Resource Allocation in Multi-User Cellular Networks:A Transformer-Based Deep Reinforcement Learning Approach

To meet the communication services with diverse requirements,dynamic resource allocation has shown increasing importance.In this paper,we consider the multi-slot and multi-user resource allocation(MSMU-RA)in a downlink cellular scenario with the aim of maximizing system spectral efficiency while guaranteeing user fairness.We first model the MSMURA problem as a dual-sequence decision-making process,and then solve it by a novel Transformerbased deep reinforcement learning(TDRL)approach.Specifically,the proposed TDRL approach can be achieved based on two aspects:1)To adapt to the dynamic wireless environment,the proximal policy optimization(PPO)algorithm is used to optimize the multi-slot RA strategy.2)To avoid co-channel interference,the Transformer-based PPO algorithm is presented to obtain the optimal multi-user RA scheme by exploring the mapping between user sequence and resource sequence.Experimental results show that:i)the proposed approach outperforms both the traditional and DRL methods in spectral efficiency and user fairness,ii)the proposed algorithm is superior to DRL approaches in terms of convergence speed and generalization performance.

Hybrid Block Diagonalization Precoding for Multi-User Weighted Sum-Rate Maximization

This paper studies large-scale multi-input multi-output(MIMO)orthogonal frequency division multiplexing(OFDM)communications in a broadband frequency-selective channel,where a massive MIMO base station(BS)communicates with multiple users equipped with multi-antenna.We develop a hybrid precoding design to maximize the weighted sum-rate(WSR)of the users by optimizing the digital and the analog precoders alternately.For the digital part,we employ block-diagonalization to eliminate inter-user interference and apply water-filling power allocation to maximize the WSR.For the analog part,the optimization of the PSN is formulated as an unconstrained problem,which can be efficiently solved by a gradient descent method.Numerical results show that the proposed block-diagonal hybrid precoding algorithm can outperform the existing works.

Joint Multi-User Detection with Weighting Factors for Unsourced Multiple Access

Multi-user detection techniques are currently being studied as highly promising technologies for improving the performance of unsourced multiple access systems. In this paper, we propose joint multi-user detection schemes with weighting factors for unsourced multiple access. First, we introduce bidirectional weighting factors in the extrinsic information passing process between the multi-user detector based on belief propagation (BP) and the LDPC decoder. Second, we incorporate bidirectional weighting factors in the message passing process between the MAC nodes and the user variable nodes in BP- based multi-user detector. The proposed schemes select the optimal weighting factors through simulations. The simulation results demonstrate that the proposed schemes exhibit significant performance improvements in terms of block error rate (BLER) compared to traditional schemes. .

Intelligent Energy Utilization Analysis Using IUA-SMD Model Based Optimization Technique for Smart Metering Data

Smart metering has gained considerable attention as a research focus due to its reliability and energy-efficient nature compared to traditional electromechanical metering systems. Existing methods primarily focus on data management,rather than emphasizing efficiency. Accurate prediction of electricity consumption is crucial for enabling intelligent grid operations,including resource planning and demandsupply balancing. Smart metering solutions offer users the benefits of effectively interpreting their energy utilization and optimizing costs. Motivated by this,this paper presents an Intelligent Energy Utilization Analysis using Smart Metering Data(IUA-SMD)model to determine energy consumption patterns. The proposed IUA-SMD model comprises three major processes:data Pre-processing,feature extraction,and classification,with parameter optimization. We employ the extreme learning machine(ELM)based classification approach within the IUA-SMD model to derive optimal energy utilization labels. Additionally,we apply the shell game optimization(SGO)algorithm to enhance the classification efficiency of the ELM by optimizing its parameters. The effectiveness of the IUA-SMD model is evaluated using an extensive dataset of smart metering data,and the results are analyzed in terms of accuracy and mean square error(MSE). The proposed model demonstrates superior performance,achieving a maximum accuracy of65.917% and a minimum MSE of0.096. These results highlight the potential of the IUA-SMD model for enabling efficient energy utilization through intelligent analysis of smart metering data.

Functional Confirmation Using a Medical X-Ray System of a Semiconductor Survey Meter

In recent years, semiconductor survey meters have been developed and are in increasing demand worldwide. This study determined if it is possible to use the X-ray system installed in each medical facility to calculate the time constant of a semiconductor survey meter and confirm the meter’s function. An additional filter was attached to the medical X-ray system to satisfy the standards of N-60 to N-120, more copper plates were added as needed, and the first and second half-value layers were calculated to enable comparisons of the facility’s X-ray system quality with the N-60 to N-120 quality values. Next, we used a medical X-ray system to measure the leakage dose and calculate the time constant of the survey meter. The functionality of the meter was then checked and compared with the energy characteristics of the meter. The experimental results showed that it was possible to use a medical X-ray system to reproduce the N-60 to N-120 radiation quality values and to calculate the time constant from the measured results, assuming actual leakage dosimetry for that radiation quality. We also found that the calibration factor was equivalent to that of the energy characteristics of the survey meter.

Detection of Water Meter Digits Based on Improved Faster R-CNN

In order to more accurately detect the accuracy of word-wheel water meter digits, 2000 water meter pictures were produced, and an improved Faster-RCNN algorithm for detecting water meter digits was proposed. The improved Faster-RCNN algorithm uses ResNet50 combined with FPN (Feature Pyramid Network) structure instead of the original ResNet50 as the feature extraction network, which can enhance the accuracy of the model for small-sized digit recognition;the use of ROI Align instead of ROI Pooling can eliminate the error caused by the quantization process of the ROI Pooling twice, so that the candidate region is more accurately mapped to the feature map, and the accuracy of the model is further enhanced. The experiment proves that the improved Faster-RCNN algorithm can reach 91.8% recognition accuracy on the test set of homemade dataset, which meets the accuracy requirements of automatic meter reading technology for water meter digital recognition, which is of great significance for solving the problem of automatic meter reading of mechanical water meters and promoting the intelligent development of water meters.

Development Of Multi-users Multi-function Watt-hour Meter Based On ATT7022B

According to the feature of city’s apartment building in China,a kind of Multi-users Watt-hour Meter based on ATT7022B has been developed in this paper.The master-slave MCU control model and the principles of Time Sharing Multiplex are adopted in this Watt-hour Meter,its function includes the measurement of current, voltage,power,power factor and the overload protection.It supports remote reading,pre-payment,multi-rate and etc. The practice shows that this meter has high accuracy,runs stable.It has wide prospect in the future market.

Controlling Congestion in Al-Seeb Highway Using Ramp Metering (Case Study)

This paper represents a case study of traffic congestion within a section on Al Seeb Street highway due to the on-ramp merging of vehicles that causes a bottleneck in the mainline road. It studies the efficiency of installing ramp metering within a ramp within the selected study zone. This is done by simulating the collected data using Vissim software by drawing three one-hour-long scenarios;the first scenario reflects the data collected for 30 minutes duration and is used as a base scenario to draw the other two scenarios, which are reflected as factored-up scenarios to create a situation observed in the early morning in the study zone at 6:00-7:00 in which slowing down of speeds exist, and breakdown is raised in working days. The two factoring-up scenarios were as follows: one without ramp metering and the other without ramp metering. Each scenario was calibrated and run five times with random seeds, and then the average was considered. The simulation examines the ability of RM to smooth traffic in mainline and reduce queuing on on-ramp roads within the selected study zone by comparing the performance of the network for the scenarios and comparing them in terms of the overall delays, number of stops and the average speeds for the vehicles within the mainline. The results showed a good performance reflected by the scenario with ramp metering with a reduction of the overall delay, a decrease in stops number and an increase of the average speed were achieved. For the base scenario, a visualization (video extracted from Vissim software) was extracted, showing no need to install RM with an associated table showing a number of stops equal to zero with an average speed of 102.74 km/h and a total delay of 6045 seconds. For the second scenario with no RM, a visualization was extracted showing a slowing down of speeds for vehicles within the mainline while vehicles merging from the on-ramp and need to be controlled with a table showing a number of stops equal to 16 and an average speed equal to 58 km/h and a total delay of 916,874 seconds. For the third scenario with RM, a visualization was extracted showing good control of the second scenario with a table showing the number of stops equal to 6, an average speed equal to 61 km/h and a total delay equal to 484,466 seconds. Ten literatures in regard to this study have been reviewed. The data collected are quantitative, which are collected using an indirect manual counting method and then the data is used to feed the software for simulation.

Closed BER expression of multi-user DS UWB systemsin indoor fading channel

The bit error rate （BER） performance of multi-user direct spreading bi-phase shift keying （DSBPSK） direct impulse ultra wideband （UWB） systems is analyzed and simulated based on a statistical indoor multi-path fading channel model. The BER of the system is theoretically derived and given in closed form, which is expressed in terms of channel parameters and system parameters such as pulse width parameter, pulse repeat period, user number and pulse waveform. With this BER expression, the effect of these parameters on the system performance can be evaluated in a uniform way. Simulation results well match the theory numerical results, and prove that the multi-access interference （MAI） of DS-BPSK UWB is a normal distribution.

Adaptive resource allocation in downlink multi-user MC-CDMA systems

The joint channel and power allocation in the downlink transmission of multi-user multi-carrier code division multiple access（MC-CDMA） systems are investigated and the throughput maximization problem is considered as a mixed integer optimization problem. For simplicity of analysis, the problem is divided into two less complex sub-problems： power allocation and channel allocation, which can be solved by a suboptimal adaptive power allocation （APA）algorithm and an optimal adaptive channel allocation （ACA） algorithm, respectively. By combining APA and ACA algorithms, an adaptive channel and power allocation scheme is proposed. The numerical results show that the proposed APA algorithm is more suitable for MC-CDMA systems than the conventional equal power allocation algorithm, and that the proposed channel and power allocation scheme can significantly improve the system throughout performance.

Optimal subcarrier allocation for cognitive radio with multi-user OFDM and distributed antenna

The subcarrier allocation problem in cognitive radio（CR）networks with multi-user orthogonal frequency-division multiplexing（OFDM）and distributed antenna is analyzed and modeled for the flat fading channel and the frequency selective channel,where the constraint on the secondary user（SU）to protect the primary user（PU）is that the total throughput of each PU must be above the given threshold instead of the ＂interference temperature＂.According to the features of different types of channels,the optimal subcarrier allocation schemes are proposed to pursue efficiency（or maximal throughput）,using the branch and bound algorithm and the 0-1 implicit enumeration algorithm.Furthermore,considering the tradeoff between efficiency and fairness,the optimal subcarrier allocation schemes with fairness are proposed in different fading channels,using the pegging algorithm.Extensive simulation results illustrate the significant performance improvement of the proposed subcarrier allocation schemes compared with the existing ones in different scenarios.

Multi-User Connection Performance Assessment of NOMA Schemes for Beyond 5G

Non-orthogonal multiple access(NOMA)is proved to be useful to satisfy the requirements of beyond 5th generation such as massive multi-user connection.Here we compare the performances of two NOMA schemes:low code rate spreading(LCRS)scheme and interleaver division multiple access(IDMA)scheme.It is found that LCRS is superior to IDMA when number of users is small due to coding gain achieved.While IDMA is preferred when number of users is high because repetition applied in IDMA can suppress multi-user interference effectively.And interleaver is important in IDMA for randomizing the interference.Also,this paper evaluates the impact of channel decoder.It is observed that Log-MAP decoder has much better performance than that of Max-Log-MAP when number of users is large.Thus,it is recommended to use Log-MAP decoder in NOMA in high user overloading case.We also compared the performance of NOMA by using different type of channel codes.We find that NOMA using specific convolutional code has a better performance than that of using specific LDPC code when number of users is high.

Complex field network-coded cooperation based on multi-user detection in wireless networks

Cooperative communication can achieve spatial diversity gains,and consequently combats signal fading due to multipath propagation in wireless networks powerfully.A novel complex field network-coded cooperation（CFNCC） scheme based on multi-user detection for the multiple unicast transmission is proposed.Theoretic analysis and simulation results demonstrate that,compared with the conventional cooperation（CC） scheme and network-coded cooperation（NCC） scheme,CFNCC would obtain higher network throughput and consumes less time slots.Moreover,a further investigation is made for the symbol error probability（SEP） performance of CFNCC scheme,and SEPs of CFNCC scheme are compared with those of NCC scheme in various scenarios for different signal to noise ratio（SNR） values.

Multi-User Detection for Spatial Modulation toward 5G Wireless Communications

Spatial modulation(SM) is a class of novel multiple-input multiple-output(MIMO) techniques toward future wireless communications,which activates only one transmit antenna in each time slot,so as to reduce the number of RF chains for saving the implement cost.Meanwhile,considering its application in 5G systems with multiple users,the detection of multi-user spatial modulation has drawn greater attention.In this paper,a pair of efficient detectors are proposed for multi-user spatial modulation.Specially,a threshold-aided approximate message passing(T-AMP) detector is proposed with the purpose of reducing the computational complexity of traditional structured approximate message passing(Str-AMP) detector.In addition,a novel probability sorting aided approximate message passing detector,called probability-ranking-aided AMP detector(P-AMP),is also proposed with the purpose of improving the performance.Simulation results show that the proposed T-AMP detector is able to achieve similar performance as traditional StrAMP with lower complexity,while the proposed P-AMP detector exhibits a better symbol error rate(SER) performance with similar complexity.

Virtual reality for immersive multi-user firefighter-training scenarios

Background Virtual reality(VR)applications can be used to provide comprehensive training scenarios that are difficult or impossible to represent in physical configurations.This includes team training for emergency services such as firefighting.Creating a high level of immersion is essential for achieving effective virtual training.In this respect,motion-capture systems offer the possibility of creating highly immersive multi-user training experiences,including full-body avatars.Methods This study presents a preliminary prototype that helps extin-guish a virtual fire on a container ship as a VR training scenario.The prototype provides a full-body and multi-user VR experience based on the synthesis of position data provided by the motion-capture system and orientation data from the VR headsets.Moreover,the prototype facilitates an initial evaluation of the results.Results The results confirm the value of using VR for training procedures that are difficult to implement in the real world.Furthermore,the results show that motion-capture-based VR technologies are particularly useful for firefighting training,in which participants can collaborate in difficult-to-access environments.However,this study also indicates that increasing the immersion in such training remains a challenge.Conclusions This study presents a prototypical VR application that enables the multi-user training of maritime firefighters.Future research should evaluate the initial results,provide more extensive training scenarios,and measure the training progress.

Cryptanalysis and Improvement of the Multi-User QPCE Protocol with Semi-Honest Third Party

In a recent work [Quantum Inf. Process 12 （2013） 1077], a multi-user protocol of quantum private comparison of equality （QPCE） is presented. Here we point out that if we relax the constraint of a semi-honest third party, the private information of the users will be totally leaked out to the third party. A special attack is demonstrated in detail. Furthermore, a possible improvement is proposed, which makes the protocol secure against this kind of attack.

Multi-user performance analysis of differential frequency hopping system over Rayleigh-fading channel

A novel non-coherent detection scheme for differential frequency hopping(DFH)system is proposedin asynchronous multi-user environments over Rayleigh-fading channels.The synchronous and asyn-chronous multi-user performances of DFH with the conventional detection scheme and this novel detectionscheme are analyzed,respectively.The performance results are validated with simulation.The results ofanalyses and simulations prove two conclusions.Firstly,the performance of asynchronous multi-user DFHsystem overcomes that of synchronous multi-user DFH system over Rayleigh-fading channel.Secondly,the novel detection scheme can achieve better performance than the conventional non-coherent detectionscheme in asynchronous multi-user environments.

Joint Source and Relay Precoding/Beamforming Algorithm for OFDM Multi-user Cooperative Relay Systems

In order to reduce the feedback load of multi-user orthogonal frequency division multiplexing （ OFDM ） -based wireless systems, a practiral limited bits feedback precoding algorithm is proposed with direct source-destination link based on amplify-and- forward cooperative relay network under frequency selective fading channels. Using joint minimum mean square error（MMSE） filter, the receiving decoding matrix is designed for each user in the paper. Source precoding （beamforming） matrix is optimized with convex function of weight mean square error （MSE）. Relay precoding matrix is obtained under MSE decomposition and convex optimization. The precoding matrix index is fed back for clustered subcarrier of OFDM with limited feedback. Then using interpolation algorithm, all precoding matrices are achieved at base station （BS） and relay nodes. Simulations indicate the effectiveness of the proposed limited feedback joint precoding and beam_formlng design. The proposed method can improve bit error rate （BER） performance and obtain better sum-rate performance in contrast to existing algorithms. It displays the BER performance is close to that of the unquantified precoding feedback method.

Wavelet Packet Domain LMS Based Multi-User Detection

An improved wavelet packet domain least mean square （IWPD-LMS） based adaptive muhiuser detection algorithm is proposed. The algorithm employs the wavelet packet transform to rewhiten the input data, and chooses the best wavelet packet basis according to a novel convergence contribution function rather than the conventional Shannon entropy. The theoretic analyses show that the inadequacy of the eigenvalue spread of the tap-input correlation matrix is ameliorated, thus the convergence performance is improved greatly. The simulation result of convergence performance and bit error rate（BER） performance as a function of the signal power to noise power ratio（SNR） are presented finally to prove the validity of the proposed algorithm.

Deep reinforcement learning-based optimization of lightweight task offloading for multi-user mobile edge computing

To improve the quality of computation experience for mobile devices,mobile edge computing(MEC)is a promising paradigm by providing computing capabilities in close proximity within a sliced radio access network,which supports both traditional communication and MEC services.However,this kind of intensive computing problem is a high dimensional NP hard problem,and some machine learning methods do not have a good effect on solving this problem.In this paper,the Markov decision process model is established to find the excellent task offloading scheme,which maximizes the long-term utility performance,so as to make the best offloading decision according to the queue state,energy queue state and channel quality between mobile users and BS.In order to explore the curse of high dimension in state space,a candidate network is proposed based on edge computing optimize offloading(ECOO)algorithm with the application of deep deterministic policy gradient algorithm.Through simulation experiments,it is proved that the ECOO algorithm is superior to some deep reinforcement learning algorithms in terms of energy consumption and time delay.So the ECOO is good at dealing with high dimensional problems.