Maximum likelihood(ML) noncoherent block detection techniques are investigated for block-coded MPSK modulation in cooperative decode-and-forward relay systems over slow fading channels.A decision-directed iterative Vi...Maximum likelihood(ML) noncoherent block detection techniques are investigated for block-coded MPSK modulation in cooperative decode-and-forward relay systems over slow fading channels.A decision-directed iterative Viterbi algorithm(IVA) is derived for a suboptimal ML noncoherent detection.Simulation results show that the IVA can approach the error performances of the exhaustive detection method but at a lower complexity.展开更多
A low-complexity likelihood methodology is proposed for automatic modulation classification of orthogonal space-time block code(STBC)based multiple-input multiple-output(MIMO)systems.We exploit the zero-forcing equali...A low-complexity likelihood methodology is proposed for automatic modulation classification of orthogonal space-time block code(STBC)based multiple-input multiple-output(MIMO)systems.We exploit the zero-forcing equalization technique to modify the typical average likelihood ratio test(ALRT)function.The proposed ALRT function has a low computational complexity compared to existing ALRT functions for MIMO systems classification.The proposed approach is analyzed for blind channel scenarios when the receiver has imperfect channel state information(CSI).Performance analysis is carried out for scenarios with different numbers of antennas.Alamouti-STBC systems with 2×2 and 2×1 and space-time transmit diversity with a 4×4 transmit and receive antenna configuration are considered to verify the proposed approach.Some popular modulation schemes are used as the modulation test pool.Monte-Carlo simulations are performed to evaluate the proposed methodology,using the probability of correct classification as the criterion.Simulation results show that the proposed approach has high classification accuracy at low signal-to-noise ratios and exhibits robust behavior against high CSI estimation error variance.展开更多
基金supported by the National Natural Science Foundation of China(61302095,61401165)the Natural Science Foundation of Fujian Province of China(2014J01243,2014J05076,2015J01262)the Huaqiao University Science Foundation(13Y0384)
文摘Maximum likelihood(ML) noncoherent block detection techniques are investigated for block-coded MPSK modulation in cooperative decode-and-forward relay systems over slow fading channels.A decision-directed iterative Viterbi algorithm(IVA) is derived for a suboptimal ML noncoherent detection.Simulation results show that the IVA can approach the error performances of the exhaustive detection method but at a lower complexity.
基金Project supported by the National Natural Science Foundation of China(Nos.61172078,61571224,and 61571225)Six Talent Peaks Pro ject in Jiangsu Province,China.
文摘A low-complexity likelihood methodology is proposed for automatic modulation classification of orthogonal space-time block code(STBC)based multiple-input multiple-output(MIMO)systems.We exploit the zero-forcing equalization technique to modify the typical average likelihood ratio test(ALRT)function.The proposed ALRT function has a low computational complexity compared to existing ALRT functions for MIMO systems classification.The proposed approach is analyzed for blind channel scenarios when the receiver has imperfect channel state information(CSI).Performance analysis is carried out for scenarios with different numbers of antennas.Alamouti-STBC systems with 2×2 and 2×1 and space-time transmit diversity with a 4×4 transmit and receive antenna configuration are considered to verify the proposed approach.Some popular modulation schemes are used as the modulation test pool.Monte-Carlo simulations are performed to evaluate the proposed methodology,using the probability of correct classification as the criterion.Simulation results show that the proposed approach has high classification accuracy at low signal-to-noise ratios and exhibits robust behavior against high CSI estimation error variance.
