scholarly journals Transmission Strategy Design and Resource Allocation in D2D Multicast Cooperative Communications with SWIPT

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Chenfan Weng ◽  
Dingcheng Yang ◽  
Jun Wan ◽  
Lin Xiao ◽  
Chuanqi Zhu
Keyword(s):  
Resource Allocation ◽  
Cooperative Communications ◽  
Communication Systems ◽  
Spectrum Efficiency ◽  
Second Step ◽  
Total System ◽  
Power Splitting ◽  
Transmission Strategy ◽  
Multiple Receivers ◽  
Strategy Design

This paper proposes a new transmission strategy for device-to-device (D2D) multicast cooperative communication systems based on Simultaneous Wireless Information and Power Transfer (SWIPT) technology. The transmission block is divided into two slots. In the first slot, the source user transmits the information and energy to the help user by SWIPT. In the second slot, the help user uses the cellular spectrum and forwards the information to multiple receivers by using harvested energy. In this paper, we aim to maximize the total system rate, and to tackle the problem, we propose a two-step scheme: In the first step, the resource allocation problem is solved by linear programming. In the second step, the power-splitting coefficient value is obtained by taking the benefit of help user into account. Numerical results show that the proposed strategy not only effectively improves the overall throughput and spectrum efficiency but also motivates the cooperation.

scholarly journals Optimization of Power Allocation for Multiusers in Multi-Spot-Beam Satellite Communication Systems

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Heng Wang ◽  
Aijun Liu ◽  
Xiaofei Pan ◽  
Jianfei Yang
Keyword(s):  
Resource Allocation ◽  
Power Allocation ◽  
Communication Systems ◽  
Satellite Communication ◽  
Utilization Efficiency ◽  
System Capacity ◽  
Total System ◽  
Allocation Algorithm ◽  
Satellite Platform ◽  
Spot Beam

In recent years, multi-spot-beam satellite communication systems have played a key role in global seamless communication. However, satellite power resources are scarce and expensive, due to the limitations of satellite platform. Therefore, this paper proposes optimizing the power allocation of each user in order to improve the power utilization efficiency. Initially the capacity allocated to each user is calculated according to the satellite link budget equations, which can be achieved in the practical satellite communication systems. The problem of power allocation is then formulated as a convex optimization, taking account of a trade-off between the maximization of the total system capacity and the fairness of power allocation amongst the users. Finally, an iterative algorithm based on the duality theory is proposed to obtain the optimal solution to the optimization. Compared with the traditional uniform resource allocation or proportional resource allocation algorithms, the proposed optimal power allocation algorithm improves the fairness of power allocation amongst the users. Moreover, the computational complexity of the proposed algorithm is linear with both the numbers of the spot beams and users. As a result, the proposed power allocation algorithm is easy to be implemented in practice.

scholarly journals Social-Aware-Based Resource Allocation for NOMA-Enhanced D2D Communications

2020 ◽  
Vol 10 (7) ◽  
pp. 2446
Author(s):  
Wenying Gu ◽  
Qi Zhu
Keyword(s):  
Resource Allocation ◽  
Power Control ◽  
Communication Systems ◽  
Channel Allocation ◽  
Matching Theory ◽  
Spectrum Efficiency ◽  
System Throughput ◽  
Convex Problem ◽  
Power Control Algorithm ◽  
Joint Channel

In mobile communication systems, device-to-device (D2D) communication and nonorthogonal multiple access (NOMA) are effective ways to improve spectrum efficiency and system throughput. In the NOMA-based D2D system, social relationship among D2D users is introduced to form D2D clusters, and NOMA is used for many-to-one communication in each D2D cluster. This paper proposes a joint channel allocation and power control algorithm which decomposes the resource allocation problem into two subproblems: channel allocation and power control. Matching theory is utilized to allocate channels for D2D clusters and sequential convex programming is applied to transform the optimization target to a convex problem before solving it via genetic algorithm. Simulation results indicate the superiority of our algorithm in improving the system throughput on the basis of meeting users’ needs for files.

A novel coevolving differential evolution and its application in intelligent device-to-device communication systems

2021 ◽  
pp. 1-15
Author(s):  
Binbin Xu ◽  
Chang Chen ◽  
Jinrui Tang ◽  
Ruoli Tang
Keyword(s):  
Resource Allocation ◽  
Differential Evolution ◽  
Communication Systems ◽  
Optimal Allocation ◽  
Modern Society ◽  
Spectrum Efficiency ◽  
D2d Communication ◽  
Optimal Resource Allocation ◽  
Device To Device ◽  
Optimal Resource

Due to the increasingly demand of wireless broadband applications in modern society, the device-to-device (D2D) communication technique plays an important role for improving communication spectrum efficiency and quality of service (QoS). This study focuses on the optimal allocation of link resource in D2D communication systems using intelligent approaches, in order to obtain optimal energy efficiency of D2D-pair users (DP) and also ensure communication QoS. To be specific, the optimal resource allocation (ORA) model for ensuring the cooperation between DP and cellular users (CU) is established, and a novel coding strategy of ORA model is also proposed. Then, for efficiently optimizing the ORA model, a novel swarm-intelligence-based algorithm called the dynamic topology coevolving differential evolution (DTC-DE) is developed, and the efficiency of DTC-DE is also tested by a comprehensive set of benchmark functions. Finally, the DTC-DE algorithm is employed for optimizing the proposed ORA model, and some state-of-the-art algorithms are also employed for comparison. Result of case study shows that the DTC-DE outperforms its competitors significantly, and the optimal resource allocation can be obtained by DTC-DE with robust performance.

scholarly journals Mobile Fog Computing-Assisted Resource Allocation for Two-Hop SWIPT OFDM Networks

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Xiaofei Di ◽  
Yu Zhang ◽  
Tong Liu ◽  
Shaoli Kang ◽  
Yue Zhao
Keyword(s):  
Resource Allocation ◽  
Orthogonal Frequency Division Multiplexing ◽  
Fog Computing ◽  
Achievable Rate ◽  
Fast Time ◽  
Power Splitting ◽  
Frequency Division ◽  
Decode And Forward ◽  
Subcarrier Pairing ◽  
Receiver Architecture

The mobile fog computing-assisted resource allocation (RA) is studied for simultaneous wireless information and power transfer (SWIPT) two-hop orthogonal frequency division multiplexing (OFDM) networks, where a decode-and-forward (DF) relay first harvests energy from signals emitted by a source and then helps the source to forward information to its destination by using the harvested energy. Power splitting (PS) strategy is adopted at the relay and a different PS (DPS) receiver architecture is proposed, where the PS factors of all subcarriers are different. A RA problem is formulated to maximize the system’s achievable rate by jointly optimizing subcarrier pairing, power allocation, and PS factors. Since the RA problem is a nonconvex problem and is difficult to solve, an efficient RA algorithm is designed. As the wireless channels are fast time-varying, the computation is performed in mobile fog node close to end nodes, instead of remote clouds. Results demonstrate that the achievable rate is significantly increased by using the proposed RA algorithm. It is also found that the computation complexity of RA algorithm of DPS receiver architecture is much lower than the existing identical PS (IPS) receiver architecture, and thus the proposed DPS architecture is more suitable for computation-constrained fog system.

scholarly journals Secrecy-Oriented Optimization of Sparse Code Multiple Access for Simultaneous Wireless Information and Power Transfer in 6G Aerial Access Networks

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Jingmin Zhang ◽  
Xiaokui Yue ◽  
Xuan Li ◽  
Haofei Zhang ◽  
Tao Ni ◽  
...  
Keyword(s):  
Multiple Access ◽  
Optimization Methods ◽  
Access Networks ◽  
Spectrum Efficiency ◽  
Sparse Code ◽  
Power Splitting ◽  
Power Transfer ◽  
Sixth Generation ◽  
Successive Convex Approximation ◽  
Iot Devices

This article focuses on the simultaneous wireless information and power transfer (SWIPT) systems, which provide both the power supply and the communications for Internet-of-Things (IoT) devices in the sixth-generation (6G) network. Due to the extremely stringent requirements on reliability, speed, and security in the 6G network, aerial access networks (AANs) are deployed to extend the coverage of wireless communications and guarantee robustness. Moreover, sparse code multiple access (SCMA) is implemented on the SWIPT system to further promote the spectrum efficiency. To improve the speed and security of SWIPT systems in 6G AANs, we have developed an optimization algorithm of SCMA to maximize the secrecy sum rate (SSR). Specifically, a power-splitting (PS) strategy is applied by each user to coordinate its energy harvesting and information decoding. Hence, the SSR maximization problems in the SCMA system are formulated in terms of the PS and resource allocation, under the constraints on the minimum rates and minimum harvested energy of individual users. Then, a successive convex approximation method is introduced to transform the nonconvex problems to the convex ones, which are then solved by an iterative algorithm. In addition, we investigate the SSR performance of the SCMA system supported by our optimization methods, when the impacts from different perspectives are considered. Our studies and simulation results show that the SCMA system supported by our proposed optimization algorithms significantly outperforms the legacy system with uniform power allocation and fixed PS.

scholarly journals Performance Analysis for Exact and Upper Bound Capacity in DF Energy Harvesting Full-Duplex with Hybrid TPSR Protocol

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Phu Tran Tin ◽  
Phan Van-Duc ◽  
Tan N. Nguyen ◽  
Le Anh Vu
Keyword(s):  
Energy Harvesting ◽  
Upper Bound ◽  
Relay Node ◽  
Ergodic Capacity ◽  
Cooperative Relaying ◽  
Spectrum Efficiency ◽  
Full Duplex ◽  
Power Splitting ◽  
Decode And Forward ◽  
Relaying System

In this paper, we investigate the full-duplex (FD) decode-and-forward (DF) cooperative relaying system, whereas the relay node can harvest energy from radiofrequency (RF) signals of the source and then utilize the harvested energy to transfer the information to the destination. Specifically, a hybrid time-power switching-based relaying method is adopted, which leverages the benefits of time-switching relaying (TSR) and power-splitting relaying (PSR) protocols. While energy harvesting (EH) helps to reduce the limited energy at the relay, full-duplex is one of the most important techniques to enhance the spectrum efficiency by its capacity of transmitting and receiving signals simultaneously. Based on the proposed system model, the performance of the proposed relaying system in terms of the ergodic capacity (EC) is analyzed. Specifically, we derive the exact closed form for upper bound EC by applying some special function mathematics. Then, the Monte Carlo simulations are performed to validate the mathematical analysis and numerical results.

scholarly journals Optimal and Robust Distributed Resource Allocation for SWIPT-Enabled Cognitive Networks

2020 ◽  
Author(s):  
Yongjun Xu ◽  
Haijian Sun ◽  
Jie Yang ◽  
Guan Gui ◽  
Song Guo
Keyword(s):  
Resource Allocation ◽  
Closed Form ◽  
Power Allocation ◽  
Energy Region ◽  
High Energy ◽  
Cognitive Networks ◽  
Feasible Region ◽  
Power Splitting ◽  
Joint Power ◽  
The Impact

Simultaneous wireless information and power transfer (SWIPT)-enabled cognitive networks (CRNs) is recognized as one of the most promising techniques to improve spectrum efficiency and prolong operation lifetime in 5G and beyond. However, existing methods focus on the centralized algorithm and the power allocation under perfect channel state information (CSI). The analytical solution and the impact of power splitting (PS) on the optimal power allocation strategy are not addressed. In addition, the influence of the PS factor on the feasible region of transit power is rarely analyzed. In this paper, we propose a joint power allocation and PS algorithm under perfect CSI and imperfect CSI, respectively, for multiuser SWIPT-enabled CRNs scenarios. The power minimization of resource allocation problem is formulated as a multivariate nonconvex optimization which is hard to obtain the closed-form solution. Hence, we propose a suboptimal algorithm to alternatively optimize the power allocation and PS coefficient under the cases of the low-harvested energy region and the high-harvested energy region, respectively. Moreover, a closed-form distributed power allocation and PS expressions are derived by the Lagrangian approach. Simulation results confirm the proposed method with good robustness and high energy efficiency.

Sign in / Sign up

Export Citation Format

Share Document