scholarly journals Coexistence of Cognitive Small Cell and WiFi System: A Traffic Balancing Dual-Access Resource Allocation Scheme

2018 ◽  
Vol 2018 ◽  
pp. 1-17 ◽  
Author(s):  
Xiaoge Huang ◽  
Yangyang Li ◽  
She Tang ◽  
Qianbin Chen
Keyword(s):  
Power Allocation ◽  
Optimization Problems ◽  
Holistic Approach ◽  
Data Rate ◽  
Small Cell ◽  
Dual Band ◽  
Cell Selection ◽  
Allocation Scheme ◽  
Traffic Balancing ◽  
Unlicensed Bands

We consider a holistic approach for dual-access cognitive small cell (DACS) networks, which uses the LTE air interface in both licensed and unlicensed bands. In the licensed band, we consider a sensing-based power allocation scheme to maximize the sum data rate of DACSs by jointly optimizing the cell selection, the sensing operation, and the power allocation under the interference constraint to macrocell users. Due to intercell interference and the integer nature of the cell selection, the resulting optimization problems lead to a nonconvex integer programming. We reformulate the problem to a nonconvex power allocation game and find the relaxed equilibria, quasi-Nash equilibrium. Furthermore, in order to guarantee the fairness of the whole system, we propose a dynamic satisfaction-based dual-band traffic balancing (SDTB) algorithm over licensed and unlicensed bands for DACSs which aims at maximizing the overall satisfaction of the system. We obtain the optimal transmission time in the unlicensed band to ensure the proportional fair coexistence with WiFi while guaranteeing the traffic balancing of DACSs. Simulation results demonstrate that the SDTB algorithm could achieve a considerable performance improvement relative to the schemes in literature, while providing a tradeoff between maximizing the total data rate and achieving better fairness among networks.

scholarly journals Small-Cell Traffic Balancing Over Licensed and Unlicensed Bands

2015 ◽  
Vol 64 (12) ◽  
pp. 5850-5865 ◽  
Author(s):  
Feilu Liu ◽  
Erdem Bala ◽  
Elza Erkip ◽  
Mihaela C. Beluri ◽  
Rui Yang
Keyword(s):  
Small Cell ◽  
Traffic Balancing ◽  
Unlicensed Bands

scholarly journals Energy efficiency based joint cell selection and power allocation scheme for HetNets

2016 ◽  
Vol 2 (4) ◽  
pp. 184-190 ◽  
Author(s):  
Kwabena Kobia Mensah ◽  
Rong Chai ◽  
Denis Bilibashi ◽  
Feifei Gao
Keyword(s):  
Energy Efficiency ◽  
Power Allocation ◽  
Cell Selection ◽  
Allocation Scheme

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.

scholarly journals End-to-End Data Rate Performance of Decode-and-Forward Relaying with Different Resource Allocation Schemes

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Inam Ullah ◽  
Alexis Dowhuszko ◽  
Zhong Zheng ◽  
David González González ◽  
Jyri Hämäläinen
Keyword(s):  
Resource Allocation ◽  
Closed Form ◽  
Data Rate ◽  
Allocation Scheme ◽  
Optimal Resource Allocation ◽  
Decode And Forward ◽  
Optimal Resource ◽  
The Mean ◽  
Resource Allocation Scheme ◽  
Resource Allocation Schemes

This paper studies the end-to-end (e2e) data rate of dual-hop Decode-and-Forward (DF) infrastructure relaying under different resource allocation schemes. In this context, we first provide a comparative analysis of the optimal resource allocation scheme with respect to several other approaches in order to provide insights into the system behavior and show the benefits of each alternative. Then, assuming the optimal resource allocation, a closed form expression for the distribution of the mean and outage data rates is derived. It turns out that the corresponding mean e2e data rate formula attains an expression in terms of an integral that does not admit a closed form solution. Therefore, a tight lower bound formula for the mean e2e data rate is presented. Results can be used to select the most convenient resource allocation scheme and perform link dimensioning in the network planning phase, showing the explicit relationships that exist between component link bandwidths, SNR values, and mean data rate.

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