Optimization Of Communication Systems Research Articles

Training of Deep Joint Transmitter-Receiver Optimized Communication System without Auxiliary Tools

Deep Joint transmitter-receiver optimized communication system (Deep JTROCS) is a new physical layer communication system. It integrates the functions of various signal processing blocks into deep neural networks in the transmitter and receiver. Therefore, Deep JTROCS can approach the optimal state at the system level by the joint training of these neural networks. However, due to the non-differentiable feature of the channel, the back-propagation of Deep JTROCS training gradients is hindered which hinders the training of the neural networks in the transmitter. Although researchers have proposed methods to train transmitters using auxiliary tools such as channel models or feedback links, these tools are not available in many real-world communication scenarios, limiting the application of Deep JTROCS. In this paper, we propose a new method to use undertrained Deep JTROCS to transmit the training signals and use these signals to reconstruct the training gradient of the neural networks in the transmitter, thus avoiding the use of an additional reliable link. The experimental results show that the proposed method outperforms the additional link-based approach in different tasks and channels. In addition, experiments conducted on real wireless channels validate the practical feasibility of the method.

Optimal Communication System With Power Control and Ultra-Wideband Propagation Channel Model Designs for Monitoring Harsh Through-Wall Environments

Optimal Communication System With Power Control and Ultra-Wideband Propagation Channel Model Designs for Monitoring Harsh Through-Wall Environments

Adaptive Risk Communication System and Policy for Health Crisis in Indonesia

Three years since its first appearance at the end of 2019, until now, Covid-19 still exists. Realizing that the handling of Covid-19 cannot be carried out alone, the Indonesian government is trying to involve various parties to provide the public with an understanding of the risks. Considering that Covid-19 is still around, efforts to reflect on the risk communication system and the various risk policies adopted are necessary as a preventive action to anticipate various potential risks and health crises in the future. This research is qualitative with a case study type. Data were obtained through in-depth interviews with the Covid-19 handling committee in Indonesia (KPC PEN), observation, and literature study. The results of this study indicate that in building a risk communication system, the government cooperates with various parties. The communication system and risk policies implemented by the Indonesian government are not optimal in understanding risks to the public. Efforts are needed to conduct regular evaluations and monitoring to optimize communication systems and risk policies in anticipation of future health crises.

Modeling and Simulation of SWARA Path Loss Model for Underwater Acoustic Communication in Multipath Environment

Effective communication in underwater environments is essential for numerous applications, including marine research, oil and gas exploration, and underwater surveillance. However, signal loss during propagation is a significant challenge for underwater communication systems. Accurate mathematical models are necessary to develop and optimize communication systems for underwater environments. This research proposes a mathematical model, SWARA, that incorporates crucial parameters such as transmitter and receiver responses, channel conditions, node placements, and signal frequency to accurately model short-range losses in underwater medium. We conducted tank trials at the UWAA Lab, CARE, IIT Delhi to validate our simulation results, using a chirp signal with a frequency ranging from 25–35 kHz. Our simulation results show that the SWARA model effectively predicts short-range propagation losses in underwater media. Compared to experimental losses, the maximum and minimum simulated losses deviated by only − 0.18–0.10 W/Hz and − 0.36–0.19 W/Hz, respectively, indicating the accuracy of the model. Our tank trials further revealed the significant impact of projector and hydrophone placements on incurred losses, highlighting the importance of careful placement in the design of underwater communication systems. In conclusion, this research proposes the SWARA model for studying short-range losses in underwater tank, which effectively incorporates crucial parameters for accurate modeling. The model has practical applications in the design and optimization of underwater communication systems for short-range applications. This research provides important insights for the development of effective underwater communication systems.

Anisotropic plasma sheath turbulence effects on the mode states of Whittaker–Gaussian beams

In this paper detection probability and crosstalk probability variance of the orbital angular momentum states of the diffraction-free Whittaker–Gaussian (WG) beams passing through an anisotropic plasma sheath turbulence (PST) are theoretically formulated. In this regard, using modified von Karman spectrum in the frame of Rytov theory the spiral spectrum of the WG beams is derived, and the role of the anisotropy parameters, refractive index fluctuation variance, initial topological charge, receiving aperture radius, the outer scale of turbulence, beam wavelength and waist in the mitigation of the turbulence-induced disturbance is numerically explored. The remarkable findings indicate that WG beams in anisotropic PST are less influenced than isotropic one, and increasing the anisotropy feature of plasma medium leads to alleviate modulated distortion. Furthermore, it is found out that the propagation performance of WG vortex beams with high-order initial topological charge is significantly better than those with lower order. We expect that our results will be helpful for designing optimal free-space communication systems.

Comparing Interventions With Speech-Generating Devices and Other Augmentative and Alternative Communication Modes: A Meta-Analysis.

Optimal augmentative and alternative communication (AAC) systems for children with complex communication needs depend in part on child characteristics, child preferences, and features of the systems themselves. The purpose of this meta-analysis was to describe and synthesize single case design studies comparing young children's acquisition of communication skills with speech-generating devices (SGDs) and other AAC modes. A systematic search of published and gray literature was conducted. Data related to study details, rigor, participant characteristics, design information, and outcomes were coded for each study. A random effects multilevel meta-analysis was performed using log response ratios as effect sizes. Nineteen single case experimental design studies with 66 participants (M age = 4.9 years) met inclusion criteria. All but one study featured requesting as the primary dependent variable. Visual analysis and meta-analysis indicated no differences between use of SGDs and picture exchange for children learning to request. Children demonstrated preferences for and learned to request more successfully with SGDs than with manual sign. Children who preferred picture exchange also learned to request more easily with picture exchange than with SGDs. Young children with disabilities may be able to request equally well with SGDs and picture exchange systems in structured contexts. More research is needed comparing AAC modes with diverse participants, communication functions, linguistic complexity, and learning contexts. https://doi.org/10.23641/asha.22111181.

Simulation Design of Baseband Optimal Digital Communication System with Non-Ideal Channel

Simulation Design of Baseband Optimal Digital Communication System with Non-Ideal Channel

EVALUATION AND STRATEGY OF TAPPING PINE TREES AS AN ATTEMPT FOR COMMUNITY EMPOWERMENTIN SUMEDANG, WEST JAVA

The increase in economic needs has resulted in increased community pressure on forest area. This encourage the government to open up access to utilize forest, in order to improve the community's economy. Since March 2018, access to utilize forest has been implemented in Masigit Kareumbi Game Reserve (TBMK). However, research related to the evaluation of activities has not been widely found. This study aims to evaluate and determine the optimal pine tapping management strategy in TBMK. The research was conducted in Sukajaya and Citengah Villages, South Sumedang District, using Ostrom Institutional Analysis and Development Framework, Stakeholder Analysis, and the Analysis Hierarchy Process. The result showed that, the potential of pine resin in the research location was 308,377.3 kg/year, which had a positive economic, social, and institutional impact on the community but tended to have a negative impact on the ecological aspects. Stakeholder analysis showed that the parties involved were among others KLHK, BBKSDA West Java, Sukajaya and Citengah Heads Village, Forest Farmer Group (KTH) Sawargi and Medal Kencana, Pinus Merkusii Cooperation, and the Indonesian Conservation Cadre Communication Forum (FK3I). Each stakeholder has a good relationship, however, there is still a need for a more optimal communication and coordination system between one another. The suggested strategy is to increase community assistance by FK3I and Pinus Merkusii Cooperation involvement in limiting the tapping pine resin.

Improving the Frequency Fluctuations Attenuation of Microgrid by Determining Optimal communication System Delay and Virtual Inertia Values

Improving the Frequency Fluctuations Attenuation of Microgrid by Determining Optimal communication System Delay and Virtual Inertia Values

7.4-Gbit/s Visible-Light Communication Utilizing Wavelength-Selective Semipolar Micro-Photodetector

Visible light communication (VLC) has drawn significant attention in recent years. Though high-speed visible-light sources have seen significant advances, commercially available photodetectors have low wavelength selectivity and modulation bandwidth in the near-violet-blue wavelengths, making them a bottleneck in VLC links. Here we show a record 7.4-Gbit/s visible-light communication link using a wavelength-selective, (2021)-oriented, semipolar InGaN/GaN multiple-quantum-well micro-photodetector (μPD) on GaN substrate. This is achieved by leveraging on the unique photodetection properties of semipolar μPDs, combined with an optimized communication system utilizing bit- and power-loading schemes in orthogonal frequency-division multiplexing (OFDM) modulation over a 2-GHz bandwidth. We used a 405-nm violet laser diode transmitter as the responsivity of the μPD was highest within the responsivity range of 360 - 420 nm. The investigation fully demonstrated the feasibility and favorable choice of semipolar InGaN/GaN μPDs for multi-Gbit/s optical wireless communication.

Low-cost communication system for explorer-class underwater remotely operated vehicle

Disaster recovery from underwater earthquake, plane crashes into the sea, and monitoring underwater cables or piping for energy purpose are underwater missions for Remotely Operated Underwater Vehicle (ROV) in ASEAN MATE 2018 Competition. Two essentials factor to perform successfully in this ROV competition are design of an efficient communication protocol system and a low-cost communication hardware. In this research, an optimal communication system between RS-232 serial communication transmission and RS-485 serial communication transmission is developed to obtain the optimal solution. Both communication system is tested in Tech_SAS ROV-Telkom University Indonesia, a microcontroller underwater ROV based which used single microcontroller to control actuator, sensor and communication, and measured the Quality of Services (QoS) for end-to-end delay and packets loss. From the the experiment and evaluation for the two schemes, shows 12.57 ms end-to-end delay, 0% data packet error and $6 RS-485 communication system are the optimal solution for Tech_SAS ROV.

Fractional Programming for Communication Systems—Part II: Uplink Scheduling via Matching

This two-part paper develops novel methodologies for using fractional programming (FP) techniques to design and optimize communication systems. Part I of this paper proposes a new quadratic transform for FP and treats its application for continuous optimization problems. In this Part II of the paper, we study discrete problems, such as those involving user scheduling, which are considerably more difficult to solve. Unlike the continuous problems, discrete or mixed discrete-continuous problems normally cannot be recast as convex problems. In contrast to the common heuristic of relaxing the discrete variables, this work reformulates the original problem in an FP form amenable to distributed combinatorial optimization. The paper illustrates this methodology by tackling the important and challenging problem of uplink coordinated multi-cell user scheduling in wireless cellular systems. Uplink scheduling is more challenging than downlink scheduling, because uplink user scheduling decisions significantly affect the interference pattern in nearby cells. Further, the discrete scheduling variable needs to be optimized jointly with continuous variables such as transmit power levels and beamformers. The main idea of the proposed FP approach is to decouple the interaction among the interfering links, thereby permitting a distributed and joint optimization of the discrete and continuous variables with provable convergence. The paper shows that the well-known weighted minimum mean-square-error (WMMSE) algorithm can also be derived from a particular use of FP; but our proposed FP-based method significantly outperforms WMMSE when discrete user scheduling variables are involved, both in term of run-time efficiency and optimizing results.

Nonlinear Fourier transform for optical data processing and transmission: advances and perspectives

Fiber-optic communication systems are nowadays facing serious challenges due to the fast growing demand on capacity from various new applications and services. It is now well recognized that nonlinear effects limit the spectral efficiency and transmission reach of modern fiber-optic communications. Nonlinearity compensation is therefore widely believed to be of paramount importance for increasing the capacity of future optical networks. Recently, there has been steadily growing interest in the application of a powerful mathematical tool—the nonlinear Fourier transform (NFT)—in the development of fundamentally novel nonlinearity mitigation tools for fiber-optic channels. It has been recognized that, within this paradigm, the nonlinear crosstalk due to the Kerr effect is effectively absent, and fiber nonlinearity due to the Kerr effect can enter as a constructive element rather than a degrading factor. The novelty and the mathematical complexity of the NFT, the versatility of the proposed system designs, and the lack of a unified vision of an optimal NFT-type communication system, however, constitute significant difficulties for communication researchers. In this paper, we therefore survey the existing approaches in a common framework and review the progress in this area with a focus on practical implementation aspects. First, an overview of existing key algorithms for the efficacious computation of the direct and inverse NFT is given, and the issues of accuracy and numerical complexity are elucidated. We then describe different approaches for the utilization of the NFT in practical transmission schemes. After that we discuss the differences, advantages, and challenges of various recently emerged system designs employing the NFT, as well as the spectral efficiency estimates available up-to-date. With many practical implementation aspects still being open, our mini-review is aimed at helping researchers assess the perspectives, understand the bottlenecks, and envision the development paths in the upcoming NFT-based transmission technologies.

Calculation of the Performance of Communication Systems From Measured Oscillator Phase Noise

Oscillator phase noise (PN) is one of the major problems that affect the performance of communication systems. In this paper, a direct connection between oscillator measurements, in terms of measured single-side band PN spectrum, and the optimal communication system performance, in terms of the resulting error vector magnitude (EVM) due to PN, is mathematically derived and analyzed. First, a statistical model of the PN, considering the effect of white and colored noise sources, is derived. Then, we utilize this model to derive the modified Bayesian Cramer-Rao bound on PN estimation, and use it to find an EVM bound for the system performance. Based on our analysis, it is found that the influence from different noise regions strongly depends on the communication bandwidth, i.e., the symbol rate. For high symbol rate communication systems, cumulative PN that appears near carrier is of relatively low importance compared to the white PN far from carrier. Our results also show that 1/f^3 noise is more predictable compared to 1/f^2 noise and in a fair comparison it affects the performance less.

Convergence of fundamental limitations in feedback communication, estimation, and feedback control over Gaussian channels

In this paper, we establish the connections of the fundamental limitations in feedback communication, estimation, and feedback control over Gaussian channels, from a unifying perspective for information, estimation, and control. The optimal feedback communication system over a Gaussian necessarily employs the Kalman filter (KF) algorithm, and hence can be transformed into an estimation system and a feedback control system over the same channel. This follows that the information rate of the communication system is alternatively given by the decay rate of the Cramer-Rao bound (CRB) of the estimation system and by the Bode integral (BI) of the control system. Furthermore, the optimal tradeoff between the channel input power and information rate in feedback communication is alternatively characterized by the optimal tradeoff between the (causal) one-step prediction mean-square error (MSE) and (anti-causal) smoothing MSE (of an appropriate form) in estimation, and by the optimal tradeoff between the regulated output variance with causal feedback and the disturbance rejection measure (BI or degree of anti-causality) in feedback control. All these optimal tradeoffs have an interpretation as the tradeoff between causality and anti-causality. Utilizing and motivated by these relations, we provide several new results regarding the feedback codes and information theoretic characterization of KF. Finally, the extension of the finite-horizon results to infinite horizon is briefly discussed under specific dimension assumptions (the asymptotic feedback capacity problem is left open in this paper).

Coordination of communication in robot teams by reinforcement learning

In multi-agent systems, the study of language and communication is an active field of research. In this paper we present the application of Reinforcement Learning (RL) to the self-emergence of a common lexicon in robot teams. By modeling the vocabulary or lexicon of each agent as an association matrix or look-up table that maps the meanings (i.e. the objects encountered by the robots or the states of the environment itself) into symbols or signals we check whether it is possible for the robot team to converge in an autonomous, decentralized way to a common lexicon by means of RL, so that the communication efficiency of the entire robot team is optimal. We have conducted several experiments aimed at testing whether it is possible to converge with RL to an optimal Saussurean Communication System. We have organized our experiments alongside two main lines: first, we have investigated the effect of the team size centered on teams of moderated size in the order of 5 and 10 individuals, typical of multi-robot systems. Second, and foremost, we have also investigated the effect of the lexicon size on the convergence results. To analyze the convergence of the robot team we have defined the team’s consensus when all the robots (i.e. 100% of the population) share the same association matrix or lexicon. As a general conclusion we have shown that RL allows the convergence to lexicon consensus in a population of autonomous agents.

Coordination of communication in robot teams by reinforcement learning

In multi-agent systems, the study of language and communication is an active field of research. In this paper, we present the application of reinforcement learning (RL) to the self-emergence of a common lexicon in robot teams. By modeling the vocabulary or lexicon of each agent as an association matrix or look-up table that maps the meanings (i.e. the objects encountered by the robots or the states of the environment itself) into symbols or signals, we check whether it is possible for the robot team to converge in an autonomous decentralized way to a common lexicon by means of RL, so that the communication efficiency of the entire robot team is optimal. We conducted several experiments aimed at testing whether it is possible to converge with RL to an optimal Saussurean communication system. We organized our experiments alongside two main lines. First, we investigated the effect of the team size centered on teams of moderate size of the order of 5 and 10 individuals, typical of multi-robot systems. Second, and foremost, we also investigated the effect of the lexicon size on the convergence results. To analyze the convergence of the robot team, we defined the team’s consensus as being when all the robots (i.e. 100% of the population) share the same association matrix or lexicon. As a general conclusion, we show that RL allows convergence to lexicon consensus in a population of autonomous agents.

Self-emergence of a common lexicon by evolution in teams of autonomous agents

In multi-agent systems, the study of language and communication is an active field of research. In this paper we present the application of evolutionary strategies to the self-emergence of a common lexicon in a population of agents. By modeling the vocabulary or lexicon of each agent as an association matrix or look-up table that maps the meanings (i.e. the objects encountered by the agents or the states of the environment itself) into symbols or signals we check whether it is possible for the population to converge in an autonomous, decentralized way to a common lexicon, so that the communication efficiency of the entire population is optimal. We have conducted several experiments aimed at testing whether it is possible to converge with evolutionary strategies to an optimal Saussurean communication system. We have organized our experiments alongside two main lines: first, we have investigated the effect of the population size on the convergence results. Second, and foremost, we have also investigated the effect of the lexicon size on the convergence results. To analyze the convergence of the population of agents we have defined the population's consensus when all the agents (i.e. 100% of the population) share the same association matrix or lexicon. As a general conclusion we have shown that evolutionary strategies are powerful enough optimizers to guarantee the convergence to lexicon consensus in a population of autonomous agents.

Designing for Disaster

Using the London Bombings of 7 July 2005 as a case study, this paper illustrates the need for sociotechnical interventions in systems design. By employing Actor Network Theory the author makes visible the active participants and technologies within the ecosystems of social software. Such visibility provides insight to the designer seeking to optimize communication systems in the wake of disaster. Guidelines for improving systems and user interfaces based on disaster scenarios are described.

Analytical Modeling of a Large Local Area Network - Part I: Internet Traffic Characterization

The goal of both IP network operators and the end users is to get the highest performance from the system for a given cost. This makes Performance a key criterion in the design, procurement, and use of computer and communication systems. In order to address problems associated with performance degradation of operational communicationssystems, over the last decade, traffic engineering techniques have emerged in an attempt to optimize communication systems’ performance and ensure more efficient use of their resources. One of these techniques is analytical modeling. Analytic performance models are an excellent tool for quickly evaluating the performance of operational or new systems. They are also well suited to comparing the performance of several alternative designs. However, analytical models can only be developed once detailed knowledge of characteristics of trafficcarried by a network is available. In Part I of this paper, traffic characterization of traffic carried by the largest Local Area Network (LAN) in Tanzania, University of Dar es Salaam Network (UDSMNET) is carried out. In Part II of this paper, an analytical model based on the Discrete Time Markov Modulated Poisson Process is proposed and validated for performance analysis of IP networks.