Transmitter Filtering-aided Sparse Activity Detection for TDD-based Random Access

We investigate active user detection (AUD) for time-division duplexing (TDD)-based random access using transmitter filtering (TF). The main purpose of TF is to reduce the delay spread in a frequency-selective channel (channel shortening), resulting in the sparseness of the effective channel. In particular, the effective channel after zero-forcing (ZF)-based TF can be regarded as a one-tap channel, enhancing the sparsity in a channel. Thus, we propose a compressed-sensing-based AUD making full use of the feature of ZF-based TF. We further introduce an approximated received signal model in which the number of unknown variables is reduced compared to the original formulation. Simulation results demonstrate the superiority of the proposed method over the conventional methods.