Spectrum-efficiency enhancement in small cell networks with biasing cell association and eICIC: An analytical framework

2014 ◽  
Vol 29 (2) ◽  
pp. 362-377 ◽  
Author(s):  
Yongbin Wang ◽  
Hong Ji ◽  
Heli Zhang
Keyword(s):  
Analytical Framework ◽  
Small Cell ◽  
Spectrum Efficiency ◽  
Efficiency Enhancement ◽  
Small Cell Networks ◽  
Cell Association ◽  
Cell Networks

scholarly journals Spectrum Sharing with Dynamic Cournot Game in Vehicle-Enabled Cognitive Small-Cell Networks

2019 ◽  
Vol 2019 ◽  
pp. 1-9
Author(s):  
Guilu Wu ◽  
Huilin Jiang
Keyword(s):  
Nash Equilibrium ◽  
Spectrum Sharing ◽  
Dynamic Game ◽  
Small Cell ◽  
Dynamic Spectrum ◽  
Spectrum Allocation ◽  
Spectrum Efficiency ◽  
Dynamic Spectrum Allocation ◽  
Small Cell Networks ◽  
Cell Networks

Cognitive radio technology can effectively improve spectrum efficiency in wireless networks and is also applicable to vehicle small-cell networks. In this paper, we consider the problem of spectrum sharing among a vehicle primary user (V-PU) and multiple vehicle secondary users (V-SUs). This problem is modeled as a competition market, and the solution for V-SUs is designed using a non-cooperative game. A utility function that measures the profit of the V-PU considering quality of service (QoS) is proposed, aiming at maximizing the profit of the V-PU. Nash equilibrium is obtained as the best solution in our game. Then, the realistic vehicle-enabled cognitive small-cell network is considered in building the dynamic spectrum allocation problem. The V-SUs adjust their current strategies gradually and iteratively based on the observations on the strategies of the previous moment. This adjustment parameter is controlled by the frequency of adjustment. The stability analysis of the dynamic game is given out subsequently for dynamic spectrum allocation. The numerical results show the effectiveness of the proposed dynamic spectrum scheme for vehicle-enabled cognitive small-cell networks and Nash equilibrium point’s existence.

scholarly journals QoE-Aware Downlink User-Cell Association in Small Cell Networks: A Transfer-matching Game Theoretic Solution With Peer Effects

IEEE Access ◽  
2016 ◽  
Vol 4 ◽  
pp. 10029-10041 ◽  
Author(s):  
Hongxiang Shao ◽  
Hangsheng Zhao ◽  
Youming Sun ◽  
Jianzhao Zhang ◽  
Yuhua Xu
Keyword(s):  
Peer Effects ◽  
Small Cell ◽  
Small Cell Networks ◽  
Cell Association ◽  
Game Theoretic ◽  
Matching Game ◽  
Theoretic Solution ◽  
Cell Networks

scholarly journals IMPSO and Linear Programming-Based Energy-Efficient Cell Association Algorithm for Backhaul-Constrained Ultra-Dense Small-Cell Networks

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Huilin Jiang ◽  
Wenxiang Zhu ◽  
Xiang Song ◽  
Guilu Wu
Keyword(s):  
Energy Efficiency ◽  
Linear Programming ◽  
Optimization Problem ◽  
Small Cell ◽  
Small Cells ◽  
Small Cell Networks ◽  
Efficiency Optimization ◽  
Cell Association ◽  
Backhaul Link ◽  
Cell Networks

This paper studies the energy efficiency optimization problem for coordinated multipoint (CoMP)-enabled and backhaul-constrained ultra-dense small-cell networks (UDNs). Energy efficiency is an eternal topic for future wireless communication networks; however, taking actual bottleneck of the backhaul link and the coordinated network architecture into consideration, it is difficult to find an effective way to improve the energy efficiency of the network. Aiming at this problem, we propose to combine cell association, subchannel allocation, backhaul resource allocation, and sleep/on of the cells together to develop an optimization algorithm for energy efficiency in UDN and then solve the formulated energy efficiency optimization problem by means of improved modified particle swarm optimization (IMPSO) and linear programming in mathematics. Simulation results indicate that nearly 13 % energy cost saving and 21 % energy efficiency improvement can be obtained by combining IMPSO with linear programming, and the backhaul link data rate can be improved by 30 % as the number of small cells increases. From the results, it can be found that by combining IMPSO with linear programming, the proposed algorithm can improve the network energy efficiency effectively at the expense of limited complexity.

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