Communication Performance Research Articles

Efficient topology reconfiguration for NoC-based multiprocessors: A greedy-memetic algorithm

In multi-core processor systems, the Network-on-Chip (NoC) serves as a vital communication infrastructure. To ensure chip reliability during potential failures, this paper proposes a two-level topology reconfiguration algorithm with core-level redundancy technology. Initially, a heuristic topology reconfiguration method utilizing a greedy strategy is proposed to perform local replacement of faulty processing elements (PEs) and generate an initial logical topology with shorter interconnection paths between PEs. Then, an intelligent optimization method based on memetic algorithm is introduced to optimize the generated initial topology for better communication performance. The experimental results demonstrate that compared to the current state-of-the-art algorithm, the proposed algorithm achieves an average improvement of 13.92% and 30.83% on various size topologies in terms of distance factor (DF) and congestion factor (CF), which represent communication delay and traffic balance respectively. The proposed algorithm significantly enhances the communication performance of the target topology, mitigating communication latency and potential congestion problems.

Optical chaotic communication system based on time-delayed shift keying and common-signal-induced synchronization

Aiming at the difficulty of traditional chaotic-shift-keying (CSK) systems in resisting return map attacks, we propose an optical chaotic communication system based on time-delayed shift keying and common-signal-induced synchronization. This scheme combines amplified spontaneous emission (ASE) noise, phase modulator (PM), and fiber Bragg grating (FBG) to achieve dual masking in both intensity and phase fields, achieving 10Gb/s information transmission. A common-signal-induced method is used to achieve the synchronization of the system. Moreover, by shifting the time delay as the message-feeding method, the return map attack is effectively resisted, to prevent the amplitude and frequency information of the chaotic attractor from being exposed. In terms of confidentiality and communication performance, this scheme demonstrates good performance of time delay signatures (TDSs) concealment and long-distance transmission capability. In addition, this scheme maintains high sensitivity to key parameters and achieves better confidentiality while increasing the key space.

Modulation effect of focusing mirror on beam propagation through anisotropic turbulence

In this study, we modulated the Bessel-Gaussian (BG) beam using a focusing mirror to enhance the performance of wireless optical communication (WOC) while considering the angles between turbulence cells and the transmitted direction when beams propagate through anisotropic atmospheric turbulence along a slant path. Numerical results reveal that when the BG beam is modulated by a focusing mirror with a focusing length of 1 km, the detection probability of orbital angular momentum (OAM) is increased by 9.06% compared with the unmodulated BG beam when the OAM quantum number is 1. Simultaneously, this modulation method effectively reduces the bit error rate and enhances the channel capacity in OAM-based WOC. Furthermore, we observed that the smaller the OAM number, the better the effect of the modulation. Through our analysis, we identified that the most significant distortions in OAM mode propagation occur at the exponential parameter approximately 3.1 in the modified von Karman spectrum. Moreover, we demonstrated that the effects of the anisotropic tilt angle can not be negligible for beams through a slant path. Therefore, the modulation of the focusing mirror, in combination with a well-designed propagation direction that takes appropriate angles into account, can significantly improve the overall quality and performance of optical communication systems.

Experimental investigation on backscattering interference cancellation for full-duplex UOWC based on time-reversal preprocessing

A co-frequency and full-duplex (FD) underwater optical wireless communication (UOWC) system has the potential to significantly enhance spectral efficiency, reduce complexity, and further facilitate UOWC networking. However, the inevitable performance degradation due to self-interference introduced by backscattering presents a significant challenge. In this paper, we first experimentally explore the inherent characteristics of the underwater backscattering channel. Subsequently, we propose a digital-domain backscattering interference cancellation (BIC) algorithm for FD-UOWC systems, incorporating a time-reversal preprocessing. We then experimentally investigate the communication performance of an FD-UOWC system to verify the feasibility of the proposed BIC algorithm under different channel conditions. The experimental results validate the effectiveness of the proposed method, yielding substantial enhancements in bit error rate performance across diverse scenarios.

Spot position scheme on a quadrant detector for a spaceborne laser communication system

The paper proposes a spot positioning method based on a four-quadrant detector for the limited computing power and memory of spaceborne laser communication, in which the adaptive interpolation segmentation (AIS) algorithm is used to fit the theoretical position curve. The algorithm uses linear operations though the fitting process and the simulated result indicates that it has higher positioning accuracy in the center area of the quadrant detector. A spot receiving and positioning system was built for experimentation and the final location of the spot was calculated. The positioning error is analyzed to evaluate the performance of the whole system. It is shown that the positioning accuracy is highest in the stable communication area of the system. In result, the scheme achieves high accuracy with simple operations, which is more suitable for spaceborne laser communication systems to release more performance for communication.

Joint Radar Jamming and Communication System Design Based on Universal Filtered Multicarrier Chirp Waveform

In this article, we propose a joint waveform based on universal filtered multicarrier (UFMC) chirp for radar jamming and communication joint systems. Modulation of radar jamming chirp signals and communication signals on different subcarrier groups in the UFMC sub-band is used to achieve the waveform design. The jamming signal in the waveform contains a frequency shift coefficient that depends on the delay time, which can effectively improve the anti-frequency hopping ability and enhance the overall jamming efficiency. Simultaneously jamming signals can provide assistance in channel estimation and equalization of communication, improving the information transmission quality of communication subsystems. We concluded through reasonable trade-off analysis that the combined weight of radar jamming and communication is closely related to the overall performance of the waveform. The simulation results show that the proposed UFMC chirp synthesized waveform has good jamming and communication performance. Software defined radio (SDR) simulation experiments demonstrated the effectiveness of this method in practical environments.

Communication Strategy Practices and Performance of The County Government of KISII

Communication Strategy Practices and Performance of The County Government of KISII

A Survey of the Mechanisms Impairing Optical fiber communications performance

The growth of information technology and Internet networks, combined with nearly daily use and many subscribers, has caused the volume of data stored in communication systems to balloon to enormous proportions. Optical fiber cable is the medium for data transfer because it has a bandwidth far more significant than other transmission methods and can span significantly greater distances. The transmission of information from one location to another can be accomplished via a technique known as fiber-optic communication. This involves passing pulses of light over an optical fiber. Optical fiber performance is affected by many effects, including attenuation, dispersion, scattering, and bending. It is feasible to enhance the performance of optical fibers for communications by utilizing carbon nanotubes and multiple coding technologies. This can be accomplished via integrated optical circuits or by making the cable more advanced and developing it further. Photosynthesis is accomplished by utilizing carbon tubes and the optical property inside them.

Equivalent analysis model of a GaN LED used as a receiver

In general, visible light communication (VLC) uses LEDs as transmitters. However, LEDs can serve as receivers to construct a simple duplex VLC system that uses only two LEDs instead of one LED and one photo-diode (PD). There is a lack of effective equivalent analysis models for characterizing and evaluating the inherent behavioral characteristics of LEDs used as receivers. This paper presents an equivalent analysis model for GaN LEDs as receivers. First, based on the proposed receiving equivalent circuit model, a third-order signal transmission mathematical analysis model is established, revealing the transmission relationship between the photocurrent and output voltage. Further research is conducted on the impact of parameter changes on the bandwidth, and the model can be simplified into a first-order low-pass mathematical analysis model under specific conditions, providing theoretical support for improving the bandwidth of LED receiving applications. The experimental results also confirm the theoretical predictions. This research result holds significant importance for revealing the intrinsic mechanisms and the improved optical communication performance of LEDs for effective reception.

Development of a validated assessment tool for medical students using simulated patients: an 8-year panel survey

BackgroundThe use of simulated patients (SPs) to assess medical students’ clinical performance is gaining prominence, underscored by patient safety perspective. However, few reports have investigated the validity of such assessment. Here, we examined the validity and reliability of an assessment tool that serves as a standardized tool for SPs to assess medical students’ medical interview.MethodsThis longitudinal survey was conducted at Keio University School of Medicine in Japan from 2014 to 2021. To establish content validity, the simulated patient assessment tool (SPAT) was developed by several medical education specialists from 2008 to 2013. A cohort of 36 SPs assessed the performance of 831 medical students in clinical practice medical interview sessions from April 2014 to December 2021. The assessment’s internal structure was analyzed using descriptive statistics (maximum, minimum, median, mean, and standard deviation) for the SPAT’s 13 item total scores. Structural validity was examined with exploratory factor analysis, and internal consistency with Cronbach’s alpha coefficients. The mean SPAT total scores across different SPs and scenarios were compared using one way analysis of variance (ANOVA). Convergent validity was determined by correlating SPAT with the post-clinical clerkship obstructive structured clinical examination (post-CC OSCE) total scores using Pearson’s correlation coefficient.ResultsOf the 831 assessment sheets, 36 with missing values were excluded, leaving 795 for analysis. Thirty-five SPs, excluding one SP who quit in 2014, completed 795 assessments, for a response rate of 95.6%. Exploratory factor analysis revealed two factors, communication and physician performance. The overall Cronbach’s alpha coefficient was 0.929. Significant differences in SPAT total scores were observed across SPs and scenarios via one-way ANOVA. A moderate correlation (r =.212, p <.05) was found between SPAT and post-CC OSCE total scores, indicating convergent validity.ConclusionsEvidence for the validity of SPAT was examined. These findings may be useful in the standardization of SP assessment of the scenario-based clinical performance of medical students.

Enhancing the performance of LiFi communication with OSTBC, QAM, and OFDM: High-capacity, low-complexity transceiver design

Light fidelity (LiFi) is one of the most promising areas within wireless optical communication system. It provides many benefits, including high capacity, improved security and enhanced cost-effectiveness. However, there is still challenges which are link blockages, attenuation, interference and bandwidth restriction of modulation techniques. Orthogonal space–time block coding (OSTBC) offers a suitable solution to address link blockage by providing an alternative communication channel between the transmitter and the receiver. OSTBC has more tolerate to the practical channel impact limitation such as attenuation and interference that may occur in overlapping regions. In addition, the use of the OSTBC technique enhances the system’s ability to transfer data as the transmission rate is duplicated by the number of transmitters and receivers. This paper proposes the utilisation of a LiFi transceiver-based OSTBC that employs quadrature amplitude modulation (QAM) in conjunction with orthogonal frequency-division multiplexing (OFDM). Co-simulation tools have been done by integrated Matlab with Optisystem, were used in the design of LiFi transceiver with all assumption required. The findings reveal the capability of LiFi transceiver of transmitting rate up to 15 Gbps with maintaining a satisfactory bit error rate (BER) of 10−4 over a link range of 200 m evenin the presence of realistic channel effects. Moreover, the LiFi transceiver’s structure used does not incorporate optical amplifier components, resulting in reduced computational complexity compared to conventional LiFi transceivers. The proposed system proved its progress over the previous work under the influence of the same input effects.

An integrated waveform design method for underwater acoustic detection and communication

AbstractIn recent years, the integrated system for underwater detection and communication (ISUDC) has become one of the important research directions. At present, the efficiency of the existing shared signals carrying communication information is low, and the synchronization performance needs to be further improved. So, this paper proposes an integrated waveform design scheme for ISUDC based on the carrier with good detection performance and binary phase shift differential keying (DBPSK). In this scheme, the signal with better underwater detection performance (e.g. Linear Frequency Modulation, LFM) is selected as the carrier, and DBPSK is used as the modulation mode to modulate the communication symbols into the carrier. However, the correlation of the detection signal will be destroyed. Thus, the down‐frequency detection signal (e.g. ngLFM) is superimposed into the signal to form a shared signal (LFM‐DBPSK‐ng, LDN). The detection performance, synchronization performance and communication performance of the shared signal are analyzed by ambiguity function, cross‐correlation and BER, respectively. In addition, according to the proposed scheme, the shared signal HFM‐DBPSK‐ng (HDN) is generated by using HFM as carrier. The comparative simulation experiments are carried out with the existing LFM‐BPSK signals. Experiments show that both LDN and HDN have better performance compared to the other shared signals, which proves the effectiveness of the integrated waveform design scheme for ISUDC proposed in this paper.

A study on resource allocation scheme for self-powered visible light communication and positioning systems

In this work, a novel resource allocation scheme is proposed for the self-powered visible light communication and positioning (SPVLCP) system based on orthogonal frequency division multiplexing (OFDM). This scheme can balance the performance of communication, positioning, and energy harvesting by optimizing the power splitting (PS) at the receiver and power allocating on each subcarrier using the multi-verse optimization (MVO) algorithm. The performance of the SPVLCP system using the proposed resource allocation scheme is investigated through simulation and experiment for different constraint conditions and transmission rates. The results indicate that the SPVLCP system using the proposed resource allocation scheme has better performance compared with that using the uniform power allocation scheme.

FedCGS: Leverage Feature Compression and Conditional GAN for Privacy Protection and Efficient Communication in Federated Learning

Federated learning is a distributed machine learning technique that can train models from decentralized data, collaboratively building central models and protecting data privacy by passing partial model updates rather than raw data in each iteration of model learning. However, recent work has shown that the information during the exchange between the server and the client is still vulnerable to gradient-based privacy attacks, and traditional privacy protection methods can incur significant costs (such as communication consumption and performance evaluation). Therefore, we need an algorithm that can protect data privacy while reducing communication costs and performance losses. Here, we propose a federated learning framework FedCGS that leverages conditional generation adversarial networks and feature compression in order to achieve privacy protection while maintaining competitive model performance and effectively improving communication efficiency. We divided the local network of each client into feature extractor and public classifier, and kept the extractor local to protect privacy, and sent classifier and client generator to the server for aggregation and update through singular value decomposition, so as to improve the performance of the local network and efficient communication. A lot of experimental data prove that FedCGS can improve the performance of local model better than traditional federation learning, and improve the communication efficiency better than common conditional generation adversarial network. Therefore, we believe that FedCGS has better federal learning potential

Research on Hybrid Relay Protocol Design and Cross-Layer Performance Based on NOMA

Wireless and power line communication hybrid relay technology can realize complementary advantages and comprehensively improve the communication coverage and performance of power Internet of Things. In order to study the mechanism of the physical layer and Media Access Control (MAC) layer algorithm that affects the performance of hybrid relay systems, the cross-layer performance modeling, optimization, and simulation analysis are carried out for the non-orthogonal multiple access (NOMA) technology. Firstly, a two-hop NOMA media access control protocol is designed based on the CSMA algorithm. Considering the effects of non-ideal channel transmission at the physical layer and competitive access at the MAC layer on the system performance, a cross-layer performance analysis model of hybrid wireless and power line communication relay system under NOMA is established. Finally, a cross-layer optimization model based on multi-objective programming is established for the hybrid relay system. By analyzing the relationship between transmitting power and performance index, the joint optimization of transmitting power and power distribution factor between users is realized. Simulation results verify the validity and reliability of the proposed cross-layer model. The results show that the hybrid relay algorithm combined with NOMA and CSMA can effectively improve the performance of the system throughput, packet loss probability, and delay.

Machine learning and IoT based MIMO-UWB Antenna Integrated with Ku-Band for Seamless Wireless Communication

The implementation of machine learning algorithms with advanced antenna technologies, such as Multiple Input Multiple Output Ultra-Wideband -UWB- and Cup-Ban, has emerged as a powerful method for improving wireless communication systems. This research focuses on the effectiveness of applying three machine learning algorithms, which are Deep Q-Networks -DQN- , Label Propagation, and Model-Agnostic Meta-Learning (MAML). Using several experiments, we analyzed the throughput, latency, and packet loss of every algorithm. These were part of the project designed on a wireless signal combined with MIMO-UWB and Ku-Band. Nevertheless, MAML has the highest average throughput of 261.3 Mbps, and the other algorithms follow one by one: DQN with 252.5 Mbps and Label Propagation with 240.6 Mbps. As to latency, the lowest average is 9.0 ms and 11.0 ms for DQN and 14.2 ms for Label Propagation. Finally, MAML proved the least packet losses with the average value of 0.18% and DQN with 0.39% and 0.73% of Label Propagation .The results presented above indicate that by adapting more quickly to changing wireless environments, MAML effectively optimizes communication performance in terms of throughput, latency, and packet loss. Specifically, through its ability to accelerate the allocation of resources and management of networks as a whole, more frequent and rapid learning with MAML results in better system reliability and data integrity.

Single input multiple output maze shaped array antenna for millimeter wave applications

In this work, maze shaped single input multiple output (SIMO) antenna array resonating at multiband is developed with a dimension 299 mm × 175 mm x 0.19 mm for THz and millimeter range applications at frequencies ranging from 30 GHz to 300 GHz. Initially 2-element array was designed with a return loss of −25dB and a gain of 4 dB which will be insufficient for long distance performance in mm wave communication. Hence, a 4-element array rectangular maze shaped single antenna was designed with improved return loss of −46dB and better gain of 8.1 dB which can support beyond 5G mm wave communication. The performance analysis for the designed antenna is verified with the various substrates such as Nylon, FR-4, and Rogers. The simulation results shows that the designed antenna provides better performance with Nylon substrate. The maximum return loss obtained is −46dB at 40 GHz while using Nylon substrate with efficiency of 97.5%.

Codebook-Based Solutions for Reconfigurable Intelligent Surfaces and Their Open Challenges

Reconfigurable intelligent surfaces (RIS) is a revolutionary technology to cost-effectively improve the performance of wireless networks. We first review the existing framework of channel estimation and passive beamforming (CE & PBF) in RISassisted communication systems. To reduce the excessive pilot signaling overhead and implementation complexity of the CE & PBF framework, we conceive a codebook-based framework to strike flexible tradeoffs between communication performance and signaling overhead. Moreover, we provide useful insights into the codebook design and learning mechanisms of the RIS reflection pattern. Finally, we analyze the scalability of the proposed framework by flexibly adapting the training overhead to the specified quality-of-service requirements and then elaborate on its appealing advantages over the existing CE & PBF approaches. It is shown that our novel codebook-based framework can be beneficially applied to all RIS-assisted scenarios and avoids the curse of model dependency faced by its existing counterparts, thus constituting a competitive solution for practical RIS-assisted communication systems.

The Impact of Relationship Intelligence on Team-based Practice: An Application for the Private Sector in Mainland China

This article aims to examine the impact of developing and applying relationship intelligence in team-based practice to provide a clear understanding of the role relationship intelligence plays in team productivity in mainland China. Relationship intelligence, a component of emotional intelligence, focuses on interpersonal interactions that are crucial in team-building but receives less attention. Exploratory qualitative research was undertaken, with emotional intelligence as the theoretical framework and the input-process-output criteria indicating group effectiveness. Data collection was based on semi-structured interviews with managers and staff of the private sector based in mainland China after utilizing the Strengths Deployment Inventory 2.0 as a learning tool. The findings identify three ways in which the integration of relationship intelligence positively affected team practice: high overall performance, a positive work climate, and improved attitudes toward coworkers and work-related tasks. The positive outcomes provide researchers and practitioners with valuable information on how relationship intelligence might be leveraged to enhance communication, collaboration, and overall team performance.

Tradeoff Between Age of Information and Operation Time for UAV Sensing Over Multi-Cell Cellular Networks

Unmanned aerial vehicles (UAVs) have a significant potential for sensing applications in further cellular networks due to their extensive coverage and flexible deployment. In this paper, we consider a multi-cell cellular network with a cellular-connected UAV, which senses data with onboard sensors and uploads sensory data to the ground base stations (BSs). To evaluate the freshness of sensory data, we employ the concept of age of information (AoI), which is defined as the time elapsed since the latest successful transmission of sensory data. A lower AoI implies fresher sensory data, which may lead to the increase of UAV operation time. To balance such tradeoff, we aim to minimize the weighted sum of operation time and total AoI for the UAV by jointly optimizing transmission scheduling, BS association, as well as UAV trajectory. The problem is formulated as a mixed-integer nonlinear programming (MINLP) problem, which is difficult to solve due to the time-varying propagation channels. To this end, we first characterize the average communication performance with statistic channel information, and then develop a search algorithm to obtain the optimal solution via employing the optimal structure as well as convex optimization techniques, while a low-complexity Double Graph based Algorithm (DGA) is developed to obtain a suboptimal solution. Then, by taking into account the site-specific performance and making fast decisions online, we propose a Deep reinforcement Learning Algorithm (DLA). Compared to DGA, DLA can adapt to the specific local environment and obtain a solution more rapidly once the training process is completed. Simulation results show that the proposed algorithms outperform the benchmarks about 30%, and achieve flexible tradeoff between operation time and AoI of UAV sensing, which is not available by considering just one objective.