Resource allocation for D2D-assisted haptic communications

Haptic communications is recognized as a promising enabler of extensive services by enabling real-time haptic control and feedback in remote environments,e.g.,teleoperation and autonomous driving.Considering the strict transmission requirements on reliability and latency,Device-to-Device(D2D)communications is introduced to assist haptic communications.In particular,the teleoperators with poor channel quality are assisted by auxiliaries,and each auxiliary and its corresponding teleoperator constitute a D2D pair.However,the haptic interaction and the scarcity of radio resources pose severe challenges to the resource allocation,especially facing the sporadic packet arrivals.First,the contentionbased access scheme is applied to achieve low-latency transmission,where the resource scheduling latency is omitted and users can directly access available resources.In this context,we derive the reliability index of D2D pairs under the contention-based access scheme,i.e.,closed-loop packet error probability.Then,the reliability performance is guaranteed by bidirectional power control,which aims to minimize the sum packet error probability of all D2D pairs.Potential game theory is introduced to solve the problem with low complexity.Accordingly,a distributed power control algorithm based on synchronous log-linear learning is proposed to converge to the optimal Nash Equilibrium.Experimental results demonstrate the superiority of the proposed learning algorithm.

Novel Sum-of-Sinusoids Simulation Channel Modeling for 6G Multiple-Input Multiple-Output Vehicle-to-Everything Communications

In this paper,a statistical cluster-based simulation channel model with a finite number of sinusoids is proposed for depicting the multiple-input multiple-output(MIMO)communications in vehicleto-everything(V2X)environments.In the proposed sum-of-sinusoids(SoS)channel model,the waves that emerge from the transmitter undergo line-of-sight(LoS)and non-line-of-sight(NLoS)propagation to the receiver,which makes the model suitable for describing numerous V2X wireless communication scenarios for sixth-generation(6G).We derive expressions for the real and imaginary parts of the complex channel impulse response(CIR),which characterize the physical propagation characteristics of V2X wireless channels.The statistical properties of the real and imaginary parts of the complex CIRs,i.e.,autocorrelation functions(ACFs),Doppler power spectral densities(PSDs),cross-correlation functions(CCFs),and variances of ACFs and CCFs,are derived and discussed.Simulation results are generated and match those predicted by the underlying theory,demonstrating the accuracy of our derivation and analysis.The proposed framework and underlying theory arise as an efficient tool to investigate the statistical properties of 6G MIMO V2X communication systems.

Anti-Jamming and Anti-Eavesdropping in A2G Communication System with Jittering UAV

This paper focuses on anti-jamming and anti-eavesdropping problem in air-to-ground(A2G)communication networks considering the impact of body jitter of unmanned aerial vehicle(UAV).A full-duplex(FD)active ground eavesdropper launches jamming attack while eavesdropping to stimulate the legitimate transmitter(i.e.,UAV)to increase its transmission power.The legitimate transmitter’s objective is to against the simultaneous wiretapping and jamming with a robust and power-efficient transmission scheme.The active eavesdropper aims to minimize the system secrecy rate.To study the interaction between the legitimate transmitter and the active eavesdropper,a non-cooperative game framework is formulated.Detailed,considering the impact of UAV jitter on antenna array response and secrecy performance,we first investigate the UAV’s transmission power minimization problem for the worst scenario with minimum legitimate data rate and maximum eavesdropping data rate under UAV jitter.Then,the active eavesdropper’s secrecy rate minimization problem with the worst scenario is investigated by optimizing its jamming strategy.Nash equilibrium is proved to be existed and obtained with the proposed iterative algorithm.Finally,extensive numerical results are provided to evaluate the system secrecy performance and to show the secrecy performance gains of the proposed method.

Integrated Sensing and Communication:Who Benefits More?

This paper compares the benefits of communication-assisted sensing and sensing-assisted communication in the context of integrated sensing and communication(ISAC).Communication-assisted sensing leverages the extensive cellular infrastructure to create a vast and cooperative sensor network,enhancing environmental perception accuracy and coverage.On the other hand,sensing-assisted communication utilizes advanced sensing technologies to improve predictive beamforming and channel estimation performance in high-frequency and highmobility scenarios,thereby increasing communication efficiency and reliability.To validate our analysis,we present an example of channel knowledge map(CKM)-assisted beam tracking.This example demonstrates the practical advantages of incorporating CKM in enhancing beam tracking accuracy.Our analysis confirms that communication-assisted sensing may offer greater development potential due to its wide coverage and cost-effectiveness in large-scale applications.

Cognitive J^(2)SAC:Joint Jamming,Sensing,and Communication Under Antagonistic Environment

Integrated sensing and communication(ISAC)is regarded as a recent advanced technology,which is expected to realize the dual functions of sensing and communication simultaneously in one system.Nevertheless,it still faces the challenges of the information security and transmission robustness caused by the openness of wireless channel,especially under antagonistic environment.Hence,this article develops a generalized framework,named cognitive joint jamming,sensing and communication(cognitive J2SAC),to empower the current sensing/communication/jamming system with a“brain”for realizing precise sensing,reliable communication and effective jamming under antagonistic environment.Three kinds of gains can be captured by cognitive J2SAC,including integrated gain,cooperative gain and cognitive gain.Moreover,we highlight the enabling mechanism among jamming,sensing,and communication,as well as illustrating several typical use cases of cognitive J2SAC.Furthermore,several key enabled technologies are analyzed and a typical sensing enhance integrated communication and jamming case study is discussed to verify the effectiveness of the proposed method.Last but not the least,the future directions are listed before concluding this article.Integrated sensing and communication(ISAC)is regarded as a recent advanced technology,which is expected to realize the dual functions of sensing and communication simultaneously in one system.Nevertheless,it still faces the challenges of the information security and transmission robustness caused by the openness of wireless channel,especially under antagonistic environment.Hence,this article develops a generalized framework,named cognitive joint jamming,sensing and communication(cognitive J2SAC),to empower the current sensing/communication/jamming system with a“brain”for realizing precise sensing,reliable communication and effective jamming under antagonistic environment.Three kinds of gains can be captured by cognitive J2SAC,including integrated gain,cooperative gain and cognitive gain.Moreover,we highlight the enabling mechanism among jamming,sensing,and communication,as well as illustrating several typical use cases of cognitive J2SAC.Furthermore,several key enabled technologies are analyzed and a typical sensing enhance integrated communication and jamming case study is discussed to verify the effectiveness of the proposed method.Last but not the least,the future directions are listed before concluding this article.

An Optimal Algorithm for Resource Allocation in D2D Communication

The number of mobile devices accessing wireless networks isskyrocketing due to the rapid advancement of sensors and wireless communicationtechnology. In the upcoming years, it is anticipated that mobile datatraffic would rise even more. The development of a new cellular networkparadigm is being driven by the Internet of Things, smart homes, and moresophisticated applications with greater data rates and latency requirements.Resources are being used up quickly due to the steady growth of smartphonedevices andmultimedia apps. Computation offloading to either several distantclouds or close mobile devices has consistently improved the performance ofmobile devices. The computation latency can also be decreased by offloadingcomputing duties to edge servers with a specific level of computing power.Device-to-device (D2D) collaboration can assist in processing small-scaleactivities that are time-sensitive in order to further reduce task delays. The taskoffloading performance is drastically reduced due to the variation of differentperformance capabilities of edge nodes. Therefore, this paper addressed thisproblem and proposed a new method for D2D communication. In thismethod, the time delay is reduced by enabling the edge nodes to exchangedata samples. Simulation results show that the proposed algorithm has betterperformance than traditional algorithm.

Performance Analysis in SWIPT-Based Bidirectional D2D Communications in Cellular Networks

In this paper,a novel traffic-aware cooperative cognitive radio network that can enable deviceto-device(D2D)communications in cellular system is proposed and investigated.By providing relay cooperation to cellular transmission,D2D users can realize their own two-way communication in the licensed spectrum.Unlike most existing works,in the proposed network,both wireless-powered D2D users can harvest energy via radio-frequency signals received from basic station(BS)through a hybrid protocol which can adaptively utilize both time-switching and powersplitting techniques.Specifically,D2D users perform decode-and-forward operation to transmit signals,and mobile user(MU)employs a selection combining technique.In addition,the performance of both D2D system and cellular system in the proposed network is evaluated by deriving the expressions of their exact outage probability and throughput.Numerical and simulation results validate correctness of derivations and reveal the influence of various system parameters of the proposed network.

Coalitional game based resource allocation in D2D-enabled V2V communication

The joint resource block(RB)allocation and power optimization problem is studied to maximize the sum-rate of the vehicle-to-vehicle(V2V)links in the device-to-device(D2D)-enabled V2V communication system,where one feasible cellular user(FCU)can share its RB with multiple V2V pairs.The problem is first formulated as a nonconvex mixed-integer nonlinear programming(MINLP)problem with constraint of the maximum interference power in the FCU links.Using the game theory,two coalition formation algorithms are proposed to accomplish V2V link partitioning and FCU selection,where the transferable utility functions are introduced to minimize the interference among the V2V links and the FCU links for the optimal RB allocation.The successive convex approximation(SCA)is used to transform the original problem into a convex one and the Lagrangian dual method is further applied to obtain the optimal transmit power of the V2V links.Finally,numerical results demonstrate the efficiency of the proposed resource allocation algorithm in terms of the system sum-rate.

MPC-based time synchronizationmethod for V2V (vehicle-tovehicle)communication

Purpose–As the strategy of 5G new infrastructure is deployed and advanced,5G-R becomes the primary technical system for future mobile communication of China’s railway.V2V communication is also an important application scenario of 5G communication systems on high-speed railways,so time synchronization between vehicles is critical for train control systems to be real-time and safe.How to improve the time synchronization performance in V2V communication is crucial to ensure the operational safety and efficiency of high-speed railways.Design/methodology/approach–This paper proposed a time synchronization method based on model predictive control(MPC)for V2V communication.Firstly,a synchronous clock for V2V communication was modeled based on the fifth generation mobile communication-railway(5G-R)system.Secondly,an observation equation was introduced according to the phase and frequency offsets between synchronous clocks of two adjacent vehicles to construct an MPC-based space model of clock states of the adjacent vehicles.Finally,the optimal clock offset was solved through multistep prediction,rolling optimization and other control methods,and time synchronization in different V2V communication scenarios based on the 5G-R system was realized through negative feedback correction.Findings–The results of simulation tests conducted with and without a repeater,respectively,show that the proposed method can realize time synchronization of V2V communication in both scenarios.Compared with other methods,the proposed method has faster convergence speed and higher synchronization precision regardless of whether there is a repeater or not.Originality/value–This paper proposed an MPC-based time synchronization method for V2V communication under 5G-R.Through the construction of MPC controllers for clocks of adjacent vehicles,time synchronization was realized for V2V communication under 5G-R by using control means such as multistep prediction,rolling optimization,and feedback correction.In view of the problems of low synchronization precision and slow convergence speed caused by packet loss with existing synchronization methods,the observer equation was introduced to estimate the clock state of the adjacent vehicles in case of packet loss,which reduces the impact of clock error caused by packet loss in the synchronization process and improves the synchronization precision of V2V communication.The research results provide some theoretical references for V2V synchronous wireless communication under 5G-R technology.

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 Efficient Power Allocation for Relay-Aided D2D Communications in 5G Networks

As one of the key technologies for the fifth generation(5G) wireless networks,device-to-device(D2D) communications allow user equipment(UE) in close proximity to communicate with each other directly.Forwarded by a relay,the relay-aided D2D(RA-D2D) communications can not only be applied to communications in much longer distance but also achieve a high quality of service(Qo S) .In this paper,we first propose a two-layer system model allowing RA-D2 D links to underlay traditional cellular uplinks.Then we maximize the energy efficiency of the RA-D2 D link while satisfying the minimum data-rate of the cellular link.The optimal transmit power at both D2 D transmitter and D2 D relay sides is obtained by transforming the nonlinear fractional programming into a nonlinear parameter programming.Simulation results show that our proposed power allocation method is more energy efficient than the existing works,and the proposed RA-D2 D scheme outperformed direct D2 D scheme when the distance between two D2 D users is longer.

DQN-based decentralized multi-agent JSAP resource allocation for UAV swarm communication

It is essential to maximize capacity while satisfying the transmission time delay of unmanned aerial vehicle(UAV)swarm communication system.In order to address this challenge,a dynamic decentralized optimization mechanism is presented for the realization of joint spectrum and power(JSAP)resource allocation based on deep Q-learning networks(DQNs).Each UAV to UAV(U2U)link is regarded as an agent that is capable of identifying the optimal spectrum and power to communicate with one another.The convolutional neural network,target network,and experience replay are adopted while training.The findings of the simulation indicate that the proposed method has the potential to improve both communication capacity and probability of successful data transmission when compared with random centralized assignment and multichannel access methods.

Joint Power Allocation and Mode Selection for D2D Communications with Imperfect CSI

Device-to-device(D2D) communications can be underlaid with a cellular infrastructure to increase resource utilization, improve user throughput and save battery energy. In such networks, power allocation and mode selection are crucial problems. To address the joint optimization of power and mode selection under imperfect CSI, we propose an optimal, energy-aware joint power allocation and mode selection(JPAMS) scheme. First, we derive the closed-form solution for the power minimization for both D2 D and cellular links while satisfying different quality of service(Qo S) constraints. Second, we address the mode selection problem in presence of imperfect CSI, based on the derived power allocation. Moreover, the theoretical analysis and simulation results are presented to evaluate the proposed scheme for the D2 D communications.

V2X-Communication Assisted Interference Minimization for Automotive Radars

With the development of automated driving vehicles, more and more vehicles will be fitted with more than one automotive radars, and the radar mutual interference will become very significant. Vehicle to everything (V2X) communication is a potential way for coordinating automotive radars and reduce the mutual interference. In this paper, we analyze the positional relation of the two radars that interfere with each other, and evaluate the mutual interference for different types of automotive radars based on Poisson point process (PPP). We also propose a centralized framework and the corresponding algorithm, which relies on V2X communication systems to allocate the spectrum resources for automotive radars to minimize the interference. The minimum spectrum resources required for zero-interference are analyzed for different cases. Simulation results validate the analysis and show that the proposed framework can achieve near-zero-interference with the minimum spectrum resources.

Performance for Device-to-Device Communication with Three-Time-Slot Two-Way Amplify-and-Forward Relay Protocol

Multi-hop device-to-device(D2D) communication can significantly improve the system performance. This paper studied the outage performance of D2 D communication assisted by another D2 D user using three-timeslot two-way amplify-and-forward relaying protocol over Rayleigh fading channels. Considering the co-channel interference from cellular user at the D2 D node,the approximate expression for the overall outage probability was derived. Furthermore,a power allocation optimum method to minimize the outage probability was developed,and the closed form expression for the optimal power allocation coefficient at the relay was derived. Simulation results demonstrate accuracy of the derived outage probability expressions. Simulation results also demonstrate that the outage performance can be improved using the proposed optimal power allocation method.

Secure Beamforming Design for SWIPT in Cooperative D2D Communications

In device-to-device(D2D) communications, device terminal relaying makes it possible for devices in a network to function as transmission relays for each other to enhance the spectral efficiency. In this paper we consider a cooperative D2D communication system with simultaneous wireless information and power transfer(SWIPT). The cooperative D2D communication scheme allows two nearby devices to communicate with each other in the licensed cellular bandwidth by assigning D2D transmitters as half-duplex(HD) relay to assists cellular downlink transmissions. In particular, we focus on secure information transmission for the cellular users when the idle D2D users are the potential eavesdroppers. We aim to design secure beamforming schemes to maximize the D2D users data rate while guaranteeing the secrecy rate requirements of the cellular users and the minimum required amounts of power transferred to the idle D2D users. To solve this non-convex problem, a semi-definite programming relaxation(SDR) approach is adopted to obtain the optimal solution. Furthermore, we propose two suboptimal secure beamforming schemes with low computational complexity for providing secure communication and efficient energy transfer. Simulation results demonstrate the superiority of our proposed scheme.

Ergodic Rate Analysis on Applying Antenna Selection in D2D Communication Underlaying Cellular Networks

By reusing the spectrum of a cellular network, device-to-device(D2D) communications is known to greatly improve the spectral efficiency bypassing the base station(BS) of the cellular network. Antenna selection is the most cost efficient scheme for interference management, which is crucial to D2D systems. This paper investigates the achievable rate performance of the D2D communication underlaying the cellular network where a multiple-antenna base station with antenna selection scheme is deployed. We derive an exact closed-form expression of the ergodic achievable rate. Also, using Jensen's inequality, two pairs of upper and lower bounds of the rate are derived and we validate the tightness of the two sets of bounds. Based on the bounds obtained, we analyze the ergodic achievable rate in noise-limited scenario, interference-limited high SNR scenario and larger-scale antenna systems. Our analysis shows that the presence of D2D users could be counter-productive if the SNR at cellular UE is high. Further analysis shows that the relationship between the ergodic rate and the number of antennas it positive, but keeps decreasing as the antenna number increasing. These show the inefficiency of antenna selection in D2D interference management.

A Joint Power and Bandwidth Allocation Method Based on Deep Reinforcement Learning for V2V Communications in 5G

Vehicular communications have recently attracted great interest due to their potential to improve the intelligence of the transportation system.When maintaining the high reliability and low latency in the vehicle-to-vehicle(V2V)links as well as large capacity in the vehicle-to-infrastructure(V2I)links,it is essential to flexibility allocate the radio resource to satisfy the different requirements in the V2V communication.This paper proposes a new radio resources allocation system for V2V communications based on the proximal strategy optimization method.In this radio resources allocation framework,a vehicle or V2V link that is designed as an agent.And through interacting with the environment,it can learn the optimal policy based on the strategy gradient and make the decision to select the optimal sub-band and the transmitted power level.Because the proposed method can output continuous actions and multi-dimensional actions,it greatly reduces the implementation complexity of large-scale communication scenarios.The simulation results indicate that the allocation method proposed in this paper can meet the latency constraints and the requested capacity of V2V links under the premise of minimizing the interference to vehicle-to-infrastructure communications.

Admission control based on beamforming and interference alignment for D2D communication underlaying cellular networks

An admission control algorithm based on beamforming and interference alignment for device-to-device( D2D) communication underlaying cellular networks is proposed. First, some portion of D2D pairs that are the farthest away from the base station( BS) is selected to perform joint zero-forcing beamforming together with the cellular user equipments( UEs) and is admitted to the cellular network. The interference of the BS transmitting signal to the cellular UEs and the portion of D2D pair is eliminated completely at the same time. Secondly,based on the idea of interference alignment,the definition of channel parallelism is given. The channel parallelism of the remaining D2D pairs which are not involved in joint zero-forcing beamforming is computed by using the channel state information from the BS to the D2D devices. The higher the channel parallelism,the less interference the D2D pair suffers from the BS. Finally,in a descending order of channel parallelism,the remaining D2D pairs are reviewed in succession to determine admission to the cellular network. The algorithm stops when the admission of a D2D pair decreases the system sum rate. Simulation results show that the proposed algorithm can effectively reduce the interference of the BS transmitting signal for D2D pairs and significantly improve system capacity. Furthermore, D2D communication is more applicable to short-range links.

Research on a Secure Communication Protocol Based on National Secret SM2 Algorithm

Most of the public key algorithms used in the exchange of information for power data transmission protocols are RSA. The core of the key part of this kind of algorithm system has not been announced. For the domestic sensitive information data field, there are threats such as preset backdoors and security vulnerabilities. In response to the above problems, the article introduces a secure communication protocol based on the optimized Secret SM2 algorithm, which uses socket programming to achieve two-way encrypted communication between clients and services, and is able to complete the security protection of data encryption transmission, authentication, data tampering, etc., and proves through experiments that the security protocol is more secure than traditional methods, can effectively identify each other, carry out stable and controllable data encryption transmission, and has good applicability.