Communication Transmission Rate Research Articles

Signal Optimization of Electronic Communication Network Based on Internet of Things

In order to solve the problem that many people communicate at the same time, there are many external interference factors, and the signal is prone to instability in the process of electronic communication, the author proposes a signal optimization method for electronic communication network based on the Internet of Things. The method takes the cloud trust mechanism as the dynamic evolution trust relationship between various Internet of Things electronic communication services, performs explicit and implicit uncertainty conversion, calculates the objective function of data communication network performance, and confirms the control strategy. The positioning information of the network nodes in the communication is added to the communication data packet, and the most stable electronic communication path in the network is obtained to form the network topology structure. The Krasovsky method is adopted, and the working state of the nodes of the communication network is divided into the congested state and the normal state, the probability of the two is calculated, and the range of the transition balance is determined, so as to realize the optimization of the stability of the network topology. Experimental results show that the transmission rate of this method has been maintained at about 180 Kb/s; although there is fluctuation, the fluctuation value is small and the transmission rate is very stable. Conclusion. It can improve the accuracy of electronic communication of the Internet of Things and is less affected by external interference factors, and the communication transmission rate is faster.

UAV Communication Network Modeling and Energy Consumption Optimization Based on Routing Algorithm.

Topological information is provided, and research on the design of routing protocols for UAV self-assembling networks is conducted, in order to enable fleet communication transfer between UAVs and UAVs and enhance their communication transmission rate in the self-assembling network. A new routing protocol is proposed through greedy forwarding and peripheral forwarding of UAV self-assembling network communication data, UAV self-assembling network planarization processing, dynamic adjustment of routing mode based on topological information, and routing protocol decision content generation. The proposed network is described using stochastic geometry theory, with the UAV and building locations modeled as two independently distributed Poisson point processes and the building shape modeled as a rectangular body with height obeying the Rayleigh distribution. An estimated equation for typical user coverage is produced using this model. The simulation results show that the approximate expression matches with the simulation results with reduced computational complexity, which verifies the validity of the approximate analysis. By comparing it with the clustering-based routing protocol, it is concluded that the new routing protocol conditions for UAV self-assembly network can realize the communication transmission between UAVs and drones and further promote their communication transmission rate.

Integrated Waveform Design for Centralized MIMO-OFDM-BPSK-LFM Radar Communication

Because the signal amplitude corresponding to the phase of BPSK modulation is ±1, it’s autocorrelation function is shaped like a mountain peak. The fuzzy function of BPSK-LFM is multiplied by two parts, the left part is the fuzzy function of the standard LFM signal, and the right part is the autocorrelation function of the BPSK communication symbol, which won’t change with the random change of the communication symbol. Therefore, the fuzzy function performance of BPSK-LFM signal is better than that of LFM signal, but the transmission rate of communication is low. The shape of the fuzzy function will change with the change of random communication symbol in QPSK-LFM and 8PSK-LFM modulation. OFDM multi-carrier modulation can improve spectrum efficiency and communication transmission rate. MIMO technology can multiply channel capacity and spectrum efficiency without increasing signal bandwidth B. As a result, the integrated radar communication signal designed in this paper is a centralized MIMO-OFDM-BPSK-LFM signal. The distance between receiving antennas and transmitting antennas is very small in centralized MIMO radars, which is easy to place together.

Efficient Integration of Magnetic Positioning and Stable Communications

A promising integration method for high-precision positioning and stable communications by utilizing magnetic induction signals is proposed. In-phase and quadrature components are assigned to the positioning and communications, respectively. A pilot signal is used for identification of the in-phase and quadrature components, which leads to mutual interference of the two components caused by carrier phase synchronization error. Simulation and experiment confirm that the mutual interference and signal-to-noise ratio (SNR) loss are acceptable in our proposed scheme, i.e., the interference is weak and the SNR loss is about 1.6 dB as the carrier phase synchronization error less than ${5^\circ }$ . For instance, it is demonstrated that the root-mean-square error of positioning is less than 1.5 m and the transmission rate of communications is about 3000 bits per second when the distance is about 150 m, which is practical for applications such as the magnetic navigation, as well as compressed voice and message communications underground or underwater.

To Go or Not to Go: On Energy-Aware and Communication-Aware Robotic Operation

We consider the scenario where a mobile robot needs to visit a number of points of interest (POIs) in a workspace, gathers its generated bits of information, and successfully transmits them to a remote station, while operating in a realistic communication environment, minimizing its total energy consumption (including both motion and communication costs), and under time and reception quality constraints. We are interested in the co-optimization of the communication and motion strategies of the robot such that it finds the optimal trajectory (the order in which it visits all of the POIs) and optimally co-plans its communication and motion strategies, including motion speed, stop times, communication transmission rate, and power. By co-optimizing the usage of both communication and motion energy costs and using realistic probabilistic link metrics that go beyond the commonly used disk models, we show how the overall problem can be posed as a mixed integer linear program (MILP) and characterize several properties of the co-optimized solution. For instance, we derive conditions under which the optimal trajectory becomes the minimum-length trajectory as well as conditions under which the trajectory deviates from the minimum length one to visit areas with very high connectivity. We further characterize if/when it is beneficial for the robot to incur motion energy to find a better spot for communication. Moreover, we derive conditions that relate the co-optimized communication and motion strategies and clearly show the interplay between the two. Finally, our simulation results with real channel and motion parameters confirm the analysis and show considerable energy savings.

SETI: The transmission rate of radio communication and the signal's detection

The transmission rate of communication between radio telescopes on Earth and extraterrestrial intelligence (ETI) is here calculated up to distances of 1000 light years. Both phase-shift keying (PSK) and frequency-shift keying (FSK) modulation schemes are considered. It is shown that M-ary FSK is advantageous in terms of energy. Narrow-band pulses scattered over the spectrum sharing a common drift rate can be the probable signals of ETI. Modern SETI spectrum analyzers are well suited to searching for these types of signals. Such signals can be detected using the Hough transform which is a dedicated tool for detecting patterns in an image. The time–frequency plane representing the power output of the spectrum analyzer during the search for ETI gives an image from which the Hough transform (HT) can detect signal patterns with frequency drift.

A Novel Energy Saving Approach through Mobile Collaborative Computing Systems

Energy saving has been studied widely in both of computing and communication research communities. For handheld devices, energy is becoming a more and more critical issue because lots of applications running on handhelds today are computation or communication intensive and take a long time to finish. Unlike previous work that proposes computing or communication energy solutions alone, this paper proposes a novel energy savings approach through mobile collaborative systems, which jointly consider computing and communication energy cost. In this work, the authors use streaming video as investigated application scenario and propose multi-hop pipelined wireless collaborative system to decode video frames with a requirement for maximum inter-frame time. To finish a computing task with such a requirement, this paper proposes a control policy that can dynamically adapt processor frequency and communication transmission rate at the collaborative devices. The authors build a mathematical energy model for collaborative computing systems. Results show that the collaborative system helps save energy, and the transmission rate between collaborators is a key parameter for maximizing energy savings. The energy saving algorithm in computing devices is implemented and the experimental results show the same trend.