A semi-blind channel estimation algorithm based on subspace approach for orthogonal frequency division multiplexing（OFDM） systems over the frequency-selective channel is proposed. A linear preeoding is applied on ea...A semi-blind channel estimation algorithm based on subspace approach for orthogonal frequency division multiplexing（OFDM） systems over the frequency-selective channel is proposed. A linear preeoding is applied on each block before the IFFT operation and a low-rank structure is created in the received signal. Then subspace properties can be exploited to identify the channel up to a scalar ambiguity. The residual scalar ambiguities eliminated by inserting pilots into data stream. Simulation results illustrate the performance of the proposed semi-blind algorithm.展开更多
Based on propagator method, a fast 2-D Angle-Of-Arrival (AOA) algorithm is proPosed in this paper. The proposed algorithm does not need the Eigen-Value Decomposition (EVD) or Singular Value Decomposition (SVD) of the ...Based on propagator method, a fast 2-D Angle-Of-Arrival (AOA) algorithm is proPosed in this paper. The proposed algorithm does not need the Eigen-Value Decomposition (EVD) or Singular Value Decomposition (SVD) of the Sample Covariance Matrix (SCM), thus the fast algorithm has lower computational complexity with insignificant performance degradation when comparing with conventional subspace approaches. Furthermore, the proposed algorithm has no performance degradation. Finally, computer simulations verify the effectiveness of the proposed algorithm.展开更多
文摘A semi-blind channel estimation algorithm based on subspace approach for orthogonal frequency division multiplexing（OFDM） systems over the frequency-selective channel is proposed. A linear preeoding is applied on each block before the IFFT operation and a low-rank structure is created in the received signal. Then subspace properties can be exploited to identify the channel up to a scalar ambiguity. The residual scalar ambiguities eliminated by inserting pilots into data stream. Simulation results illustrate the performance of the proposed semi-blind algorithm.
基金Supported by the Foundation of National Key Laboratory.
文摘Based on propagator method, a fast 2-D Angle-Of-Arrival (AOA) algorithm is proPosed in this paper. The proposed algorithm does not need the Eigen-Value Decomposition (EVD) or Singular Value Decomposition (SVD) of the Sample Covariance Matrix (SCM), thus the fast algorithm has lower computational complexity with insignificant performance degradation when comparing with conventional subspace approaches. Furthermore, the proposed algorithm has no performance degradation. Finally, computer simulations verify the effectiveness of the proposed algorithm.
