研究目的
Investigating the problem of database-assisted spectrum access in dynamic TV white spectrum networks with varying active user sets and no central controller or information exchange.
研究成果
The paper concludes that the best Nash equilibrium is almost the same with the optimal solution, and the achievable throughput of the proposed learning algorithm is very close to the optimal one, validating the effectiveness of the proposed game-theoretic solution in dynamic networks with varying active user sets.
研究不足
The study assumes no central controller and no information exchange among users, which may limit the applicability in scenarios where such features are present. Additionally, the dynamic nature of the active user set adds complexity to the system.
1：Experimental Design and Method Selection:
The study formulates a state-based spectrum access game and a robust spectrum access game to address the dynamic and incomplete information constraints. A distributed learning algorithm is proposed to achieve the pure strategy Nash equilibrium (NE) of the games.
2：Sample Selection and Data Sources:
Cognitive APs are randomly located in a 500m×500m square area, with M = 5 channels and bandwidth B = 6MHz. The noise power is σ = ?100 dBm, and the path loss factor is α =
3：List of Experimental Equipment and Materials:
Cognitive APs, geo-location spectrum database, channels with specified bandwidth and noise power.
4：Experimental Procedures and Operational Workflow:
The learning algorithm involves initialization, channel selection based on mixed strategies, channel access and transmission, and updating mixed strategies based on received payoffs.
5：Data Analysis Methods:
The performance is evaluated through simulation results showing the convergence behavior and throughput performance of the proposed algorithm compared to optimal solutions and Nash equilibria.
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