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To solve the problems of energy limitation, spectrum shortage, and serious co-frequency interference in the unmanned aerial vehicle (UAV)-assisted D2D (device-to-device) communication network under passive eavesdropping, the concept of the network secrecy energy efficiency was introduced by taking into account the secrecy rate and transmit power constraints of each user. Based on the physical layer secure transmission theory, the joint optimization problem of spectrum multiplexing and power control strategies was investigated to maximize the network secrecy energy efficiency. The problem was a nonlinear nonconvex problem, a resource allocation algorithm combining Dinkelbach's algorithm and the convex approximation algorithm was proposed to transform the nonconvex optimization problem into a geometric planning problem through the convex approximation algorithm and ensure that the original problem converges to the global optimal solution by Dinkelbach's algorithm. Simulation results show that the proposed algorithm can effectively mitigate the co-channel interference, improve the network secrecy energy efficiency, and balance the relationship between the secure communication performance and power consumption of the network. [ABSTRACT FROM AUTHOR]

In MEC combining IRS and resource allocation strategies to improve system energy efficiency is a current hot topic of research at home and abroad. This paper aimed to maximize energy efficiency in IRS-assisted MEC system through joint optimization of the computing frequency at users, transmit power and time, and the IRS discrete phase-shift based on the transmission mode of hybrid non-orthogonal multiple access. Since the optimization process involved non-convex fractional programming problems that are difficult to solve, this paper proposed a Dinkelbach-SCA algorithm with two iterative-steps. Firstly, this paper converted the initial problem into a tractable form via Dinkelbach' s method, optimization of IRS discrete phase shift by separating variables. Then, by introducing auxiliary variables, and leveraging successive convex approximation, the paper decoupled the relationship between transmit power and time while converted the non-convex problem to a convex one. Hence, the paper could obtain optimal solution. The simulation results show that the energy efficiency of the proposed system scheme is better than other comparison ones, and the energy efficiency of the system increases with the decrease of the minimum computational data amount of user 2. [ABSTRACT FROM AUTHOR]

This paper proposed a power and bandwidth allocation algorithm that maximized energy efficiency with backhaul capacity constraints for heterogeneous cellular networks using non-orthogonal multiple access (NOMA) technology. Firstly, considering the small cell transmit power constraints, small cell rate constraints and backhaul link capacity constraints, it constructed a power and bandwidth allocation model. Then,for power allocation, it used the difference of convex( DC) programming and the quasi-concavity of the function to transform the original problem into an equivalent convex problem, and used the convex difference iteration method and the dichotomy to find the global optimal solution. For the backhaul link bandwidth allocation, it transformed into a feasibility problem and gave an analytical solution. The simulation results show that the energy efficiency of the proposed scheme is higher than that of the existing schemes in the same scenario. [ABSTRACT FROM AUTHOR]

Copyright of Journal of South China University of Technology (Natural Science Edition) is the property of South China University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Telecommunication Engineering is the property of Telecommunication Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In order to solve problems of high power consumption, spectrum shortage and low energy efficiency in the ultra- intensive 5G mobile communication scenario, a resource allocation algorithm based on the maximum energy efficiency for the two-layer heterogeneous cellular non-orthogonal multiple access network was proposed. The original NP-hard optimization problem on the downlink communication link of ultra-dense scene was divided into two subproblem, such as frequency resource allocation and power allocation, which became a deterministic constraint optimization problem. The frequency resource allocation scheme of different user groups was obtained by using base station clustering based on the improved k-means algorithm and users grouping based on spectral clustering algorithm. The fraction of energy efficiency optimization was transformed into a solvable continuous convex optimization problem and power distribution was realized by Dinkelbach method, and the Lagrange multiplier iterative algorithm, respectively. Jointly optimize system energy efficiency in terms of base station clustering, user grouping, resource block allocation and power allocation, which minimized the inter-cluster interference and intra-cluster interference of the base station efficiently. The simulation results show that the proposed algorithm is better on energy efficiency and computational efficiency compared with existing algorithms. [ABSTRACT FROM AUTHOR]

Copyright of Journal on Communication / Tongxin Xuebao is the property of Journal on Communications Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Chongqing University of Posts & Telecommunications (Natural Science Edition) is the property of Chongqing University of Posts & Telecommunications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Chongqing University of Posts & Telecommunications (Natural Science Edition) is the property of Chongqing University of Posts & Telecommunications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Signal Processing is the property of Journal of Signal Processing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Energy efficiency (EE) has become a new indicator of network performance, and maximizing EE has become a hotspot in communication technology. In order to solve the problem of EE optimization in Macro/Femtocell heterogeneous network (HetNet) , this paper applied the bat algorithm to the problem firstly. Then.it proposed an inertial weight bat algorithm based on exponential decreasing. Aiming at the maximize the network EE as the optimization target.it used the improved algorithm to carry out the carrier allocation under the premise of satisfying the quality of service (QoS) .and compared the performance with the standard bat and genetic algorithm. The simulation results show that the number of carriers and users affects the EE. The proposed algorithm improves the transmission rate of the network and improves the EE by about 11% compared with the genetic algorithm. Experiments show that in the HetNet,the use of improved bat algorithm for carrier allocation can improve EE. [ABSTRACT FROM AUTHOR]

Appropriate resource allocation has great significance for enhancing the energy efficiency (EE) for Massive MIMO system Therefore, we formulate this problem as transmit power and antenna-based resource allocation in multi-user downlink Massive MIMO system, and solve it with the resource allocation iteration mechanism based on energy efficiency. First, a low complexity antenna selection algorithm is used to implement antenna subset after achieve number of antennas by the Lambert W function. Second, the properties of fractional programming and convex optimization are used to allocate transmit power. The simulation results indicate that the resource allocation scheme can effectively improve energy efficiency and enhance system performance. [ABSTRACT FROM AUTHOR]

Copyright of Computer Measurement & Control is the property of Magazine Agency of Computer Measurement & Control and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)