We introduce maximum-SINR sparse-binary waveforms that modulate data information symbols from any finite alphabet and span the whole continuum of the available/deviceaccessible spectrum. We offer an optimal algorithm ...
详细信息
ISBN:
(纸本)9781509041176
We introduce maximum-SINR sparse-binary waveforms that modulate data information symbols from any finite alphabet and span the whole continuum of the available/deviceaccessible spectrum. We offer an optimal algorithm that designs the proposed waveforms by maximizing the signalto- interference-plus-noise ratio (SINR) at the output of the maximum-SINR linear receiver. In addition, we offer a suboptimal algorithm for the same problem with significantly reduced computational complexity. The post-filtering SINR improvements attained by the proposed waveforms in a single-input single-output (SISO) communication system with colored interference are presented analytically. Simulation studies compare the proposed waveforms with their conventional non-sparse counterparts and demonstrate their superior SINR performance.
We introduce maximum-SINR sparse-binary waveforms that modulate data information symbols from any finite alphabet and span the whole continuum of the available/device-accessible spectrum. We offer an optimal algorithm...
详细信息
ISBN:
(纸本)9781509041183
We introduce maximum-SINR sparse-binary waveforms that modulate data information symbols from any finite alphabet and span the whole continuum of the available/device-accessible spectrum. We offer an optimal algorithm that designs the proposed waveforms by maximizing the signal-to-interference-plus-noise ratio (SINR) at the output of the maximum-SINR linear receiver. In addition, we offer a suboptimal algorithm for the same problem with significantly reduced computational complexity. The post-filtering SINR improvements attained by the proposed waveforms in a single-input single-output (SISO) communication system with colored interference are presented analytically. Simulation studies compare the proposed waveforms with their conventional non-sparse counterparts and demonstrate their superior SINR performance.
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