认知无线电中基于Stackelberg博弈的分布式功率分配算法

在underlay认知无线电场景中，为了让认知用户能随机地接入主用户正在使用的授权频段，且对主用户产生的干扰不高于主用户能够容忍的干扰温度门限，该文采用Stackelberg博弈机制进行认知用户的发射功率分配。将主用户作为模型中的leader，认知用户作为follower，认知用户使用主用户的授权频段时需以干扰功率为单位支付给主用户相应的费用，而主用户则可以通过调整价格，限制认知用户产生的总干扰功率不高于其所能容忍的干扰温度门限，以便获得最大收益。同时，不同认知用户间根据主用户制定的价格，进行非协作博弈。仿真结果表明，与集中式的最优功率分配算法相比，该文可通过简单的分布式功率分配算法获得与其相近的系统性能，且主用户与认知用户间只需进行少量的信息交互，这与需进行大量信息交互的集中式最优算法相比，具有较大的优势。

Stackelberg Game-based Distributed Power Allocation Algorithm in Cognitive Radios

In underlay cognitive radio scene, secondary users can opportunistically access the licensed spectrum under the constraint of interference temperature. In this paper, Stackelberg game is adopted for allocating power resource. In this model, the primary user acts as leader, secondary users act as followers. When using the licensed spectrum, secondary users must make payments to the primary user based on the induced interference power to the primary user. Meanwhile, the primary user aims at maximizing its own revenue through adjusting its price, under the constraint of interference temperature. Given specified price, the secondary users compete with each other using the non-cooperative game theory. Simulation shows that, compared with the centralized optimal power allocation algorithm, the proposed distributed power allocation algorithm not only can achieve close-to-optimal performance, but also needs much less communicating overhead than the optimal algorithm which is very beneficial.