2021/08/01 by Nam Yul Yu, Yu, Nam Yul
Engineering · #Advanced MIMO Systems Optimization #Advanced Wireless Communication Technologies #Energy Harvesting in Wireless Networks #FOS: Computer and information sciences #FOS: Electrical engineering #Information Theory (cs.IT) #Signal Processing (eess.SP) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2108.00361
openalex publication_date 2021/08/01 · openalex created_date 2022/07/25 · openalex updated_date 2026/07/28
In massive machine-type communications (mMTC), grant-free access is a key enabler for a massive number of users to be connected to a base station with low signaling overhead and low latency. In this paper, a two-stage genetic algorithm (GA) is proposed to design a new set of user-specific, non-orthogonal, unimodular sequences for uplink grant-free access. The first-stage GA is to find a subsampling index set for a partial unitary matrix that can be approximated to an equiangular tight frame. Then in the second-stage GA, we try to find a sequence to be masked to each column of the partial unitary matrix, in order to reduce the peak-to-average power ratio of the resulting columns for multicarrier transmission. Finally, the masked columns of the matrix are proposed as new non-orthogonal sequences for uplink grant-free access. Simulation results demonstrate that the non-orthogonal sequences designed by our two-stage GA exhibit excellent performance for compressed sensing based joint activity detection and channel estimation in uplink grant-free access. Compared to algebraic design, this GA-based design can present a set of good non-orthogonal sequences of arbitrary length, which provides more flexibility for uplink grant-free access in mMTC.