Researcher On The Algorithms On Adaptive Step-Size Power Control

In CDMA mobile communication systems, there are several disadvantages such as multiple access interference, white Gaussian noise, multi-path, near-far effect, doppler frequency shifts and so on. All of those bad effects described above may affect the reliability of CDMA system or even lower the capacity of CDMA system.As one of the key technologies in mobile communications, power control technology not only adjusts transmit power of the mobile stations as well as the base stations but also compensates channel fading and counteracts near-far effect. More importantly, this kind of technology also makes all the users maintaining on the lowest standard, possibly reduces interference to the others, and finally increases system capacity. In a word, power control technology is the crucial technology which leads CDMA to practicality. With the improvement of performance parameters, power control algorithm has optimized a lot. Nowadays adaptive step-size power control algorithm has been widely researched by scientists in this field.Actually, power control process makes use of the transmit power change to offset channel random change process, or the change of the power control step to approach channel step random change process in the same time interval. This paper researches the adaptive power control based on Markov state, analyzes the fading characteristic of the channel. According to the fact that mobile moves at different speed with different channel fading, we simulate the fixed step power control, find out the best track step in different speed. Using TPC command bit patterns, we estimate the channel fading change, and show a new adaptive step-size power control algorithm, which selects the power control step size based on mobile speed and TPC command bit patterns. Then the proposed scheme is simulated and validated on fluctuating condition of receive power and power control error. Finally, we compare the proposed scheme with the adaptive power control algorithm based on Markov state, and find that the new algorithm is superior in terms of the performance.