在分碼多重存取通訊系統中，功率控制技術在解決near-far的問題，以及維持使用者達到個別可接受的訊雜比，甚至是延長系統的使用壽命上，都相當地重要。根據訊雜比與資料傳輸率的要求，系統可得知在此情形下所需的通訊品質，並進而期望使用功率控制技術來確保每一使用者，在移動路徑上每一處所接收到的通訊品質都能達到要求。然而，由於使用者的移動與傳輸環境的變化，通訊品質也隨之發生改變。例如接收訊號與同頻干擾強度，皆會受到通道的屏蔽效應影響而產生相當大的變動。因此，如何使用功率控制技術，來確保使用者隨時收到符合所要求的通訊品質，是相當重要且困難的課題。
一般可用載波雜訊比來表示蜂巢式行動通訊系統中的通訊品質。準確的載波雜訊比變化之預測，將有助於系統分析通訊品質的改變。已有論文提出，在有無多重存取干擾的情況下，用以預測使用者下一刻將接收到的載波雜訊比之變化程度的方法及模型[3]。本論文將利用此一方法預測下一刻載波雜訊比之可能變化情形，並引入通訊品質可靠度的概念，提出基於預測通訊品質變化之功率控制技術，確保使用者在下一時刻仍能在所限定的可靠度之下，符合所要求的通訊品質；進一步提出簡化之功率控制技術，並用電腦模擬兩者與一般不作任何通訊品質預測之功率控制技術作比較。

In code division multiple access (CDMA) system, power control technique is very important to solve the near-far problems, to maintain the acceptable signal to interference ratios (SIRs) for all users, and to extend the system lifetime.
The carrier-to-interference ratio (CIR) denotes the ratio of the desired signal power to the total co-channel interference (CCI) power. According to SIR requirement and data rate, system can know the user’s CIR requirement. Thus, CIR is generally used to represent the link quality in mobile cellular systems. Unfortunately, as the mobile moves, the propagation environment changes accordingly and so does the link performance. Shadowing effect causes the large variations in receiving signal strength and total co-channel interference ratio (CCI). Therefore, the CIR is also changed randomly as the mobile moves, and using power control technique to guarantee the mobile’s CIR preceding the requirement in all the way is very difficult.
Accurate prediction of the CIR variation profits analyzing the behavior of link quality. In [2], regardless of multiple access interference (MAI) from the serving cell, the spatial correlation of the CIR received by the moving mobile in the downlink environment can be modeled as a simple Gaussian-Markov stochastic model. Furthermore, [3] proposed a methodology to characterize the spatial correlation and link variation of the CIR involved with MAI.
In this research, by using the methodology of [3] to predict the next time CIR variation, we propose the CIR-prediction-based power control scheme to reserve enough power against the probable channel variation in advance, and accomplish the desired purpose that guaranteeing the link quality of a traveling mobile station with a required reliability in all the way. Moreover, we simplify our proposed scheme, and compare them with the general non-prediction-based power control schemes in the simulation.
This research can be extensively applied in adaptive power and rate allocation, downlink capacity analysis, performance simulations, and so on.

[1] G. L. Stuber, Principles of Mobile Communication, 2nd Edition, Boston, Kluwer Academic Publishers, 2001.
[2] Y. R. Tsai and J. W. Syu, “Spatial Correlation Models for Total Co-channel Interference and Carrier-to-Interference Ratio in Mobile Cellular Systems,” IEEE Globecom, vol. 5, pp. 3073-3077, 2004.
[3] Y. R. Tsai and J. W. Syu, “Stochastic models for the spatial correlation properties of total co-channel interference and the carrier-to-interference ratio in mobile communication systems,” M.S. thesis, Inst. of Comm. Engineering, Natl. Tsing Hua Univ., Hsinchu, Taiwan, Jul. 2004.
[4] S. Ariyavisitakul, “SIR-Based Power Control in a CDMA System,” IEEE Globecom, vol. 2, pp. 868-873, Dec. 1992.
[5] S. Ariyavisitakul and L. F. Chang, “Signal and interference statistics of A CDMA system with feedback power control,” IEEE Transactions on Communications, vol. 41, pp. 1626-1634, Nov. 1993.
[6] L. F. Chang and S. Ariyavisitakul, “Performance of a CDMA radio communications system with feed-back power control and multipath dispersion,” IEEE Globecom, vol. 2, pp.1017-1021, Dec. 1991.
[7] F. Ling and D. D. Falconer, “Combined orthogonal/convolutional coding for a digital cellular CDMA system,” IEEE VTC, vol. 1, pp. 63-66, May. 1992.
[8] M. Gudmundson, “Correlation Model for shadow fading in mobile radio systems,” Electronics Letters, vol. 27, pp. 2145-2146, Nov. 1991.
[9] L. F. Fenton, “The sum of log-normal probability distributions in scatter transmission systems,” IRE Trans. Comm. Syst., vol. COM-8, pp. 57–67, Mar. 1960.
[10] A. Safak, “Statistical analysis of the power sum of multiple correlated log-normal components,” IEEE Trans. Veh. Technol., vol. 42, no. 1, pp. 58–61, Feb. 1993.
[11] M. Rai and R. Tripathi, “Performance analysis of a multi access cellular communication network using base site transmitter power control approach,” IEEE ICPWC, pp. 527-532, Jan. 2005.
[12] I. H. Lee and D. Kim, “Power cost of mobility in cellular systems with closed-loop power control,” IEEE WCNC, vol. 2, pp. 1150-1154, Mar. 2005.
[13] S. Ghahramani, Fundamentals of Probability, 2nd Edition, Prentice Hall, 2000.