Diversity Order Analysis for Quantized Constant Envelope Transmission

Quantized constant envelope (QCE) transmission is a popular and effective technique to reduce the hardware cost and improve the power efficiency of 5G and beyond systems equipped with large antenna arrays. It has been widely observed that the number of quantization levels has a substantial impact on the system performance. This paper aims to quantify the impact of the number of quantization levels on the system performance. Specifically, we consider a downlink single-user multiple-input-single-output (MISO) system with M-phase shift keying (PSK) constellation under the Rayleigh fading channel. We first derive a novel bound on the system symbol error probability (SEP). Based on the derived SEP bound, we characterize the achievable diversity order of the quantized matched filter (MF) precoding strategy. Our results show that full diversity order can be achieved when the number of quantization levels L is greater than the PSK constellation order M, i.e., L>M, only half diversity order is achievable when L=M, and the achievable diversity order is 0 when L<M. Simulation results verify our theoretical analysis.Comment: 9 pages, 3 figures, submitted for possible publicatio

Asymptotic SEP Analysis and Optimization of Linear-Quantized Precoding in Massive MIMO Systems

A promising approach to deal with the high hardware cost and energy consumption of massive MIMO transmitters is to use low-resolution digital-to-analog converters (DACs) at each antenna element. This leads to a transmission scheme where the transmitted signals are restricted to a finite set of voltage levels. This paper is concerned with the analysis and optimization of a low-cost quantized precoding strategy, referred to as linear-quantized precoding, for a downlink massive MIMO system under Rayleigh fading. In linear-quantized precoding, the signals are first processed by a linear precoding matrix and subsequently quantized component-wise by the DAC. In this paper, we analyze both the signal-to-interference-plus-noise ratio (SINR) and the symbol error probability (SEP) performances of such linear-quantized precoding schemes in an asymptotic framework where the number of transmit antennas and the number of users grow large with a fixed ratio. Our results provide a rigorous justification for the heuristic arguments based on the Bussgang decomposition that are commonly used in prior works. Based on the asymptotic analysis, we further derive the optimal precoder within a class of linear-quantized precoders that includes several popular precoders as special cases. Our numerical results demonstrate the excellent accuracy of the asymptotic analysis for finite systems and the optimality of the derived precoder.Comment: 58 pages, 8 figures, submitted for possible publicatio

Linear One-Bit Precoding in Massive MIMO: Asymptotic SEP Analysis and Optimization

This paper focuses on the analysis and optimization of a class of linear one-bit precoding schemes for a downlink massive MIMO system under Rayleigh fading channels. The considered class of linear one-bit precoding is fairly general, including the well-known matched filter (MF) and zero-forcing (ZF) precoding schemes as special cases. Our analysis is based on an asymptotic framework where the numbers of transmit antennas and users in the system grow to infinity with a fixed ratio. We show that, under the asymptotic assumption, the symbol error probability (SEP) of the considered linear one-bit precoding schemes converges to that of a scalar ``signal plus independent Gaussian noise'' model. This result enables us to provide accurate predictions for the SEP of linear one-bit precoding. Additionally, we also derive the optimal linear one-bit precoding scheme within the considered class based on our analytical results. Simulation results demonstrate the excellent accuracy of the SEP prediction and the optimality of the derived precoder.Comment: 5 pages, 2 figures, accepted for publication at SPAWC 202

CI-Based One-Bit Precoding for Multiuser Downlink Massive MIMO Systems with PSK Modulation: A Negative ℓ1\ell_1 Penalty Approach

In this paper, we consider the one-bit precoding problem for the multiuser downlink massive multiple-input multiple-output (MIMO) system with phase shift keying (PSK) modulation and focus on the celebrated constructive interference (CI)-based problem formulation. We first establish the NP-hardness of the problem (even in the single-user case), which reveals the intrinsic difficulty of globally solving the problem. Then, we propose a novel negative $\ell_1$ penalty model for the considered problem, which penalizes the one-bit constraint into the objective with a negative $\ell_1$-norm term, and show the equivalence between (global and local) solutions of the original problem and the penalty problem when the penalty parameter is sufficiently large. We further transform the penalty model into an equivalent min-max problem and propose an efficient alternating optimization (AO) algorithm for solving it. The AO algorithm enjoys low per-iteration complexity and is guaranteed to converge to a stationary point of the min-max problem and a local minimizer of the penalty problem. To further reduce the computational cost, we also propose a low-complexity implementation of the AO algorithm, where the values of the variables will be fixed in later iterations once they satisfy the one-bit constraint. Numerical results show that, compared against the state-of-the-art CI-based algorithms, both of the proposed algorithms generally achieve better bit-error-rate (BER) performance with lower computational cost, especially when the problem is difficult (e.g., high-order modulations, large number of antennas, or high user-antenna ratio).Comment: 13 pages, 8 figures, submitted for possible publication. arXiv admin note: text overlap with arXiv:2110.0476

Efficient Quantized Constant Envelope Precoding for Multiuser Downlink Massive MIMO Systems

Quantized constant envelope (QCE) precoding, a new transmission scheme that only discrete QCE transmit signals are allowed at each antenna, has gained growing research interests due to its ability of reducing the hardware cost and the energy consumption of massive multiple-input multiple-output (MIMO) systems. However, the discrete nature of QCE transmit signals greatly complicates the precoding design. In this paper, we consider the QCE precoding problem for a massive MIMO system with phase shift keying (PSK) modulation and develop an efficient approach for solving the constructive interference (CI) based problem formulation. Our approach is based on a custom-designed (continuous) penalty model that is equivalent to the original discrete problem. Specifically, the penalty model relaxes the discrete QCE constraint and penalizes it in the objective with a negative $\ell_2$-norm term, which leads to a non-smooth non-convex optimization problem. To tackle it, we resort to our recently proposed alternating optimization (AO) algorithm. We show that the AO algorithm admits closed-form updates at each iteration when applied to our problem and thus can be efficiently implemented. Simulation results demonstrate the superiority of the proposed approach over the existing algorithms.Comment: 5 pages, 5 figures, submitted for possible publicatio

Packing Densities of Delzant and Semitoric Polygons

Exploiting the relationship between 4-dimensional toric and semitoric integrable systems with Delzant and semitoric polygons, respectively, we develop techniques to compute certain equivariant packing densities and equivariant capacities of these systems by working exclusively with the polygons. This expands on results of Pelayo and Pelayo-Schmidt. We compute the densities of several important examples and we also use our techniques to solve the equivariant semitoric perfect packing problem, i.e., we list all semitoric polygons for which the associated semitoric system admits an equivariant packing which fills all but a set of measure zero of the manifold. This paper also serves as a concise and accessible introduction to Delzant and semitoric polygons in dimension four

Robust Super-Resolution Imaging Based on a Ring Core Fiber with Orbital Angular Momentum

Single fiber imaging technology offers unique insights for research and inspection in difficult to reach and narrow spaces. In particular, ultra-compact multimode fiber (MMF) imaging, has received increasing interest over the past decade. However, MMF imaging will be seriously distorted when subjected to dynamic perturbations due to time-varying mode coupling, and the imaging of space objects via Gaussian beam will be relatively degraded at the edge due to insufficient contrast. Here, a robust super-resolution imaging method based on a ring core fiber (RCF) with orbital angular momentum (OAM) has been proposed and experimentally demonstrated. The OAM modes propagating in the RCF form a series of weakly-coupled mode groups, making our imaging system robust to external perturbations. In addition, a spiral phase plate is used as a vortex filter to produce OAM for edge enhancement, thus improving the image resolution. Furthermore, a few-shot U-Transformer neural network is proposed to enhance the resilience of the developed RCF-OAM imaging system against environmental perturbations. Finally, the developed RCF-OAM imaging system achieves biological image transmission, demonstrating the practicality of our scheme. This pioneering RCF OAM imaging system may have broad applications, potentially revolutionising fields such as biological imaging and industrial non-destructive testing

Arts therapies for mental disorders in COVID-19 patients: a comprehensive review

Background and objectiveThe COVID-19 global pandemic has necessitated the urgency for innovative mental health interventions. We performed a comprehensive review of the available literature on the utility and efficacy of arts therapies in treating mental health problems, with special emphasis on their deployment during the COVID-19 pandemic, aiming to provide some evidence for the application of this therapy.MethodsThe potential studies were systematically sourced from five authoritative databases: PubMed, Embase, the Cochrane Library, Web of Science, and the CNKI database. The evaluation of these studies was conducted based on stringent criteria, including validity, suitability, therapeutic potential, and consistency. Each piece of included literature was meticulously scored in accordance with these criteria, thus ensuring the inclusion of only the most robust studies in this review. The data from these Randomized Controlled Trials (RCTs) were carefully extracted using the PICO(S) framework, ensuring a comprehensive and systemic approach to data collection. In order to emphasize the variability in the effects of differing arts therapies on COVID-19-induced psychiatric disturbances, the sourced literature was systematically categorized and scrutinized based on distinct modalities.ResultsOut of the 7,250 sourced articles, 16 satisfied the inclusion conditions. The therapies were predominantly meditation (n = 7), supplemented by individual studies on color therapy (n = 3), music therapy (n = 2), and single studies on horticultural therapy, dance therapy, mindfulness and music therapy, and yoga and music therapy (n = 4 collectively). These various forms of arts therapies had a positive short to medium-term impact on the mental health of COVID-19 patients. Besides improving patients' physical and mental health, these therapies can also be employed to mitigate mental health issues among healthcare professionals.ConclusionThe COVID-19 pandemic has profound and long-lasting implications for public mental health. Diverse forms of arts therapies are potentially effective in addressing related psychiatric symptoms. The integration of artificial intelligence might further enhance the efficacy and scalability of arts therapies in future implementations