Search

Developing China's high-tech industry is important to make the country innovation-oriented. This requires optimising the allocation of innovation resources and improving innovation efficiency. However, few studies have investigated this topic and the realisation path for the high-tech industry. This study develops an input-oriented inverse data envelopment analysis (DEA) model with frontier changes to analyse the optimisation of resource allocation in China's high-tech industry during 2019–2025. With this method, decision makers can scientifically analyse the specific amount of resource investment. We also construct an analysis framework from short- and long-term perspectives. The results show that the excessive input of research and development (R&D) personnel and unbalanced allocation of capital resources are the main barriers to the development of high-tech industries in the short term, and in the mid- and long terms, the demands for investment in talent and capital will continue to increase. Improvement directions for promoting the development of China's high-tech industry are discussed. Finally, we present valuable information for policymaking to promote progress in high-tech industries in different regions. [ABSTRACT FROM AUTHOR]

In this paper, a novel negative refractive index metamaterial (NIM) is developed and characterized. The proposed metamaterial exhibits negative effective permittivity (εeffe) and negative effective permeability (µeffe) at millimeter wave frequency of 28 GHz. This attractive feature is utilized to enhance the gain of a microstrip patch antenna (MPA). Two thin layers of 5 × 5 subwavelength unit cell array of NIM are placed above a single MPA to enhance the gain of the antenna. Each unit cell has an area of 3.4 × 3.4 mm2. A gain increase of 7.9 dBi has been observed when using the proposed NIM as a superstrate. Furthermore, the NIM array is placed over a 2 × 2 array of MPAs with four ports to demonstrate versatility of the metamaterial. The total size of the 2 × 2 antenna array system with N-MTM is about 61.1 × 34 × 16mm3 (5.71λ × 3.18λ × 1.5λ, where λ is the free-space wavelength at 28 GHz). The measurement result indicate that the maximum gain of the antenna array is 13.5dBi. A gain enhancement of 7.55 dB in E-Plane and 7.25 dB in H-Plane at the resonant frequency of 28 GHz is obtained. The proposed antenna structure is suitable for 5G millimeter wave communications, in particular, for possible implementation in future millimeter wave access points and cellular base stations. [ABSTRACT FROM AUTHOR]

Summary: Fifth generation cellular networks have high data rates and connectivity demands. The relaying approaches are widely used in cellular networks to improve coverage, user throughput, and capacity at low cost. The increasing data requirements of the mobile network increase energy consumption. Energy efficiency‐based approaches also impact network coverage and throughput. Therefore, developing an energy‐efficient network with optimal coverage and throughput is considered a challenging issue. It can be resolved with optimal deployment of Base Station (BS), Relay Station (RS), and minimizing power consumption. In this research, a joint clustering‐based deployment technique is proposed for BS–RS deployment by considering the network throughput and coverage ratio. After enabling optimal BS–RS deployment, the network traffic is estimated with an On‐demand real‐time traffic estimation framework (ODTE). It estimates user association values using Beacon frames. In addition, the Relay Assisted Base station Power Scheduling (RABPS) approach to minimize power consumption is included. Based on Erlang's probability, the RABPS algorithm is enhanced with sleep mode activation during off‐peak hours. The proposed 5G network ensures uninterrupted connectivity and energy efficiency with varying time slots of power scheduling. The throughput performance of the clustering‐based approach is increased with a coverage ratio of 88%. The simulation results show the superiority of the proposed 5G BS–RS deployment and power scheduling in terms of throughput, coverage ratio, and power consumption. [ABSTRACT FROM AUTHOR]

A heterogeneous network, also known as a HetNet, is a network made up of numerous distinct wireless network nodes placed throughout the cellular service coverage area. These nodes have differing features and capabilities. In some areas, the user density may be high or a single macro eNB cannot supply good coverage. This problem can be solved by deploying low-power nodes, such as pico-cells, within the range of a macro-cell. A model built of macro eNBs and pico eNBs, used to fulfill machine-to-machine (M2M) and human-to-human (H2H) devices, no matter how different is the quality of service (QoS), is the main topic of this paper. Furthermore, the paper presents a method to associate cells and balance loads on the network for both M2M and H2H devices, by utilizing a new scheme based on Q-learning. The scheme employs two independent algorithms, where both of them are based on Q-learning. The performance of the proposed scheme is assessed by comparison in two ways: traditional comparison and a Q-learning based scheme deployed in the UE devices, to compare the H2H and M2M blocking probability with the M2M uplink transmission power. As concluded from the results of testing the proposed scheme, the blocking probability of M2M and H2H devices is reduced by about 20–30%. Furthermore, the uplink transmission power of M2M devices is reduced by 50% even under high load conditions, which makes this scheme power-efficient. [ABSTRACT FROM AUTHOR]

Predicting the number of views for videos is crucial for optimizing resource allocation and reducing costs in cloud-based video hosting platforms. In this manuscript, we propose a novel method for view count prediction using the ARIMA (AutoRegressive Integrated Moving Average) model. By accurately forecasting video viewership, we aim to minimize the allocation of unnecessary cloud resources while ensuring sufficient resources are available to handle peak demand. Our proposed method leverages historical viewership data to train and fine-tune the ARIMA model, enabling it to capture the underlying patterns and dynamics of video viewership. Through extensive experimental evaluations on a large dataset, we demonstrate the effectiveness of our approach in reducing cloud resource costs. Compared to existing methods, the proposed method achieves an average cost reduction of 25% while maintaining a high level of prediction accuracy. Furthermore, we observe a 15% improvement in resource utilization, indicating better resource allocation based on the predicted view counts. [ABSTRACT FROM AUTHOR]

Multiple communication applications such as high-quality video streaming, IoT, cellular vehicle to anything, augmented reality, virtual reality, and low-latency web browsing make the cellular network heterogeneous. To seamlessly support heterogeneous functionality in the upcoming 6G mobile network, the open radio access network (O-RAN) Alliance is being formed. The O-RAN Alliance is a step towards defining a standard interface between systems. It aims to reduce complexity and accelerate the deployment of 6G mobile networks. However, in deploying the 6G mobile network, the efficient sharing of resources among heterogeneous users is challenging. We considered a novel ultra-dense heterogeneous 6G O-RAN-based cellular network architecture and proposed a multi-objective particle swarm optimization at both small cell base stations (SBSs) and macrocell base stations (MBSs) for collaborative resource optimization. Analytical expressions are derived for joint energy and spectrum optimization at SBS and MBS. The simulation results show that the proposed scheme has a noticeable effect on the optimization of the energy consumption of the system in different scenarios and prove that this algorithm has a remarkable convergence. [ABSTRACT FROM AUTHOR]

Employing multi-layer networks represents a promising approach to address the increasing demand for high data rates and efficient congestion control in cellular communication networks. This study focuses on the downlink performance of a two-tier network comprising multiple macro base stations and femto access points, where the spatial distributions of macro base stations, femto access points, and macro users follow Poisson point processes. Also, femto users are uniformly distributed within the coverage area of femto access points, each of which is subject to a backhaul constraint, limiting the number of users it can serve. Consequently, a hybrid access policy is adopted, wherein each macro user is assigned to its closest femto access point or the macro base station, based on a distance ratio criterion. Under this access model, the outage probability experienced by macro users served by femto access points is analyzed, alongside the derivation of the outage probability for macro users served by macro base stations. Both analytical derivations are further supported by computer simulations. [ABSTRACT FROM AUTHOR]

Uncertain noncausal systems (UNCSs) are uncertain singular systems that are supposed to be regular along.This study investigates two-player zero-sum games (TPZSGs) for UNCSs using the optimistic value criterion. The first step is to introduce a method to convert a linear uncertain noncausal system (UNCS) considering linear control terms into subsystems including two kinds of uncertain difference equations. Recurrence equations are derived for tackling a TPZSG subject to linear UNCSs. Using recurrence equations, we give an algorithm for solving the TPZSG subject to linear UNCSs and show how to apply the algorithm to find the saddle-point solution and the equilibrium value of this kind of game by a numerical example. To expand on these results, we provide the corresponding equations for solving TPZSGs subject to nonlinear UNCSs. Moreover, we give the saddle-point solution and equilibrium value of a TPZSG for a nonlinear UNCS considering quadratic control terms by solving the equations. [ABSTRACT FROM AUTHOR]

In the present work, orthogonal frequency division multiplexing (OFDM) is combined with wavelength division multiplexing-passive optical networks (WDMPONs) to obtain the combined benefits of both technologies for overall system improvement. performance of five OFDM signals using WDM is analyzed. An optical system is designed using the OFDM signal, and its performance is analyzed using various matrices like bit error rate (BER) and Q-factor under the effect of varying laser power. Mapping of OFDM signals is done using 16-QAM modulation. The system shows an enhancement in the performance by increasing the laser power but up to some limit, and efficient results are obtained in the 70–130 mW laser power range. [ABSTRACT FROM AUTHOR]

Data caching is a promising technique to alleviate the data traffic burden from the backhaul and minimize data access delay. However, the cache capacity constraint poses a significant challenge to obtaining content through the cache resource that degrades the caching performance. In this paper, we propose a novel two-tier caching mechanism for data caching on mobile user equipment (UE) and the small base station (SBS) level in ultra-dense 6G heterogeneous networks for reducing data access failure via cache resources. The two-tier caching enables users to retrieve their desired content from cache resources through device-to-device (D2D) communications from neighboring users or the serving SBS. The cache-enabled UE exploits millimeter-wave (mmWave)-based D2D communications, utilizing line-of-sight (LoS) links for high-speed data transmission to content-demanding mobile UE within a limited connection time. In the event of D2D communication failures, a dual-mode hybrid system, combining mmWave and microwave μ Wave technologies, is utilized to ensure effective data transmission between the SBS and UE to fulfill users' data demands. In the proposed framework. the data transmission speed is optimized through mmWave signals in line-of-sight (LoS) conditions. In non-LoS scenarios, the system switches to μ Wave mode for obstacle-penetrating signal transmission. Subsequently, we propose a reinforcement learning (RL) approach to optimize cache decisions through the approximation of the Q action-value function. The proposed technique undergoes iterative learning, adapting to dynamic network conditions to enhance the content placement policy and minimize delay. Extensive simulations demonstrate the efficiency of our proposed approach in significantly reducing network delay compared with benchmark schemes. [ABSTRACT FROM AUTHOR]

Effective sharing of the communication channel among many users, or multiple access (MA) techniques, can play a vital role in meeting the diverse demands of low latency, high reliability, massive connectivity, better fairness, and high throughput. In this context, non-orthogonal multiple access with multiple antennas, also known as multiple-input, multiple-output NOMA (MIMO-NOMA), is a promising enabling technology for fifth-generation (5G) and beyond (5G) wireless networks. The proper design of beamforming systems is one of the major difficulties in developing MIMO-NOMA. There are various ways to design beamforming for MIMO-NOMA in the literature. However, there is not much work dedicated to the survey focusing only on beamforming design in MIMO-NOMA systems. This work presents a comprehensive overview of beamforming methods in MIMO-NOMA for 5G and B5G. These strategies are classified in detail and have varied attributes, benefits, and drawbacks. As a result, future research gaps are also highlighted. Moreover, a simulation study is presented as a case study on the impact of random beamforming in various scenarios of heterogeneous environments with small and macro-cells. For this purpose, users' outage probability is simulated with various types of interference in the heterogeneous systems, including inter-cluster, cross-tier, and co-tier interferences. This analysis also helps to contrast the performance of small and macro-cells. Finally, future research directions are discussed for beamforming in MIMO-NOMA for 5G and B5G. [ABSTRACT FROM AUTHOR]

In this paper, we consider an uplink non-orthogonal multiple access (NOMA) for energy harvesting at the base station or access point in the wireless system. By exploiting energy enough, a base station or access point can serve many users at the downlink. The fixed power allocation factors are adopted, and the power splitting energy harvesting protocol brings many benefits to both the uplink and downlink of a wireless system. The closed-form expressions of outage probability are investigated and examined in a group of two users. Moreover, the optimal outage probability for two users is shown numerically. Finally, Monte Carlo simulations are presented to further support the validity of our framework and findings. [ABSTRACT FROM AUTHOR]

Featured Application: Although, during an MRI scan based on ISO/TS 10974:2018, an assessment of the enhanced tissue heating due to coupling between leads of close proximity should be performed, a specific method for this estimation has not been defined. Therefore, the aim of this work is to evaluate a numerical method, similar to the Tier 3 process, for the estimation of the deposited power at the tips of two coupled implanted leads with a 1.5 T coil. Furthermore, in a previous work, an experimental process was proposed on a parallel couple of cables with a constant distance between them; our method advances this model, allowing the calculation of the deposited power for realistic in vivo implant placements and not only for the parallel placement of leads. Our proposed method is totally numerical, as the experimental measurement of the temperature increase at the in vivo placements of implants could not be feasible. A specific method for the estimation of the induced power at the tip by an active implantable medical device (AIMD) during an MRI scan is not defined in ISO/TS 10974:2018 for the cases of devices with multiple leads or the presence of abandoned and retained leads, where coupling between two leads could take place. Therefore, the aim of this work is to evaluate a numerical method, similar to Tier 3 of ISO/TS 10974:2018, for the estimation of the deposited power at the tips of two coupled implanted leads. Specifically, the proposed methodology applies the same parameters as the standard Tier 3 process. However, these parameters are calculated for each implant in the presence of its neighbors in order to include the coupling between them. Numerical electromagnetic simulations were performed, in which a pair of generic implant leads was excited and placed at various positions relative to each other. The deposited power at the tips of the pair was analyzed based on the standard Tier 3 approach, and the results show that this could overestimate the induced power by more than 6 dB. Therefore, a modified Tier 3 numerical method for the estimation of the deposited power at their tips is proposed, which can produce a reliable calculation. This method was confirmed by evaluating various configurations of the two leads excited by orthogonal electrical fields, and also its uncertainty budget was developed. Finally, the method was repeated for different properties of the generic implants and the surrounding tissue, as well as for a pair of realistic implants and in vivo implantation trajectories. [ABSTRACT FROM AUTHOR]

Cellular coverage plays an important role in throughput enhancement. So as to increase coverage especially in the dead spots of corporate buildings and shopping malls; 'G' number of micro cells (or Femtocells) are installed. These micro cells operate on both the licensed LTE spectrum and WiFi's unlicensed spectrum in LTE-U mode. In this mode, out of 40 mSec time, WiFi Access Point utilizes the channels of unlicensed spectrum for some amount of time and for the remaining time (= T); 'G' micro cells adopt these channels. For all the channels used by micro cells, powers are assigned that endeavour to optimize the total throughput of 'G' micro cells. Further, because of allotted powers, sustainable interference only is to be created to the data sent from macro cell and other micro cells. Moreover, all the users of micro cells have to get enough signal strength from their corresponding micro cells. Besides, the throughput of the micro cells needs to exceed the desired limit. Hence, the foregoing resource allocation is tagged with 'Resource Allocation in FemTocells' (RAFT). Here, average powers are measured with closed-form solution and using these average powers, optimal solution is produced for the RAFT with computational overhead that is considerably lower than that of the prevailing 'conventional iterative algorithms' by a factor of O(10 5 ). [ABSTRACT FROM AUTHOR]

This article addresses resource allocation scheduling problems with slack due window on a single machine. Linear resource allocation and convex resource allocation are considered. Our goal is to determine the optimal schedule, the optimal slack due window, and the optimal resource allocation, minimizing various objective functions with respect to scheduling criteria (position-dependent weights with number of early jobs, number of tardy jobs, due window starting time, and window size) and resource consumption function. For the linear resource allocation problem, we study two cases where the resource compression ration is related to job and position respectively, and provide a lower bound on the number of early jobs and an upper bound on the number of tardy jobs. For the convex resource allocation problem, we provide a bi-criteria analysis of scheduling criteria and resource consumption cost. Polynomial time algorithms are developed for these problems. [ABSTRACT FROM AUTHOR]

This paper is dedicated to solving the problem of Advanced Persistent Threat (APT) attack and defense in the Industrial Internet of Things (IIoT). Due to the diversity of IIoT equipment and the inconsistency of protection capabilities, it is difficult for the existing uniform defense strategy and the random defense strategy to achieve ideal results. Considering that both attackers and defenders aim to achieve maximum benefits by paying the minimum cost, as well as the differences between devices, this paper proposes an equipment classification based differential game method for APT in IIoT. Firstly, all equipment is divided into two categories according to their protective capabilities. Secondly, the APT attack and defense process is mathematically described, and the corresponding differential game problem is formulated and analyzed theoretically. Finally, the theoretical results of this method are verified by various experiments, including the comparisons with the uniform defense strategy, the random defense strategy, and the latest model. • A new equipment-based evolutionary dynamics model is proposed. • A necessity system is established to narrow the scope of searching for Nash equilibrium. • An algorithm is designed to generate the Nash equilibrium. [ABSTRACT FROM AUTHOR]