Xie, W.; Tian, R.; Zhang, H. Iterative List Patterned Reed-Muller Projection Detection-Based Packetized Unsourced Massive Random Access. Sensors2023, 23, 6596.
Xie, W.; Tian, R.; Zhang, H. Iterative List Patterned Reed-Muller Projection Detection-Based Packetized Unsourced Massive Random Access. Sensors 2023, 23, 6596.
Xie, W.; Tian, R.; Zhang, H. Iterative List Patterned Reed-Muller Projection Detection-Based Packetized Unsourced Massive Random Access. Sensors2023, 23, 6596.
Xie, W.; Tian, R.; Zhang, H. Iterative List Patterned Reed-Muller Projection Detection-Based Packetized Unsourced Massive Random Access. Sensors 2023, 23, 6596.
Abstract
We consider a coded compressed sensing protocol for unsourced massive random access (URA) that concatenates a shared Patterned Reed-Muller (PRM) inner codebook to an outer error-correction code. In this paper, an iterative list PRM projection algorithm is proposed to supplant the signal detector associated with the inner PRM sequences. In particular, we first propose an enhanced paths-saving algorithm called list PRM projection detection for the single-user scenario that keeps multiple candidates for the first few layers to remedy the risk of spreading errors. On this basis, we further propose an iterative list PRM projection algorithm for the multi-user scenario. The vectors for PRM codes and channel coefficients are jointly detected in an iterative manner, which offers significant improvements regarding the convergence rate for signal recovery. Furthermore, the performances of the proposed algorithms are analyzed mathematically, and we verified that the theoretical simulations are consistent with the numerical simulations. Finally, we concatenate the inner PRM codes that employ the iterative list detection to two practical error-correction outer codes. According to the simulation results, we conclude that the packetized URA with the proposed iterative list projection detection works better than benchmarks in terms of the number of active users it can support in each slot and the amount of energy needed per bit to meet an expected error probability.
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