devices. Ti-based compounds as promising anode materials are known for their outstanding high-rate capacity and cycling stability as well as improved safety over graphite. However, Ti-based materials still suffer from the low capacity, thus largely limiting their commercialized application. Here, we present an overview of the recent development of Ti-based anode materials in LIBs, and special emphasis is placed on capacity enhancement by rational design of hybrid nanocomposites with conversion-/ alloying-type anodes. This review is expected to provide a guidance for designing novel Ti-based materials for energy storage and conversion. Keywords: lithium-ion batteries (LIBs) anode titania lithium titanateNational Natural Science Foundation (China) (51472137)National Natural Science Foundation (China) (51772163

An Experimental Investigation of Enhanced SM-OFDM Over Indoor Rician Multipath Channels

In this Correspondence, we investigate enhanced spatial modulation (ESM) aided orthogonal frequency division multiplexing (OFDM) systems. ESM extends the conventional SM by introducing a series of signal constellations. Existing research shows that ESM displays performance superiority over SM in flat-fading channels. For frequency-selective fading channels, we design a practical implementation of an ESM&SM aided OFDM hybrid system to characterize the bit error rate (BER) performance of ESM and conventional SM with an experimental wireless testbed. From the experimental results, it is found that ESM achieves better BER performance than SM on frequency selective channels, which are consistent with the Monte Carlo simulation results

Sparse or Dense: A Comparative Study of Code-Domain NOMA Systems

This paper is focused on code-domain non-orthogonal multiple access (CD-NOMA), which is an emerging paradigm to support massive connectivity for future machine-type wireless networks. We take a comparative approach to study two types of overloaded CD-NOMA, i.e., sparse code multiple access (SCMA) and dense code multiple access (DCMA), which are distinctive from each other in terms of their codebooks having sparsity or not. By analysing their individual diversity orders (DO) in Rayleigh fading channels, it is found that DCMA can be designed with the aid of generalized sphere decoder (i.e., a nonlinear multiuser detector) to enjoy full DO which is equal to the maximum number of resource nodes in the system. This is in contrast to SCMA whose error rate suffers from limited DO equal to the codebook sparsity (i.e., the effective number of resource nodes occupied by each user). We conduct theoretical analysis for the codebook design criteria and propose to use generalized sphere decoder for DCMA detection. We numerically evaluate two types of multiple access schemes under “4 × 6” (i.e., six users communicate over four subcarriers) and “5 × 10” NOMA settings and reveal that DCMA gives rise to significantly improved error rate performance in Rayleigh fading channels, whilst having decoding complexity comparable to that of SCMA

HpGAN: Sequence Search with Generative Adversarial Networks

Sequences play an important role in many engineering applications and systems. Searching sequences with desired properties has long been an interesting but also challenging research topic. This article proposes a novel method, called HpGAN, to search desired sequences algorithmically using generative adversarial networks (GAN). HpGAN is based on the idea of zero-sum game to train a generative model, which can generate sequences with characteristics similar to the training sequences. In HpGAN, we design the Hopfield network as an encoder to avoid the limitations of GAN in generating discrete data. Compared with traditional sequence construction by algebraic tools, HpGAN is particularly suitable for intractable problems with complex objectives which prevent mathematical analysis. We demonstrate the search capabilities of HpGAN in two applications: 1) HpGAN successfully found many different mutually orthogonal complementary code sets (MOCCS) and optimal odd-length Z-complementary pairs (OB-ZCPs) which are not part of the training set. In the literature, both MOCSSs and OB-ZCPs have found wide applications in wireless communications. 2) HpGAN found new sequences which achieve four-times increase of signal-to-interference ratio--benchmarked against the well-known Legendre sequence--of a mismatched filter (MMF) estimator in pulse compression radar systems. These sequences outperform those found by AlphaSeq.Comment: 12 pages, 16 figure

Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

This work presents Depth Anything, a highly practical solution for robust monocular depth estimation. Without pursuing novel technical modules, we aim to build a simple yet powerful foundation model dealing with any images under any circumstances. To this end, we scale up the dataset by designing a data engine to collect and automatically annotate large-scale unlabeled data (~62M), which significantly enlarges the data coverage and thus is able to reduce the generalization error. We investigate two simple yet effective strategies that make data scaling-up promising. First, a more challenging optimization target is created by leveraging data augmentation tools. It compels the model to actively seek extra visual knowledge and acquire robust representations. Second, an auxiliary supervision is developed to enforce the model to inherit rich semantic priors from pre-trained encoders. We evaluate its zero-shot capabilities extensively, including six public datasets and randomly captured photos. It demonstrates impressive generalization ability. Further, through fine-tuning it with metric depth information from NYUv2 and KITTI, new SOTAs are set. Our better depth model also results in a better depth-conditioned ControlNet. Our models are released at https://github.com/LiheYoung/Depth-Anything.Comment: Accepted by CVPR 2024. Project page: https://depth-anything.github.i

Numerical Simulation of the Rock SHPB Test with a Special Shape Striker Based on the Discrete Element Method

A split Hopkinson pressure bar (SHPB) system with a special shape striker has been suggested as the test method by the International Society for Rock Mechanics (ISRM) to determine the dynamic characteristics of rock materials. In order to further verify this testing technique and microscopically reveal the dynamic responses of specimens in SHPB tests, a numerical SHPB test system was established based on particle flow code (PFC). Numerical dynamic tests under different impact velocities were conducted. Investigation of the stresses at the ends of a specimen showed that the specimen could reach stress equilibrium after several wave reverberations, and this balance could be maintained well for a certain time period after the peak stress. In addition, analyses of the reflected waves showed that there was a clear relationship between the variation of the reflected wave and the stress equilibrium state in the specimen, and the turning point of the reflected wave corresponded well with the peak stress in the specimen. Furthermore, the reflected waves can be classified into three types according to their patterns. Under certain impact velocities, the specimen deforms at a constant strain rate during the whole loading process. Finally, the influence of the micro-strength ratio ( $${{\tau_{\text{c}} } \mathord{\left/ {\vphantom {{\tau_{\text{c}} } {\sigma_{\text{c}} }}} \right. \kern-0pt} {\sigma_{\text{c}} }}$$

Numerical Simulation of the Rock SHPB Test with a Special Shape Striker Based on the Discrete Element Method

A split Hopkinson pressure bar system with a special shape striker has been suggested as the test method by the International Society for Rock Mechanics (ISRM) to determine the dynamic characteristics of rock materials. In order to further verify this testing technique and microscopically reveal the dynamic responses of specimens in SHPB tests, a numerical SHPB test system was established based on particle flow code (PFC). Numerical dynamic tests under different impact velocities were conducted. Investigation of the stresses at the ends of a specimen showed that the specimen could reach stress equilibrium after several wave reverberations, and this balance could be maintained well for a certain time period after peak stress. In addition, analyses of the reflected waves showed that there was a clear relationship between the variation of the reflected wave and the stress equilibrium state in the specimen, and the turning point of the reflected wave corresponded well with the peak stress in the specimen. Furthermore, the reflected waves can be classified into three types according to their patterns. Under certain impact velocities, the specimen deforms at a constant strain rate during the whole loading process. Finally, the influence of the micro-strength ratio and distribution pattern on the dynamic increase factor of strength DIF were studied, and the lateral inertia confinement and heterogeneity were found to be two important factors causing the strain-rate effect for rock materials