scholarly journals Energy-Efficient Joint Base Station Switching and Power Allocation for Smart Grid Based Hybrid-Powered CoMP-Enabled HetNet

2021 ◽  
Vol 13 (8) ◽  
pp. 213
Author(s):  
Shornalatha Euttamarajah ◽  
Yin Hoe Ng ◽  
Chee Keong Tan
Keyword(s):  
Wireless Networks ◽  
Power Allocation ◽  
Low Complexity ◽  
Base Station ◽  
Design Criterion ◽  
Combinatorial Optimisation ◽  
Dual Decomposition ◽  
Hybrid Energy ◽  
Data Intensive ◽  
Bs Switching

With the rapid proliferation of wireless traffic and the surge of various data-intensive applications, the energy consumption of wireless networks has tremendously increased in the last decade, which not only leads to more CO2 emission, but also results in higher operating expenditure. Consequently, energy efficiency (EE) has been regarded as an essential design criterion for future wireless networks. This paper investigates the problem of EE maximisation for a cooperative heterogeneous network (HetNet) powered by hybrid energy sources via joint base station (BS) switching (BS-Sw) and power allocation using combinatorial optimisation. The cooperation among the BSs is achieved through a coordinated multi-point (CoMP) technique. Next, to overcome the complexity of combinatorial optimisation, Lagrange dual decomposition is applied to solve the power allocation problem and a sub-optimal distance-based BS-Sw scheme is proposed. The main advantage of the distance-based BS-Sw is that the algorithm is tuning-free as it exploits two dynamic thresholds, which can automatically adapt to various user distributions and network deployment scenarios. The optimal binomial and random BS-Sw schemes are also studied to serve as benchmarks. Further, to solve the non-fractional programming component of the EE maximisation problem, a low-complexity and fast converging Dinkelbach’s method is proposed. Extensive simulations under various scenarios reveal that in terms of EE, the proposed joint distance-based BS-Sw and power allocation technique applied to the cooperative and harvesting BSs performs around 15–20% better than the non-cooperative and non-harvesting BSs and can achieve near-optimal performance compared to the optimal binomial method.

scholarly journals Energy-Efficient Power Allocation and Relay Selection Schemes for Relay-Assisted D2D Communications in 5G Wireless Networks

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2865 ◽  
Author(s):  
Md Rahman ◽  
YoungDoo Lee ◽  
Insoo Koo
Keyword(s):  
Wireless Networks ◽  
Power Allocation ◽  
Relay Selection ◽  
Base Station ◽  
Data Rate ◽  
Transmission Power ◽  
D2d Communications ◽  
Long Distance ◽  
Inference System ◽  
Efficient Power

Device-to-device (D2D) communications allows user equipment (UE) that are in close proximity to communicate with each other directly without using a base station. Relay-assisted D2D (RA-D2D) communications in 5G networks can be applied to support long-distance users and to improve energy efficiency (EE) of the networks. In this paper, we first establish a multi-relay system model where the D2D UEs can communicate with each other by reusing only one cellular uplink resource. Then, we apply an adaptive neuro-fuzzy inference system (ANFIS) architecture to select the best D2D relay to forward D2D source information to the expected D2D destination. Efficient power allocation (PA) in the D2D source and the D2D relay are critical problems for operating such networks, since the data rate of the cellular uplink and the maximum transmission power of the system need to be satisfied. As is known, 5G wireless networks also aim for low energy consumption to better implement the Internet of Things (IoT). Consequently, in this paper, we also formulate a problem to find the optimal solutions for PA of the D2D source and the D2D relay in terms of maximizing the EE of RA-D2D communications to support applications in the emerging IoT. To solve the PA problems of RA-D2D communications, a particle swarm optimization algorithm is employed to maximize the EE of the RA-D2D communications while satisfying the transmission power constraints of the D2D users, minimum data rate of cellular uplink, and minimum signal-to-interference-plus-noise-ratio requirements of the D2D users. Simulation results reveal that the proposed relay selection and PA methods significantly improve EE more than existing schemes.

scholarly journals Energy-Saving Management Mechanism Based on Hybrid Energy Supplies for LTE Heterogeneous Networks

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Peng Yu ◽  
Lei Feng ◽  
Wenjing Li ◽  
Xuesong Qiu
Keyword(s):  
Energy Saving ◽  
Heterogeneous Networks ◽  
Power Supply ◽  
Low Complexity ◽  
Base Station ◽  
Green Economy ◽  
User Association ◽  
Management Mechanism ◽  
Hybrid Energy ◽  
Self Organized

Aiming at the lack of integrated energy-saving (ES) methods based on hybrid energy supplies in LTE heterogeneous networks, a novel ES management mechanism considering hybrid energy supplies and self-organized network (SON) is proposed. The mechanism firstly constructs ES optimization model with hybrid energy supplies. And then a SON framework is proposed to resolve the model under practical networks. According to the framework, we divide the ES problem into four stages, which are traffic variation prediction, regional Base Station (BS) mode determination, BS-user association, and power supply. And four corresponding low-complexity algorithms are proposed to resolve them. Simulations are taken on under LTE underlay heterogeneous networks. Compared with other algorithms, results show that our mechanism can save 47.4% energy consumption of the network, while keeping coverage, interference, and service quality above acceptable levels, which takes on great green-economy significance.

scholarly journals Power Allocation and User Assignment Scheme for beyond 5G Heterogeneous Networks

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Khush Bakht ◽  
Furqan Jameel ◽  
Zain Ali ◽  
Wali Ullah Khan ◽  
Imran Khan ◽  
...  
Keyword(s):  
Wireless Networks ◽  
Power Allocation ◽  
Heterogeneous Networks ◽  
Cognitive Radios ◽  
Limiting Factors ◽  
Dual Decomposition ◽  
Joint Power ◽  
Decomposition Approach ◽  
Spectrum Scarcity ◽  
The Individual

The issue of spectrum scarcity in wireless networks is becoming prominent and critical with each passing year. Although several promising solutions have been proposed to provide a solution to spectrum scarcity, most of them have many associated tradeoffs. In this context, one of the emerging ideas relates to the utilization of cognitive radios (CR) for future heterogeneous networks (HetNets). This paper provides a marriage of two promising candidates (i.e., CR and HetNets) for beyond fifth generation (5G) wireless networks. More specifically, a joint power allocation and user assignment solution for the multiuser underlay CR-based HetNets has been proposed and evaluated. To counter the limiting factors in these networks, the individual power of transmitting nodes and interference temperature protection constraints of the primary networks have been considered. An efficient solution is designed from the dual decomposition approach, where the optimal user assignment is obtained for the optimized power allocation at each node. The simulation results validate the superiority of the proposed optimization scheme against conventional baseline techniques.

scholarly journals Low-complexity beam-domain channel estimation and power allocation in hybrid architecture massive MIMO systems

2019 ◽  
Vol 2019 (1) ◽  
Author(s):  
Xiao Chen ◽  
Zaichen Zhang ◽  
Liang Wu ◽  
Jian Dang
Keyword(s):  
Channel Estimation ◽  
Power Allocation ◽  
Spectral Efficiency ◽  
Communication Systems ◽  
Mimo Systems ◽  
Beam Steering ◽  
Estimation Method ◽  
Low Complexity ◽  
Estimation Accuracy ◽  
Hybrid Architecture

Abstract In this journal, we investigate the beam-domain channel estimation and power allocation in hybrid architecture massive multiple-input and multiple-output (MIMO) communication systems. First, we propose a low-complexity channel estimation method, which utilizes the beam steering vectors achieved from the direction-of-arrival (DOA) estimation and beam gains estimated by low-overhead pilots. Based on the estimated beam information, a purely analog precoding strategy is also designed. Then, the optimal power allocation among multiple beams is derived to maximize spectral efficiency. Finally, simulation results show that the proposed schemes can achieve high channel estimation accuracy and spectral efficiency.

scholarly journals Joint Optimization on Trajectory, Cache Placement, and Transmission Power for Minimum Mission Time in UAV-Aided Wireless Networks

2021 ◽  
Vol 10 (7) ◽  
pp. 426
Author(s):  
Tingting Lan ◽  
Danyang Qin ◽  
Guanyu Sun
Keyword(s):  
Wireless Communication ◽  
Power Allocation ◽  
Optimization Problems ◽  
Base Station ◽  
Optimization Techniques ◽  
Joint Optimization ◽  
Transmission Power ◽  
Wireless Backhaul ◽  
Mission Time ◽  
Cache Placement

In recent years, due to the strong mobility, easy deployment, and low cost of unmanned aerial vehicles (UAV), great interest has arisen in utilizing UAVs to assist in wireless communication, especially for on-demand deployment in emergency situations and temporary events. However, UAVs can only provide users with data transmission services through wireless backhaul links established with a ground base station, and the limited capacity of the wireless backhaul link would limit the transmission speed of UAVs. Therefore, this paper designed a UAV-assisted wireless communication system that used cache technology and realized the transmission of multi-user data by using the mobility of UAVs and wireless cache technology. Considering the limited storage space and energy of UAVs, the joint optimization problem of the UAV’s trajectory, cache placement, and transmission power was established to minimize the mission time of the UAV. Since this problem was a non-convex problem, it was decomposed into three sub-problems: trajectory optimization, cache placement optimization, and power allocation optimization. An iterative algorithm based on the successive convex approximation and alternate optimization techniques was proposed to solve these three optimization problems. Finally, in the power allocation optimization, the proposed algorithm was improved by changing the optimization objective function. Numerical results showed that the algorithm had good performance and could effectively reduce the task completion time of the UAV.

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