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Coping with the limited amount of available spectrum, time division duplexing (TDD) system is considered as an attractive duplexing method due to exploiting channel reciprocity as well as flexible resource management. The conventional scheduling scheme is based on the channel quality indicator (CQI) reported from the user equipment (UE) to estimate instantaneous data rates for the scheduling metric calculation. However, CQI is insufficient to reflect the state of the channel variation in terms of frequency and time. Based on the channel reciprocity of TDD systems, we utilize uplink sounding reference signal (SRS) to estimate downlink channel status. However the received SRS power is a result of uplink power control where power control effect should be compensated to estimate channel status in downlink scheduling. In order to solve this problem, we propose the SRS path loss estimation method based on the power headroom report. By using this scheme, the base station (BS) can obtain the compensated signal-to-interference-plus-noise-ratio (SINR) and determine the scheduling metric based on its calculated SINR instead of reported CQI from UE. Simulation results show that the proposed scheduling algorithm outperforms the conventional scheme in total throughput, whereas the fairness index experienced by the proposed algorithm is lesser than of the conventional scheme based on CQI.

To improve the performance of Single Carrier Frequency Division Multiple Access (SC-FDMA) system, a simple and effective noise estimation algorithm based on Sounding Reference Signal (SRS) is necessary. An improved noise estimation algorithm based on Discrete Fourier transform (DFT) is proposed for the disadvantage of the traditional DFT. In addition, the influence of signal leakage is effectively reduced by time-domain Hamming windowing operation to the improved noise estimation algorithm based on DFT. Simulation results show that the improved noise estimation algorithm based on DFT has an improvement of 4 dB compared with the traditional algorithm in low Signal-to-Noise Ratio (SNR) regions. Hamming windowing operation can effectively correct the disadvantage of the improved noise estimation algorithm based on DFT which has bad performance to get an improvement of 4 dB at least in high SNR regions.