Cross-layer design of joint relay selection and power control scheme in relay-based multi-cell networks

2011 ◽  
Author(s):  
Di Wu ◽  
Gang Zhu ◽  
Dongmei Zhao ◽  
Lina Liu
Keyword(s):  
Power Control ◽  
Relay Selection ◽  
Cross Layer ◽  
Cross Layer Design ◽  
Control Scheme ◽  
Cell Networks

scholarly journals Security of Data with Enhanced Technique of AASR Protocol for Secure Crosslayer Routing in MANET

2020 ◽  
Vol 6 (6) ◽  
pp. 17-21
Author(s):  
Shifana Begum ◽  
Megha M Gamskar ◽  
Prakrithi Mogasale
Keyword(s):  
Power Control ◽  
Routing Protocol ◽  
Physical Layer ◽  
Cross Layer ◽  
Cross Layer Design ◽  
Transmission Power ◽  
Dos Attacks ◽  
Layered Architecture ◽  
And Performance ◽  
Reliable Path

MANET supports communication without any wired medium and with layered architecture. It does not uses any infrastructure support. Present alternative to the layered architecture is cross layer design approaches and the interaction between the layers is supported. The security of CLPC (Cross Layer Design Approach for Power control) routing protocol will be discussed in this paper. The transmission power and finding the effective route between source and destination can be improved by CLPC. The reliable path between the source and destination can be determined by RSS from the physical layer, but it is vulnerable to the DOS attacks. Here we propose a Secure cross layer power control protocol SCLPC to placate the attacks on CLPC. The SCLPC protocol provides better results and performance.

scholarly journals Power Control via Stackelberg Game for Small-Cell Networks

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Yanxiang Jiang ◽  
Hui Ge ◽  
Mehdi Bennis ◽  
Fu-Chun Zheng ◽  
Xiaohu You
Keyword(s):  
Power Control ◽  
Optimization Problems ◽  
Stackelberg Game ◽  
Small Cell ◽  
User Equipment ◽  
Stackelberg Equilibrium ◽  
Small Cell Networks ◽  
Transmit Power ◽  
Control Scheme ◽  
Cell Networks

In this paper, power control in the uplink for two-tier small-cell networks is investigated. We formulate the power control problem as a Stackelberg game, where the macrocell user equipment (MUE) acts as the leader and the small-cell user equipment (SUE) acts as the follower. To reduce the cross-tier and cotier interferences and the power consumption of both the MUE and SUE, we propose optimizing not only the transmit rate but also the transmit power. The corresponding optimization problems are solved through a two-layer iteration. In the inner iteration, the SUE items (SUEs) compete with each other, and their optimal transmit powers are obtained through iterative computations. In the outer iteration, the optimal transmit power of the MUE is obtained in a closed form based on the transmit powers of the SUEs through proper mathematical manipulations. We prove the convergence of the proposed power control scheme, and we also theoretically show the existence and uniqueness of the Stackelberg equilibrium (SE) in the formulated Stackelberg game. The simulation results show that the proposed power control scheme provides considerable improvements, particularly for the MUE.

Game Theory-Based Coverage Optimization for Small Cell Networks

2015 ◽  
pp. 184-211
Author(s):  
Yiqing Zhou ◽  
Liang Huang ◽  
Lin Tian ◽  
Jinglin Shi
Keyword(s):  
Game Theory ◽  
Power Control ◽  
Optimization Methods ◽  
Small Cell ◽  
Small Cell Networks ◽  
Control Center ◽  
Coverage Optimization ◽  
Control Scheme ◽  
Coverage Problems ◽  
Cell Networks

Focusing on the coverage optimization of small cell networks (SCN), this chapter starts with a detailed analysis on various coverage problems, based on which the coverage optimization problem is formulated. Then centralized and distributed coverage optimization methods based on game theory are described. Firstly, considering the coverage optimization with a control center, a modified particle swarm optimization (MPSO) is presented for the self-optimization of SCN, which employs a heuristic power control scheme to search for the global optimum solution. Secondly, distributed optimization using game theory (DGT) without a control center is concerned. Considering both throughput and interference, a utility function is formulated. Then a power control scheme is proposed to find the Nash Equilibrium (NE). Simulation results show that MPSO and DGT significantly outperform conventional schemes. Moreover, compared with MPSO, DGT uses much less overhead. Finally, further research directions are discussed and conclusions are drawn.

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