Passive Reflection Codebook Design for IRS-Integrated Access Point

Intelligent reflecting surface (IRS) has emerged as a promising technique to extend the wireless signal coverage of access point (AP) and improve the communication performance cost-effectively. In order to reduce the path-loss of the cascaded user-IRS-AP channels, the IRS-integrated AP architecture has been proposed to deploy the IRSs and the antenna array of the AP within the same antenna radome. To reduce the pilot overhead for estimating all IRS-involved channels, in this paper, we propose a novel codebook-based IRS reflection design for the IRS-integrated AP to enhance the coverage performance in a given area. In particular, the codebook consisting of a small number of codewords is designed offline by employing an efficient sector division strategy based on the azimuth angle. To ensure the performance of each sector, we optimize its corresponding codeword for IRS reflection pattern to maximize the sector-min-average-effective-channel-power (SMAECP) by applying the alternating optimization (AO) and semidefinite relaxation (SDR) methods. With the designed codebook, the AP performs the IRS reflection training by sequentially applying all codewords and selects the one achieving the best communication performance for data transmission. Numerical results show that our proposed codebook design can enhance the average channel power of the whole coverage area, as compared to the system without IRS. Moreover, our proposed codebook-based IRS reflection design is shown to achieve significant performance gain over other benchmark schemes in both single-user and multi-user transmissions.Comment: 13 pages, 11 figure

Service selection strategic analysis for selfoperated e-commerce platforms under settlement

In order to study whether e-commerce platforms carry out service cooperation after settlement in-depth, this paper focuses on service selection strategic analysis for agent channels on some self-operated e-commerce platforms settled in hybrid e-commerce platforms. We present multi-leader-follower models in two different scenarios with the platforms as leaders and the manufacturers as followers and give some numerical experiments to analyze the impacts of service selection strategies for self-operated platforms on all supply chain members. Our finding shows that if the service cost efficiency is moderate or low, the self-operated platform prefers to provide its service for the agent; otherwise, its selection mainly depends on the unit product service fee. In addition, fierce service competition and high unit service fee are unfavorable to all members, while high service cost efficiency may hurt both the platform and the manufacturer

A novel approach for bilevel programs based on Wolfe duality

This paper considers a bilevel program, which has many applications in practice. To develop effective numerical algorithms, it is generally necessary to transform the bilevel program into a single-level optimization problem. The most popular approach is to replace the lower-level program by its KKT conditions and then the bilevel program can be reformulated as a mathematical program with equilibrium constraints (MPEC for short). However, since the MPEC does not satisfy the Mangasarian-Fromovitz constraint qualification at any feasible point, the well-developed nonlinear programming theory cannot be applied to MPECs directly. In this paper, we apply the Wolfe duality to show that, under very mild conditions, the bilevel program is equivalent to a new single-level reformulation (WDP for short) in the globally and locally optimal sense. We give an example to show that, unlike the MPEC reformulation, WDP may satisfy the Mangasarian-Fromovitz constraint qualification at its feasible points. We give some properties of the WDP reformulation and the relations between the WDP and MPEC reformulations. We further propose a relaxation method for solving WDP and investigate its limiting behavior. Comprehensive numerical experiments indicate that, although solving WDP directly does not perform very well in our tests, the relaxation method based on the WDP reformulation is quite efficient

Effect of dynamic threshold pressure gradient on production performance in water-bearing tight gas reservoir

AbstractWater content and distribution have important impacts on gas production in water-bearing tight gas reservoirs. However, due to the structural and chemical heterogeneity of tight reservoirs, the water phase exists in various states, which has complicated the analyses of the effects of water characteristics on tight gas production performance. In this work, the water phase is distinguished from immobile to mobile states and the term of constrained water saturation is proposed. It is established that water can flow when the driving pressure difference is larger than the critical driving pressure difference. A new theoretical model of threshold pressure gradient is derived to incorporate the influences of constrained water saturation and permeability. On this basis, a new prediction model considering the varied threshold pressure gradient is obtained, and the result indicates that when threshold pressure gradient is constant, the real gas production capacity of the reservoir will be weakened. Meanwhile, a dynamic supply boundary model is presented, which indicates that the permeability has a strong influence on the dynamic supply boundary, whereas the impact of initial water saturation is negligible. These findings provide insights into the understanding of the effects of water state and saturation on the threshold pressure gradient and gas production rate in tight gas reservoirs. Furthermore, this study provides useful guidance on the prediction of field-scale gas production.Cited as: Zhu, W., Liu, Y., Shi, Y., Zou, G., Zhang, Q., Kong, D. Effect of dynamic threshold pressure gradient on production performance in water-bearing tight gas reservoir. Advances in Geo-Energy Research, 2022, 6(4): 286-295. https://doi.org/10.46690/ager.2022.04.0

VideoDreamer: Customized Multi-Subject Text-to-Video Generation with Disen-Mix Finetuning

Customized text-to-video generation aims to generate text-guided videos with customized user-given subjects, which has gained increasing attention recently. However, existing works are primarily limited to generating videos for a single subject, leaving the more challenging problem of customized multi-subject text-to-video generation largely unexplored. In this paper, we fill this gap and propose a novel VideoDreamer framework. VideoDreamer can generate temporally consistent text-guided videos that faithfully preserve the visual features of the given multiple subjects. Specifically, VideoDreamer leverages the pretrained Stable Diffusion with latent-code motion dynamics and temporal cross-frame attention as the base video generator. The video generator is further customized for the given multiple subjects by the proposed Disen-Mix Finetuning and Human-in-the-Loop Re-finetuning strategy, which can tackle the attribute binding problem of multi-subject generation. We also introduce MultiStudioBench, a benchmark for evaluating customized multi-subject text-to-video generation models. Extensive experiments demonstrate the remarkable ability of VideoDreamer to generate videos with new content such as new events and backgrounds, tailored to the customized multiple subjects. Our project page is available at https://videodreamer23.github.io/