OFDMA based Massive Grant-free Transmission in the Presence of Timing Offset

Gangle Sun, Yining Li, Xinping Yi, Wenjin Wang, Xiqi Gao, Lei Wang

Abstract: In the massive grant-free orthogonal frequency division multiple access (OFDMA), the timing offsets between users impose new challenges on joint active user detection (AUD) and channel estimation (CE) for the subsequent data recovery. In the asynchronous OFDMA, the timing offset effects can be modeled as the phase-shifting on the pilot matrix. As such, by constructing the measurement matrix with timing offsets, the joint estimation problem can be formulated as a generalized multiple measurement vector (MMV) recovery problem with structured sparsity. However, such a structured sparsity cannot be tackled by the existing compressed sensing (CS) techniques. To address this issue, we develop an efficient structured generalized approximate message passing (S-GAMP) algorithm, which includes the parallel AMP-MMV algorithm as a particular case. Simulation results confirm the superiority of the proposed algorithm in grant-free OFDMA in the presence of timing offset.