Optimal sampling structure for asynchronous multi-access channels

A sensitive receiver operation in multi-access reception is to detect the presence of training signals and identify sources from which the signals are sent, with a certain physical delay and center frequency. This is typically a sequential search, where the receiver tests the presence of specific signals and then acquires synchronization parameters (delays, Dopplers), for each component. In this paper, we develop an optimal compressive multichannel sampling (CMS) architecture, the output samples of which are fed to the proposed Sparsity Regularized (SR) Generalized Likelihood Ratio Test (GLRT). It is shown that SR-GLRT using the optimal sampling scheme exhibits better performance than conventional compressed sensing structure, and furthermore effectively scales down the storage requirement and complexity with greater flexibility than conventional architectures.