Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: This letter considers multiple symbol differential detection for multiple-antenna systems over flat Ricean-fading channels when partial channel state information (CSI) is available at the transmitter. Using the maximum likelihood (ML) principle, and assuming perfect knowledge of the channel mean,  derive the optimal multiple symbol detection (MSD) rule for diagonal differential unitary space-time modulation (DUSTM). This rule is used to develop a sphere decoding bound intersection detector (SD-BID) with low complexity. A suboptimal MSD based decision feedback DD (DF-DD) algorithm is also derived. The simulation results show that our proposed MSD algorithms reduce the error floor of conventional differential detection and that the computational complexity of these new algorithms is reasonably low.
['Tao Cui', 'Chintha Tellambura']
I am writing a research paper on a idea On Multiple Symbol Detection for Diagonal DUSTM Over Ricean Channels
[{"from": "human", "value": "I am writing a research paper on a idea On Multiple Symbol Detection for Diagonal DUSTM Over Ricean Channels"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: This letter considers multiple symbol differential detection for multiple-antenna systems over flat Ricean-fading channels when partial channel state information (CSI) is available at the transmitter. Using the maximum likelihood (ML) principle, and assuming perfect knowledge of the channel mean,  derive the optimal multiple symbol detection (MSD) rule for diagonal differential unitary space-time modulation (DUSTM). This rule is used to develop a sphere decoding bound intersection detector (SD-BID) with low complexity. A suboptimal MSD based decision feedback DD (DF-DD) algorithm is also derived. The simulation results show that our proposed MSD algorithms reduce the error floor of conventional differential detection and that the computational complexity of these new algorithms is reasonably low."}]