Research On RSRP Measurement Methods For OFDM Communication Systems

As one of the core measurement parameters in orthogonal frequency division multiplexing(OFDM)systems,reference signal received power(RSRP)is used to directly characterise the signal strength at receiver side and reflect the current channel quality information.However,the existing RSRP measurement techniques suffer from insufficient measurement accuracy and limited measurement scenarios.In particular,the traditional measurement techniques are based on the assumption of quasi-invariance in the frequency domain,which leads to RSRP inaccuracy in high sparsity factor scenarios,thus seriously impairing the accuracy of channel information acquisition.This thesis investigates the design and optimisation of RSRP measurement techniques for OFDM systems in different scenarios,so as to improve the accuracy,flexibility and robustness of RSRP measurements as much as possible with acceptable computational complexity.Firstly,this thesis introduces the time correlation method(TCM)and frequency correlation method(FCM)for RSRP measurement in OFDM systems with low sparsity factor scenarios,and analyses the performance of the algorithms from various aspects,including cumulative distribution function,mean square error(MSE)and computational complexity.Subsequently,the conventional FCM is improved by introducing the concept of step size,redesigning the core RSRP estimator.The conventional FCM is demonstrated to be a special case of the proposed FCM when the step size is equal to 2.The proposed FCM effectively improves the RSRP measurement accuracy in low sparsity factor scenarios without increasing the system time-frequency resource overhead,and achieves an effective conversion between the system computational and spectrum resources.Finally,theoretical analysis and conclusions are verified by simulation.Compared with conventional FCM and TCM,the average measurement accuracy of the proposed FCM with step size of 5 is improved by 0.6 d B and 0.8 d B,respectively.Secondly,to address the inaccuracy of RSRP measurement in high sparsity factor scenarios,an offset-compensated FCM(OC-FCM)is proposed by using the a priori information of the channel.Specifically,the assumption of quasi-invariance in the frequency domain is abandoned,based on which the offset closure expression is derived and the determinant operation is replaced by the real part taking operation in the core RSRP estimator.OC-FCM makes full use of the differences in channel frequency response at different reference signals,and effectively improves the measurement accuracy without adding additional time-frequency resource overhead.The simulation results show that OCFCM with step size of 5 improves the MSE performance by a minimum of 17.5% and a maximum of 31.2% in high sparsity scenarios compared to the conventional FCM.