Resource Allocation for IRS Assistedmm Wave Wireless Powered Sensor Networks with User Cooperation

In this paper,we investigate IRS-aided user cooperation(UC)scheme in millimeter wave(mmWave)wirelesspowered sensor networks(WPSN),where two single-antenna users are wireless powered in the wireless energy transfer(WET)phase first and then cooperatively transmit information to a hybrid access point(AP)in the wireless information transmission(WIT)phase,following which the IRS is deployed to enhance the system performance of theWET andWIT.We maximized the weighted sum-rate problem by jointly optimizing the transmit time slots,power allocations,and the phase shifts of the IRS.Due to the non-convexity of the original problem,a semidefinite programming relaxation-based approach is proposed to convert the formulated problem to a convex optimization framework,which can obtain the optimal global solution.Simulation results demonstrate that the weighted sum throughput of the proposed UC scheme outperforms the non-UC scheme whether equipped with IRS or not.

Computation Rate Maximization in Multi-User Cooperation-Assisted Wireless-Powered Mobile Edge Computing with OFDMA

In the era of Internet of Things(Io T),mobile edge computing(MEC)and wireless power transfer(WPT)provide a prominent solution for computation-intensive applications to enhance computation capability and achieve sustainable energy supply.A wireless-powered mobile edge computing(WPMEC)system consisting of a hybrid access point(HAP)combined with MEC servers and many users is considered in this paper.In particular,a novel multiuser cooperation scheme based on orthogonal frequency division multiple access(OFDMA)is provided to improve the computation performance,where users can split the computation tasks into various parts for local computing,offloading to corresponding helper,and HAP for remote execution respectively with the aid of helper.Specifically,we aim at maximizing the weighted sum computation rate(WSCR)by optimizing time assignment,computation-task allocation,and transmission power at the same time while keeping energy neutrality in mind.We transform the original non-convex optimization problem to a convex optimization problem and then obtain a semi-closed form expression of the optimal solution by considering the convex optimization techniques.Simulation results demonstrate that the proposed multi-user cooperationassisted WPMEC scheme greatly improves the WSCR of all users than the existing schemes.In addition,OFDMA protocol increases the fairness and decreases delay among the users when compared to TDMA protocol.

Interference-Limited Device-to-Device Multi-User Cooperation Scheme for Optimization of Edge Networking

Device-to-device （D2D） communication is an emerging technology for improving cellular networks, which plays an important role in realizing Internet of Things （IoT）. The spectrum efficiency, energy efficiency and throughput of network can be enhanced by the cooperation among multiple D2D users in a self-organized method. In order to limit the interference of D2D users and load off the energy consumption of D2D users without decreasing communication quality, an interference- limited multi-user cooperation scheme is proposed for multiple D2D users to solve the energy problem and the interference problem in this paper. Multiple D2D users use non-orthogonal spectrums to form clusters by self-organized method. Multiple D2D users are divided into different cooperative units. There is no interference among different cooperative units so as to limit the interference of each D2D user in cooperative units. When the link capacity cannot meet the requirements of the user rate, it will produce an interrupt event. In order to evaluate the communication quality, the outrage probability of D2D link is derived by considering link delay threshold, data rate and interference. Besides the energy availability and signal-to-noise ratio （SNR） of each D2D user, the distance between D2D users is considered when selecting the relaying D2D users so as to enhance the signal-to-interference-plus-noise ratio （SINR） of D2D receiving users. Combining the derived outrage probability, the relationships among the average link delay threshold, the efficiency of energy and the efficiency of capacity are studied. The simulation results show that the interference-limited multiple D2D users cooperation scheme can not only help to offioad energy consumption and limit the interference of D2D users, but also enhance the efficiency of energy and the efficiency of capacity.

Optimal Energy Efficiency Resource Allocation Strategy for Cognitive Clustering Network under PUEA Attack

5G has pushed the use of radio spectrum to a new level,and cognitive clustering network can effectively improve the utilization of radio spectrum,which is a feasible way to solve the growing demand for wireless communications.However,cognitive clustering network is vulnerable to PUEA attack,which will lead to the degradation of system detection performance,thereby reducing the energy efficiency.Aiming at these problems,this paper investigates the optimal energy efficiency resource allocation scheme for cognitive clustering network under PUEA attack.A cooperative user selection algorithm based on selection factor is proposed to effectively resist PUEA user attack and improve detection performance.We construct the energy efficiency optimization problem under multi-constraint conditions and transform the nonlinear programming problem into parametric programming problem,which is solved by Lagrangian function and Karush-Kuhn-Tucker condition.Then the sub-gradient iterative algorithm based on optimal energy efficiency under PUEA attack is proposed and its complexity is analyzed.Simulation results indicate that proposed method is effective when subjected to PUEA attacks,and the impact of different parameters on energy efficiency is analyzed.