Harvested Energy Maximization of SWIPT System with Popularity Cache Scheme in Dense Small Cell Networks

In this paper, we propose a harvested energy maximization problem of simultaneous wireless information and power transfer (SWIPT) system with popularity cache scheme in dense small cell networks. Firstly, network model, content request, and popularity cache schemes are provided in the system model. Then, we establish a harvested energy maximization problem of SWIPT system with popularity cache scheme in dense small cell networks, where maximum transmit power of small cell base stations (SBSs), minimum rate requirement, i.e., quality of service (QoS) of user terminals (UTs), and power splitting ratio are considered. Further, an iterative power splitting ratio and power allocation optimization (IPSPA) algorithm is proposed to solve the formulated problem. Finally, the better performance of our proposed method is demonstrated through a number of simulations. These results are of significance for maximizing harvesting energy of UTs and reducing consumption of backhaul resources and energy.

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On the Performance of UAV-Aided Content Caching in Small-Cell Networks with Joint Transmission

Electronics ◽

10.3390/electronics10091040 ◽

2021 ◽

Vol 10 (9) ◽

pp. 1040

Author(s):

Menghan Wei ◽

Youjia Chen ◽

Ming Ding

Keyword(s):

Transmission Rate ◽

High Mobility ◽

Limited Resource ◽

Small Cell ◽

Base Stations ◽

Cell Content ◽

Small Cell Networks ◽

Content Caching ◽

Cell Networks ◽

Joint Transmission

Unmanned aerial vehicles (UAVs), featured by the high-mobility and high-quality propagation environment, have shown great potential in wireless communication applications. In this paper, a novel UAV-aided small-cell content caching network is proposed and analyzed, where joint transmission (JT) is considered in the dense small-cell networks and mobile UAVs are employed to shorten the serving distance. The system performance is evaluated in terms of the average cache hit probability and the ergodic transmission rate. From the analytical results, we find that (i) the proposed UAV-aided small-cell network shows superior caching performance and, even with a small density of UAVs the system’s cache hit probability, can be improved significantly; (ii) the content’s optimal caching probability to maximize the cache hit probability is proportional to the (K+1)-th root of its request probability, where K is the number of small-cell base stations that serve each user by JT; (iii) caching the most popular content in UAVs may lead to a low transmission rate due to the limited resource offered by the low-density UAVs. Simulation results are presented to validate the theoretical results and the performance gain achieved by the optimal caching strategy.

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Game Theory-Based Radio Resource Optimization in Heterogeneous Small Cell Networks (HSCNs)

Game Theory Framework Applied to Wireless Communication Networks - Advances in Wireless Technologies and Telecommunication ◽

10.4018/978-1-4666-8642-7.ch006 ◽

2015 ◽

pp. 137-183

Author(s):

Mugen Peng ◽

Yaohua Sun ◽

Chengdan Sun ◽

Manzoor Ahmed

Keyword(s):

Game Theory ◽

Resource Allocation ◽

Small Cell ◽

Base Stations ◽

Radio Resource Allocation ◽

Radio Resource ◽

Small Cell Networks ◽

The Game Theory ◽

Simulation Results ◽

Cell Networks

To optimize radio resource allocation, the game theory is utilized as a powerful tool because its characteristic can be adaptive to the distribution characteristics of in heterogeneous small cell networks (HSCNs). This chapter summarizes the recent achievements for the game theory based radio resource allocation in HSCNs, where macro base stations (MBSs) and dense small cell base stations (SBSs) share the same frequency spectrum and interfere with each other. Two kinds of game models are introduced to optimize the radio resource allocation, namely the non-cooperative Stackelberg and the cooperative coalition. System models, optimization problem formulation, problem solution, and simulation results for these two kinds of game models are presented. Particularly, the Stackelberg models for HSCNs are presented with the Stackelberg equilibrium and the closed-form expressions. The coalition formations for traditional HCSNs, cloud small cell networks, and heterogeneous cloud small cell networks are introduced. Simulation results are shown to demonstrate the proposed game theory based radio resource optimization strategies converged and efficient.

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