A novel subspace method for precise carrier frequency offset estimation in multicarrier modulation scheme under multiuser environment

摘要

In recent years, the demand on data communication is rapidly increasing, and there is a need of spectrally efficient modulation scheme for massive data transmissions. Multicarrier modulation (MCM) is widely used in wireless systems to support high data rate multimedia services such as audio, video, image, and data. Multicarrier code division multiple access (MC-CDMA) is one of the MCM techniques which combines the best features of orthogonal frequency division multiplexing (OFDM) and code division multiple access (CDMA). The carrier frequency offset (CFO) due to oscillator instabilities or Doppler shifts greatly deteriorates the performance of MC-CDMA system. Hence, the subcarriers are no longer orthogonal and introduce intercarrier interference (ICI) at the receiver. The simultaneous CFO estimation and compensation in multiuser mobile environment are a challenging task which needs to be addressed for optimum performance. The blind CFO estimation such as maximum likelihood estimation (MLE) has limited estimation range which is less than half the subcarrier spacing. Multiple signal classification (MUSIC) is the spectral estimation-based subspace method suited for simultaneous CFO estimation in the multiuser environment. MUSIC offers precise CFO estimation only for the well-spaced CFOs and fails to discriminate the strictly spaced CFOs. Hence, a novel subspace method is proposed in this paper to improve the estimation accuracy for closely spaced CFOs with the reduced computational complexity. Simulation results show that the proposed enhanced root MUSIC estimation outperforms MLE and MUSIC in terms of estimation accuracy, bit error rate (BER), and ICI power.