The orthogonal time frequency space(OTFS)modulation proposed in recent years is considered to have superior performance than orthogonal frequency division multiplexing(OFDM)for the doubly selective(DS)channels.The wor...The orthogonal time frequency space(OTFS)modulation proposed in recent years is considered to have superior performance than orthogonal frequency division multiplexing(OFDM)for the doubly selective(DS)channels.The works in the existing literature on OTFS mainly focus on the cases where the channels are underspread(i.e.,the product of the delay spread and the Doppler spread is less than 1).In the scenario of overspread DS channel,which has large delay spread and severe Doppler spread,such as underwater acoustic(UWA)channel,the channel model in delay-Doppler(DD)Domain derived by existing work is no longer applicable.In this paper,we derive a more generalized expression of the channel model in delay-Doppler domain,which allows the product of the delay spread and Doppler spread to be larger than1.The result shows that the existing channel model is just a special case of the one we proposed.Using the proposed channel matrix in DD domain,we build the OTFS detectors with the minimum mean square error(MMSE)and message passing(MP)algorithms on overspread doubly selective channel.Finally,simulation results are presented to verify the theoretical derivation and the effectiveness of the detectors.展开更多
A sparse channel estimation method is proposed for doubly selective channels in multiple- input multiple-output （ MIMO ） orthogonal frequency division multiplexing （ OFDM ） systems. Based on the basis expansion mo...A sparse channel estimation method is proposed for doubly selective channels in multiple- input multiple-output （ MIMO ） orthogonal frequency division multiplexing （ OFDM ） systems. Based on the basis expansion model （BEM） of the channel, the joint-sparsity of MIMO-OFDM channels is described. The sparse characteristics enable us to cast the channel estimation as a distributed compressed sensing （DCS） problem. Then, a low complexity DCS-based estimation scheme is designed. Compared with the conventional compressed channel estimators based on the compressed sensing （CS） theory, the DCS-based method has an improved efficiency because it reconstructs the MIMO channels jointly rather than addresses them separately. Furthermore, the group-sparse structure of each single channel is also depicted. To effectively use this additional structure of the sparsity pattern, the DCS algorithm is modified. The modified algorithm can further enhance the estimation performance. Simulation results demonstrate the superiority of our method over fast fading channels in MIMO-OFDM systems.展开更多
基金supported by National Natural Science Foundation of China(grant number 62071504)State Key Program of National Natural Science Foundation of China(grant numbers 62192712,62192711)+2 种基金Project of Science and Technology in Henan Province(grant numbers 222102210317,232102210078)Doctoral Research Foundation of Zhengzhou University of Light Industry(grant number 2021BSJJ030)Special Projects in Key Fields for General Universities of Guangdong Province(grant num 2021ZDZX1056)。
文摘The orthogonal time frequency space(OTFS)modulation proposed in recent years is considered to have superior performance than orthogonal frequency division multiplexing(OFDM)for the doubly selective(DS)channels.The works in the existing literature on OTFS mainly focus on the cases where the channels are underspread(i.e.,the product of the delay spread and the Doppler spread is less than 1).In the scenario of overspread DS channel,which has large delay spread and severe Doppler spread,such as underwater acoustic(UWA)channel,the channel model in delay-Doppler(DD)Domain derived by existing work is no longer applicable.In this paper,we derive a more generalized expression of the channel model in delay-Doppler domain,which allows the product of the delay spread and Doppler spread to be larger than1.The result shows that the existing channel model is just a special case of the one we proposed.Using the proposed channel matrix in DD domain,we build the OTFS detectors with the minimum mean square error(MMSE)and message passing(MP)algorithms on overspread doubly selective channel.Finally,simulation results are presented to verify the theoretical derivation and the effectiveness of the detectors.
基金Supported by the National Natural Science Foundation of China(61077022)
文摘A sparse channel estimation method is proposed for doubly selective channels in multiple- input multiple-output （ MIMO ） orthogonal frequency division multiplexing （ OFDM ） systems. Based on the basis expansion model （BEM） of the channel, the joint-sparsity of MIMO-OFDM channels is described. The sparse characteristics enable us to cast the channel estimation as a distributed compressed sensing （DCS） problem. Then, a low complexity DCS-based estimation scheme is designed. Compared with the conventional compressed channel estimators based on the compressed sensing （CS） theory, the DCS-based method has an improved efficiency because it reconstructs the MIMO channels jointly rather than addresses them separately. Furthermore, the group-sparse structure of each single channel is also depicted. To effectively use this additional structure of the sparsity pattern, the DCS algorithm is modified. The modified algorithm can further enhance the estimation performance. Simulation results demonstrate the superiority of our method over fast fading channels in MIMO-OFDM systems.
