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A full‐duplex relay selection strategy based on potential game in cognitive cooperative networks
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SummaryIn this paper, we study the full‐duplex relay selection strategy based on a potential game in a cognitive cooperative network under the interference power constraint from secondary users to the primary receivers, the total available transmission power constraint for the secondary system, and the self‐interference constraint at each secondary relay. The relay selection problem is modeled as a non‐cooperative game where the total rate of a cognitive cooperative network has common utility. Then, we prove that the game is a potential game that has at least a pure strategy Nash equilibrium (NE), and the optimal strategy set that able to maximize cognitive cooperative system rate is also a pure strategy NE of the proposed game model. On the premise of having no information of infeasible strategy sets, we solve the feasibility conditions of the pure NE in the proposed game. Furthermore, we propose a cognitive full‐duplex relay iterative algorithm that can achieve a pure strategy NE, and the complexity and the convergence of the proposed algorithm are studied. Simulation results show that the proposed algorithm can achieve optimal or near optimal rate performance with low complexity and offers significant performance gain compared with the traditional half‐duplex mode.
Title: A full‐duplex relay selection strategy based on potential game in cognitive cooperative networks
Description:
SummaryIn this paper, we study the full‐duplex relay selection strategy based on a potential game in a cognitive cooperative network under the interference power constraint from secondary users to the primary receivers, the total available transmission power constraint for the secondary system, and the self‐interference constraint at each secondary relay.
The relay selection problem is modeled as a non‐cooperative game where the total rate of a cognitive cooperative network has common utility.
Then, we prove that the game is a potential game that has at least a pure strategy Nash equilibrium (NE), and the optimal strategy set that able to maximize cognitive cooperative system rate is also a pure strategy NE of the proposed game model.
On the premise of having no information of infeasible strategy sets, we solve the feasibility conditions of the pure NE in the proposed game.
Furthermore, we propose a cognitive full‐duplex relay iterative algorithm that can achieve a pure strategy NE, and the complexity and the convergence of the proposed algorithm are studied.
Simulation results show that the proposed algorithm can achieve optimal or near optimal rate performance with low complexity and offers significant performance gain compared with the traditional half‐duplex mode.
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