Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/228639
Title: Self-Organizing Hit Avoidance in Distributed Frequency Hopping Multiple Access Networks
Authors: Long Yu;Yuhua Xu;Qihui Wu;Luliang Jia
Year: 2017
Publisher: IEEE
Abstract: In this paper, we investigate the frequency hit avoidance problem in distributed frequency hopping multiple access (FHMA) networks, in which each user intends to avoid the frequency hit with others by choosing the appropriate frequency set and frequency hopping sequence. First, we define the network hit degree as the metric for the hits, and formulate the frequency hit avoidance problem as an optimization problem of the network hit degree. Second, we formulate a non-cooperative game model to solve this optimization problem, and prove the game is an exact potential game, which illustrates that the Nash equilibria (NE) point of the game is the optimal solution of the optimization problem. Finally, we propose a fragment-based distributed hit avoidance (FDHA) learning algorithm and prove that the learning algorithm can converge to the NE point. The simulation results show that the proposed algorithm can converge to the optimal solution rapidly such that the FHMA network is hit-free.
Description: 
URI: http://localhost/handle/Hannan/228639
volume: 5
More Information: 26614,
26622
Appears in Collections:2017

Files in This Item:
File SizeFormat 
8114165.pdf4.84 MBAdobe PDF
Title: Self-Organizing Hit Avoidance in Distributed Frequency Hopping Multiple Access Networks
Authors: Long Yu;Yuhua Xu;Qihui Wu;Luliang Jia
Year: 2017
Publisher: IEEE
Abstract: In this paper, we investigate the frequency hit avoidance problem in distributed frequency hopping multiple access (FHMA) networks, in which each user intends to avoid the frequency hit with others by choosing the appropriate frequency set and frequency hopping sequence. First, we define the network hit degree as the metric for the hits, and formulate the frequency hit avoidance problem as an optimization problem of the network hit degree. Second, we formulate a non-cooperative game model to solve this optimization problem, and prove the game is an exact potential game, which illustrates that the Nash equilibria (NE) point of the game is the optimal solution of the optimization problem. Finally, we propose a fragment-based distributed hit avoidance (FDHA) learning algorithm and prove that the learning algorithm can converge to the NE point. The simulation results show that the proposed algorithm can converge to the optimal solution rapidly such that the FHMA network is hit-free.
Description: 
URI: http://localhost/handle/Hannan/228639
volume: 5
More Information: 26614,
26622
Appears in Collections:2017

Files in This Item:
File SizeFormat 
8114165.pdf4.84 MBAdobe PDF
Title: Self-Organizing Hit Avoidance in Distributed Frequency Hopping Multiple Access Networks
Authors: Long Yu;Yuhua Xu;Qihui Wu;Luliang Jia
Year: 2017
Publisher: IEEE
Abstract: In this paper, we investigate the frequency hit avoidance problem in distributed frequency hopping multiple access (FHMA) networks, in which each user intends to avoid the frequency hit with others by choosing the appropriate frequency set and frequency hopping sequence. First, we define the network hit degree as the metric for the hits, and formulate the frequency hit avoidance problem as an optimization problem of the network hit degree. Second, we formulate a non-cooperative game model to solve this optimization problem, and prove the game is an exact potential game, which illustrates that the Nash equilibria (NE) point of the game is the optimal solution of the optimization problem. Finally, we propose a fragment-based distributed hit avoidance (FDHA) learning algorithm and prove that the learning algorithm can converge to the NE point. The simulation results show that the proposed algorithm can converge to the optimal solution rapidly such that the FHMA network is hit-free.
Description: 
URI: http://localhost/handle/Hannan/228639
volume: 5
More Information: 26614,
26622
Appears in Collections:2017

Files in This Item:
File SizeFormat 
8114165.pdf4.84 MBAdobe PDF