This paper proposes a subspace-based noise variance and Signal-to-Noise Ratio (SNR) estimation algorithm for Multi-Input Multi-Output (MIMO) wireless Orthogonal Frequency Division Multiplexing (OFDM) systems. The spec...This paper proposes a subspace-based noise variance and Signal-to-Noise Ratio (SNR) estimation algorithm for Multi-Input Multi-Output (MIMO) wireless Orthogonal Frequency Division Multiplexing (OFDM) systems. The special training sequences with the property of orthogonality and phase shift orthogonality are used in pilot tones to obtain the estimated channel correlation matrix. Partitioning the observation space into a delay subspace and a noise subspace, we achieve the measurement of noise variance and SNR. Simulation results show that the proposed estimator can obtain accurate and real-time measurements of the noise variance and SNR for various multipath fading channels, demonstrating its strong robustness against different channels.展开更多
SM (spatial multiplexing) can effectively increase the information rate in multiple input multiple output system. BLAST is the typical representation of SM, especially VBLAST, which has some simple de- tection algorit...SM (spatial multiplexing) can effectively increase the information rate in multiple input multiple output system. BLAST is the typical representation of SM, especially VBLAST, which has some simple de- tection algorithms such as ML, ZF-DFE and ML-DFE, etc. However, the existing algorithms cannot approach ML performance. This paper discusses the effect for detection performance by the correlation of channel ma- trix, proposes a new algorithm—HPML detection algorithm, which can approach ML performance with low complexity. In the new algorithm, we travel the first d layers, and use the DFE procedure for the remaining layers, then perform ML detection for all obtained signals. Simulation results show that HPML can approach ML performance when the traveling numbers are not less than half of the number of transmitting antennas, and the algorithm complexity is smaller than ML.展开更多
基金Supported by the National Natural Science Foundation of China(No.60496311)
文摘This paper proposes a subspace-based noise variance and Signal-to-Noise Ratio (SNR) estimation algorithm for Multi-Input Multi-Output (MIMO) wireless Orthogonal Frequency Division Multiplexing (OFDM) systems. The special training sequences with the property of orthogonality and phase shift orthogonality are used in pilot tones to obtain the estimated channel correlation matrix. Partitioning the observation space into a delay subspace and a noise subspace, we achieve the measurement of noise variance and SNR. Simulation results show that the proposed estimator can obtain accurate and real-time measurements of the noise variance and SNR for various multipath fading channels, demonstrating its strong robustness against different channels.
文摘SM (spatial multiplexing) can effectively increase the information rate in multiple input multiple output system. BLAST is the typical representation of SM, especially VBLAST, which has some simple de- tection algorithms such as ML, ZF-DFE and ML-DFE, etc. However, the existing algorithms cannot approach ML performance. This paper discusses the effect for detection performance by the correlation of channel ma- trix, proposes a new algorithm—HPML detection algorithm, which can approach ML performance with low complexity. In the new algorithm, we travel the first d layers, and use the DFE procedure for the remaining layers, then perform ML detection for all obtained signals. Simulation results show that HPML can approach ML performance when the traveling numbers are not less than half of the number of transmitting antennas, and the algorithm complexity is smaller than ML.
