Abstract:
In this article, we propose a probabilistic K-repetition scheme for grant-free random access (GFRA) in the uplink of a cell-free massive MIMO network. The proposed appr...Show MoreMetadata
Abstract:
In this article, we propose a probabilistic K-repetition scheme for grant-free random access (GFRA) in the uplink of a cell-free massive MIMO network. The proposed approach allows for configuring the number of repetitions to maximize system reliability, distinguishing it from the conventional K-repetition strategy. The performance of the proposed approach is evaluated using analytical metrics that consider, first, the effects of a user activity detection (AUD) strategy tailored for the proposed probabilistic K-repetition algorithm, second, the utilization of a conjectured minimum mean square error (MMSE) channel estimation process that incorporates the activity coefficients from the K-repetition-assisted AUD process and, third, the implementation of both linear and successive interference cancellation (SIC)-assisted payload data decoding techniques. Extensive simulation results clearly demonstrate the superiority of the proposed probabilistic K-repetition scheme compared to the conventional K-repetition strategy, particularly when employing SIC-based decoding techniques and appropriately configuring the optimal number of repetitions per frame according to the specific scenario under evaluation.
Published in: IEEE Transactions on Vehicular Technology ( Volume: 73, Issue: 3, March 2024)