Neural radiance fields in the industrial and robotics domain: applications, research opportunities and use cases

The proliferation of technologies, such as extended reality (XR), has increased the demand for high-quality three-dimensional (3D) graphical representations. Industrial 3D applications encompass computer-aided design (CAD), finite element analysis (FEA), scanning, and robotics. However, current methods employed for industrial 3D representations suffer from high implementation costs and reliance on manual human input for accurate 3D modeling. To address these challenges, neural radiance fields (NeRFs) have emerged as a promising approach for learning 3D scene representations based on provided training 2D images. Despite a growing interest in NeRFs, their potential applications in various industrial subdomains are still unexplored. In this paper, we deliver a comprehensive examination of NeRF industrial applications while also providing direction for future research endeavors. We also present a series of proof-of-concept experiments that demonstrate the potential of NeRFs in the industrial domain. These experiments include NeRF-based video compression techniques and using NeRFs for 3D motion estimation in the context of collision avoidance. In the video compression experiment, our results show compression savings up to 48\% and 74\% for resolutions of 1920x1080 and 300x168, respectively. The motion estimation experiment used a 3D animation of a robotic arm to train Dynamic-NeRF (D-NeRF) and achieved an average peak signal-to-noise ratio (PSNR) of disparity map with the value of 23 dB and an structural similarity index measure (SSIM) 0.97

Agent-Based Model of the Spectrum Auctions with Sensing Imperfections in Dynamic Spectrum Access Networks

Cognitive radio (CR) is the underlying platform for the application of dynamic spectrum access (DSA) networks. Although the auction theory and spectrum trading mechanisms have been discussed in the CR related works, their joint techno-economic impact on the efficiency of distributed CR networks has not been researched yet. In this paper we assume heterogeneous primary channels with network availability statistics unknown to each secondary user (SU) terminal. In order to detect the idle primary user (PU) network channels, the SU terminals trigger regularly the spectrum sensing mechanism and make the cooperative decision regarding the channel status at the fusion center. The imperfections of the spectrum mechanism create the possibility of the channel collision, resulting in the existence of the risk (in terms of user collision) in the network. The spectrum trading within SU network is governed by the application of the sealed-bid first-price auction, which takes into account the channel valuation as well as the statistical probability of the risk existence. In order to maximize the long-term payoff, the SU terminals take an advantage of the reinforcement comparison strategy. The results demonstrate that in the investigated model, total revenue and total payoff of the SU operator (auctioneer) and SU terminals (bidders) are characterized by the existence of the global optimum, thus there exists the optimal sensing time guaranteeing the optimum economic factors for both SU operator and SU terminals

On the Interdependence of the Financial Market and Open Access Spectrum Market in the 5G Network

Modern 5G networks offer a large space for innovation and a completely new approach to addressing network functioning. A fixed spectrum assignment policy is a significant limitation of today’s wireless communication network practice and is to be replaced by a completely new approach called dynamic spectrum access (DSA). However, there is no general agreement on the organization of the DSA. Some studies suggest that open access market can be inspired by the electricity or financial markets. It allows to treat operators with region coverage as investors entering the market and trading the spectra on an on-demand basis. Because investors operate in both the financial markets and the markets for spectra, new interference between both markets emerges. Our paper shows how the risk-free rate of return stemming from the financial markets influences the techno-economic properties of the network. We show that, for low risk-free returns, the spectrum market becomes oversupplied, which keeps service prices very low and spectrum trading volumes large. In contrast, if risk-free returns are high, then spectrum trading volumes decline and the market becomes price sensitive; in other words, economic rules begin to work better

On the Interdependence of the Financial Market and Open Access Spectrum Market in the 5G Network

Modern 5G networks offer a large space for innovation and a completely new approach to addressing network functioning. A fixed spectrum assignment policy is a significant limitation of today’s wireless communication network practice and is to be replaced by a completely new approach called dynamic spectrum access (DSA). However, there is no general agreement on the organization of the DSA. Some studies suggest that open access market can be inspired by the electricity or financial markets. It allows to treat operators with region coverage as investors entering the market and trading the spectra on an on-demand basis. Because investors operate in both the financial markets and the markets for spectra, new interference between both markets emerges. Our paper shows how the risk-free rate of return stemming from the financial markets influences the techno-economic properties of the network. We show that, for low risk-free returns, the spectrum market becomes oversupplied, which keeps service prices very low and spectrum trading volumes large. In contrast, if risk-free returns are high, then spectrum trading volumes decline and the market becomes price sensitive; in other words, economic rules begin to work better

The agent-based model of the dynamic spectrum access networks based on the bilateral bargaining

This paper describes a simple bargaining mechanism that allows au-tonomous agents to engage in a bargaining decisions taking place in the dynam-ic spectrum access market. The agents take on the role of operators which aims to purchase the frequency spectra on the wholesale market and in turn, provide the services towards the end-users. In the paper, the wholesale distribution of the resources in the agent-based model is governed by the bilateral bargaining between the operators and the spectrum broker. The aim of such an interaction is to reach agreements (agreement in terms of the negotiated wholesale price and number of contracted channels) through an iterative bargaining. The opera-tors aim to attract the end-users via dynamic retail pricing scheme. The activity of the end-users follows the truncated Gaussian distribution, which mimics the activity of the end-users throughout the daily cycle. The numerical results sug-gest that the model is capable of capturing the stochastic activity of the end-users, which reflects itself in the variable operator's profit and retail price

Financial Implications of Femtocell Deployment

Increased usage in wireless communication has been observed in the last decades and it is expected to rise even more. Traditional spectrum allocation mechanism together with increasing demand for data transfers caused spectrum to become more congested. As a consequence, high pressure for its more effective usage emerges. Modern concept of heterogeneous networks with cognitive femtocells represents one of the promising solutions. Associated technical issues of heterogeneous networks have been discussed in many papers. However, economic aspects of femtocell deployment in network are still insufficiently analysed. This paper is devoted to economic aspects of operators’ behaviour in the macro-femto network but we also focus on technical issue of overall spectrum usage. For this purpose, the agent-based model of two-tier network was proposed. Results of simulation confirm significant influence of number of deployed femtocells and their location in the network on operators’ pricing strategies and their whole economic performance