摘要
Signal-to-Interference Ratio(SIR) is a very important metric of communication link quality. For wireless cellular systems, several control mechanisms, such as power control mechanisms, rate control mechanisms, and allocation of radio resource, are based on SIR estimation.In previous researches, most of researchers concentrated on WCDMA systems, in which pilot symbol is time-multiplexed with data symbol; the method developed in this case is not feasible for cdma2000 systems where pilot symbol is code-multiplexed with data symbol. This paper first develops the SIR estimators based on the reverse pilot channel and then derives the approximate analytic expression for its Mean Squared Error (MSE) function, the accuracy of which is validated through simulation. It is shown that the MSE of the new SIR estimator is significantly smaller than that of other widely used SIR estimators, especially in low SIR case. Finally, the estimate quality of the proposed method is further improved by long-termly averaging the sample interference.
Signal-to-interference Ratio(SIR) is a very important metric of communication link quality. For wireless cellular systems, several control mechanisms, such as power control mechanisms, rate control mechanisms, and allocation of radio resource, are based on SIR estimation. In previous researches, most of researchers concentrated on WCDMA systems, in which pilot symbol is time-multiplexed with data symbol; the method developed in this case is not feasible for cdma2000 systems where pilot symbol is code-multiplexed with data symbol. This paper first develops the SIR estimators based on the reverse pilot channel and then derives the approximate analytic expression for its Mean Squared Error (MSE) function, the accuracy of which is validated through simulation. It is shown that the MSE of the new SIR estimator is significantly smaller than that of other widely used SIR estimators, especially in low SIR case. Finally, the estimate quality of the proposed method is further improved by long-termly averaging the sample interference.
