基于离散功率空间的定步长认知无线网络功率控制算法

针对现有认知无线网络功率控制算法在离散功率空间内无法收敛的问题，提出一种定步长功率控制算法。在离散功率空间内，将认知用户的目标信干扰比 （signal to interference plus noise ratio，SINR）由具体的目标数值扩展为目标窗口。为了最大化系统容量，在满足系统约束条件的前提下，建立了滑动窗口机制。通过认知用户总干扰与干扰温度域上下限的比较，动态调整中值SINR，从而实现目标窗口的滑动。对于确定的目标窗口，采用定步长迭代算法进行发射功率的调整。仿真实验表明，算法达到了预期效果，并取得与最优算法相近的系统性能。

Fixed step power control algorithm for cognitive wireless networks based on the discrete power space

Aim at the problem that the existing power control algorithms for cognitive wireless networks can not converge in the discrete power space, this paper presents a fixed step power control algorithm. In the discrete power space, the target SINR of cognitive user is extended from a specific target value to a target window. In order to maximize the system capacity, it is established that the sliding window mechanism is under the premise of meeting the system constraints. The middle SINR is dynamically adjusted by the comparison between the total interference of the cognitive user and the interference temperature domain in order to achieve the target window to slide. For the specific target window, the fixed-step iterative algorithm is used for transmitting power adjustment. Simulation results show that the presented algorithm achieves the desired results and obtains the similar performance of the optimal algorithm.