Joint Optimization of Resource Allocation and Trajectory Based on User Trajectory for UAV-Assisted Backscatter Communication System

The Backscatter communication has gained widespread attention from academia and industry in recent years. In this paper, A method of resource allocation and trajectory optimization is proposed for UAV-assisted backscatter communication based on user trajectory. This paper will establish an optimization problem of jointly optimizing the UAV trajectories, UAV transmission power and BD scheduling based on the large-scale channel state signals estimated in advance of the known user trajectories, taking into account the constraints of BD data and working energy consumption, to maximize the energy efficiency of the system. The problem is a non-convex optimization problem in fractional form, and there is nonlinear coupling between optimization variables.An iterative algorithm is proposed based on Dinkelbach algorithm, block coordinate descent method and continuous convex optimization technology. First, the objective function is converted into a non-fractional programming problem based on Dinkelbach method,and then the block coordinate descent method is used to decompose the original complex problem into three independent sub-problems. Finally, the successive convex approximation method is used to solve the trajectory optimization sub-problem. The simulation results show that the proposed scheme and algorithm have obvious energy efficiency gains compared with the comparison scheme.

Coati Optimization-Based Energy Efficient Routing Protocol for Unmanned Aerial Vehicle Communication

With the flexible deployment and high mobility of Unmanned Aerial Vehicles(UAVs)in an open environment,they have generated con-siderable attention in military and civil applications intending to enable ubiquitous connectivity and foster agile communications.The difficulty stems from features other than mobile ad-hoc network(MANET),namely aerial mobility in three-dimensional space and often changing topology.In the UAV network,a single node serves as a forwarding,transmitting,and receiving node at the same time.Typically,the communication path is multi-hop,and routing significantly affects the network’s performance.A lot of effort should be invested in performance analysis for selecting the optimum routing system.With this motivation,this study modelled a new Coati Optimization Algorithm-based Energy-Efficient Routing Process for Unmanned Aerial Vehicle Communication(COAER-UAVC)technique.The presented COAER-UAVC technique establishes effective routes for communication between the UAVs.It is primarily based on the coati characteristics in nature:if attacking and hunting iguanas and escaping from predators.Besides,the presented COAER-UAVC technique concentrates on the design of fitness functions to minimize energy utilization and communication delay.A varied group of simulations was performed to depict the optimum performance of the COAER-UAVC system.The experimental results verified that the COAER-UAVC technique had assured improved performance over other approaches.

Energy Efficiency and Spectrum Efficiency in Underlay Device-to-Device Communications Enabled Cellular Networks

In this paper, we investigate the energy efficiency and spectrum efficiency, including one-hop device-to-device(D2D) communications mode and two-way amplify-and-forward(AF) relaying D2D communications mode in underlay D2D communications enabled cellular networks. An analysis of average energy efficiency and spectrum efficiency are developed and closed-form expressions are obtained for two types of D2D communications modes under the effect of Rayleigh fading channel, path loss, and co-channel interference. Analytical results are validated through numerical simulations. Based on the simulation, the effects of the interference, the distance between D2D pair and the position of relay node on the energy efficiency and spectrum efficiency of D2D communications are investigated. The optimal D2D transmission powers of these two modes to maximize the energy efficiency are also investigated.

Energy efficiency maximization for buffer-aided multi-UAV relaying communications

This paper studies a multiple unmanned aerial vehicle(UAV)relaying communication system,where multiple UAV re-lays assist the blocked communication between a group of ground users(GUs)and a base station(BS).Since the UAVs only have limited-energy in practice,our design aims to maximize the energy efficiency(EE)through jointly designing the communica-tion scheduling,the transmit power allocation,as well as UAV trajectory under the buffer constraint over a given flight period.Actually,the formulated fractional optimization problem is diffi-cult to be solved in general because of non-convexity.To re-solve this difficulty,an efficient iterative algorithm is proposed based on the block coordinate descent(BCD)and successive convex approximation(SCA)techniques,as well as the Dinkel-bach’s algorithm.Specifically,the optimization variables of the formulated problem are divided into three blocks and we alter-nately optimize each block of the variables over iteration.Numeri-cal results verify the convergence of the proposed iterative al-gorithm and show that the proposed designs achieve significant EE gain,which outperform other benchmark schemes.

Energy efficiency optimization of relay-assisted D2D two-way communications with SWIPT

Aiming at the energy consumption of long-distance device-to-device(D2D) devices for two-way communications in a cellular network,this paper proposes a strategy that combines two-way relay technology(TWRT) and simultaneous wireless information and power transfer(SWIPT) technology to achieve high energy efficiency(EE) communication.The scheme first establishes a fractional programming problem to maximize EE of D2D,and transforms it into a non-fractional optimization problem that can be solved easily.Then the problem is divided into three sub-problems:power control,power splitting ratios optimization,and relay selection.In order to maximize EE of the D2D pair,the Dinkelbach iterative algorithm is used to optimize the transmitted power of two D2D devices simultaneously;the one-dimensional search algorithm is proposed to optimize power splitting ratios;an improved optimal relay selection scheme based on EE is proposed to select relay.Finally,experiments are carried out on the Matlab simulation platform.The simulation results show that the proposed algorithm has faster convergence.Compared with the one-way relay transmission and fixed relay algorithms,the proposed scheme has higher EE.

Energy Efficiency in ARQ-Based Multi-Hop Systems and the Tradeoff with Throughput

The minimum energy per bit(EPB)as the energy efficiency(EE)metric in an automatic retransmission request(ARQ)based multi-hop system is analyzed under power and throughput constraints.Two ARQ protocols including type-I(ARQ-I)and repetition redundancy(ARQ-RR)are considered and expressions for the optimal power allocation(PA)are obtained.Using the obtained optimal powers,the EE-throughput tradeoff(EETT)is analyzed and the EETT closed-form expressions for both ARQ protocols and in arbitrary average channel gain values are obtained.It is shown that how different throughput requirements,especially the high levels,affect the EE performance.Additionally,asymptotic analysis is made in the feasible high throughput values and lower and upper EETT bounds are derived for ARQ-I protocol.To evaluate the EE a distributed PA scenario,as a benchmark,is presented and the energy savinggain obtained from the optimal PA in comparison with the distributed PA for ARQ-I and ARQ-RR protocols is discussed in different throughput values and node locations.

Communication-Efficient Edge AI Inference over Wireless Networks

Given the fast growth of intelligent devices, it is expected that a large number of high-stakes artificial intelligence (AI) applications, e. g., drones, autonomous cars, and tac?tile robots, will be deployed at the edge of wireless networks in the near future. Therefore, the intelligent communication networks will be designed to leverage advanced wireless tech?niques and edge computing technologies to support AI-enabled applications at various end devices with limited communication, computation, hardware and energy resources. In this article, we present the principles of efficient deployment of model inference at network edge to provide low-latency and energy-efficient AI services. This includes the wireless distribut?ed computing framework for low-latency device distributed model inference as well as the wireless cooperative transmission strategy for energy-efficient edge cooperative model infer?ence. The communication efficiency of edge inference systems is further improved by build?ing up a smart radio propagation environment via intelligent reflecting surface.

Efficient Three-Party Quantum Secure Direct Communication with EPR Pairs

In order to get rid of the drawback of information leakage which existed in Chong et al.’s protocol (Opt. Commun., 284, 2011, 515-518), an efficient three-party quantum secure direct communication (3P-QSDC) based on some ideas of quantum dense coding with EPR pairs is proposed, in which each entangled pair can be used to exchange a longer length of secret message between three legal users. By improving the classical channels and the qubit transmissions, our scheme can avoid this kind of drawback. Thus the secret messages are not leaked out to other people from the public information. Moreover, compared with Chong et al.’s protocol, our protocol can achieve higher efficiency.

Wearable Antenna for Power Efficient On-Body and Off-Body Communications

A novel dual-band and diverse radiation pattern antenna is proposed for power efficient on-body and off-body communications intended for various applications in healthcare and sport monitoring. The antenna is dual band at 2.45 GHz (ISM band) with omnidirectional radiation pattern over the body surface to communicate power efficiently with other co-located body worn devices and at 1.9 GHz (PCS band), it has directive radiation pattern towards off the body to communicate from on-body device to off-body devices. The free space and on-body performances of the antenna are investigated by both simulation and experiment. The antenna shows very good on-body radiation efficiency of 58% at 2.45 GHz and 61% at 1.9 GHz. Good on-body gain is noticed at both frequency bands. Results show that the gain of the proposed antenna increases by 4.7% at 2.45 GHz and 3.2% at 1.9 GHz when placed on the body.

MSRA-Fed:A Communication-Efficient Federated Learning Method Based on Model Split and Representation Aggregate

Recent years have witnessed a spurt of progress in federated learning,which can coordinate multi-participation model training while protecting the data privacy of participants.However,low communication efficiency is a bottleneck when deploying federated learning to edge computing and IoT devices due to the need to transmit a huge number of parameters during co-training.In this paper,we verify that the outputs of the last hidden layer can record the characteristics of training data.Accordingly,we propose a communication-efficient strategy based on model split and representation aggregate.Specifically,we make the client upload the outputs of the last hidden layer instead of all model parameters when participating in the aggregation,and the server distributes gradients according to the global information to revise local models.Empirical evidence from experiments verifies that our method can complete training by uploading less than one-tenth of model parameters,while preserving the usability of the model.

Ways to Enhance the Efficiency of International Communication

Ethnocentrism exists in all cultures and everyone is ethnocentric to some extent. People always tend to hold a stand on the side of their own cultural beliefs, values and manners to judge what is correct and what is wrong with regard to the cultures and traditions of other countries. Some feasible ways are given in this paper to adjust ethnocentric tendency in people's minds in the future intercultural communication.

Optimal Deep Learning Enabled Communication System for Unmanned Aerial Vehicles

Recently,unmanned aerial vehicles(UAV)or drones are widely employed for several application areas such as surveillance,disaster management,etc.Since UAVs are limited to energy,efficient coordination between them becomes essential to optimally utilize the resources and effective communication among them and base station(BS).Therefore,clustering can be employed as an effective way of accomplishing smart communication systems among multiple UAVs.In this aspect,this paper presents a group teaching optimization algorithm with deep learning enabled smart communication system(GTOADL-SCS)technique for UAV networks.The proposed GTOADL-SCS model encompasses a two stage process namely clustering and classification.At the initial stage,the GTOADL-SCS model includes a GTOA based clustering scheme to elect cluster heads(CHs)and organize clusters.Besides,the GTOADL-SCS model develops a fitness function containing three input parameters as residual energy of UAVs,average neighoring distance,and UAV degree.For classification process,the GTOADLSCS model applies pre-trained densely connected network(DenseNet201)feature extractor with gated recurrent unit(GRU)classifier.For ensuring the enhanced performance of the GTOADL-SCS model,a widespread simulation analysis is performed and the comparative study reported the significant outcomes over the existing approaches with maximum packet delivery ratio(PDR)of 92.60%.

Using irrigation intervals to optimize water-use efficiency and maize yield in Xinjiang,northwest China

Worldwide, scarce water resources and substantial food demands require efficient water use and high yield.This study investigated whether irrigation frequency can be used to adjust soil moisture to increase grain yield and water use efficiency(WUE) of high-yield maize under conditions of mulching and drip irrigation.A field experiment was conducted using three irrigation intervals in 2016: 6, 9, and 12 days(labeled D6, D9, and D12) and five irrigation intervals in 2017: 3, 6, 9, 12, and 15 days(D3, D6, D9, D12, and D15).In Xinjiang, an optimal irrigation quota is 540 mm for high-yield maize.The D3, D6, D9, D12, and D15 irrigation intervals gave grain yields of 19.7, 19.1–21.0, 18.8–20.0, 18.2–19.2, and 17.2 Mg ha^-1 and a WUE of 2.48, 2.53–2.80, 2.47–2.63, 2.34–2.45, and 2.08 kg m-3, respectively.Treatment D6 led to the highest soil water storage, but evapotranspiration and soil-water evaporation were lower than other treatments.These results show that irrigation interval D6 can help maintain a favorable soil-moisture environment in the upper-60-cm soil layer, reduce soilwater evaporation and evapotranspiration, and produce the highest yield and WUE.In this arid region and in other regions with similar soil and climate conditions, a similar irrigation interval would thus be beneficial for adjusting soil moisture to increase maize yield and WUE under conditions of mulching and drip irrigation.

Green5G: Enhancing Capacity and Coverage in Device-to-Device Communication

With the popularity of green computing and the huge usage of networks,there is an acute need for expansion of the 5G network.5G is used where energy efficiency is the highest priority,and it can play a pinnacle role in helping every industry to hit sustainability.While in the 5G network,conventional performance guides,such as network capacity and coverage are still major issues and need improvements.Device to Device communication(D2D)communication technology plays an important role to improve the capacity and coverage of 5G technology using different techniques.The issue of energy utilization in the IoT based system is a significant exploration center.Energy optimizationin D2D communication is an important point.We need to resolve this issue for increasing system performance.Green IoT speaks to the issue of lessening energy utilization of IoT gadgets which accomplishes a supportable climate for IoT systems.In this paper,we improve the capacity and coverage of 5G technology using Multiple Inputs Multiple Outputs(MU-MIMO).MUMIMO increases the capacity of 5G in D2D communication.We also present all the problems faced by 5G technology and proposed architecture to enhance system performance.

Communication efficiency optimization of federated learning for computing and network convergence of 6G networks

Federated learning effectively addresses issues such as data privacy by collaborating across participating devices to train global models.However,factors such as network topology and computing power of devices can affect its training or communication process in complex network environments.Computing and network convergence(CNC)of sixth-generation(6G)networks,a new network architecture and paradigm with computing-measurable,perceptible,distributable,dispatchable,and manageable capabilities,can effectively support federated learning training and improve its communication efficiency.By guiding the participating devices'training in federated learning based on business requirements,resource load,network conditions,and computing power of devices,CNC can reach this goal.In this paper,to improve the communication eficiency of federated learning in complex networks,we study the communication eficiency optimization methods of federated learning for CNC of 6G networks that give decisions on the training process for different network conditions and computing power of participating devices.The simulations address two architectures that exist for devices in federated learning and arrange devices to participate in training based on arithmetic power while achieving optimization of communication efficiency in the process of transferring model parameters.The results show that the methods we proposed can cope well with complex network situations,effectively balance the delay distribution of participating devices for local training,improve the communication eficiency during the transfer of model parameters,and improve the resource utilization in the network.

LLR-AWARE SMART LINK-ADAPTIVE STRATEGY FOR DECODE-AND-FORWARD COOPERATIVE COMMUNICATION

Error propagation seriously degenerate the diversity order of Decode-and-Forward (DF) cooperative communication. To address this problem, a novel Log Likelihood Ratio (LLR)-based Link Adaptive Relaying (LAR) is proposed to promote adaption accuracy at relay. The instantaneous Bit Error Probability (BEP) is calculated according to the LLR of the received signals firstly, then based on it, the equivalent Signal-to-Noise Ratio (SNR) is employed to operate dynamic power scaling by relay. It is theoretically proved that the full diversity order can be attained by the scheme. Besides, the power sensitivity is also analyzed. Simulation results show that the proposed scheme outperform the conventional LAR and can achieve full diversity order. Moreover, its strong adaptation to SNR fluctuation is validated.

Exploiting Geometric Advantages of Cooperative Communications for Energy Efficient Wireless Sensor Networks

Energy efficiency and enhanced backbone capacity is obtained by exploiting the geometric orientation of cooperative nodes in wireless sensor network. The cooperative communication in wireless sensor networks (WSN) gives us leverage to get the inherent advantages of its random node’s locations and the direction of the data flow. Depending on the channel conditions and the transmission distance, the number of cooperative nodes is selected, that participate in an energy efficient transmission/reception. Simulation results show that increasing the cooperative receive diversity, decreases the energy consumption per bit in cooperative communications. It has also been shown that the network backbone capacity can be increased by controlled displacement of antennas at base station at the expense of energy per bit.