Improving sum-rate of cell-free massive MIMO with expanded compute-and-forward

J Zhang, J Zhang, DWK Ng, S Jin… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
J Zhang, J Zhang, DWK Ng, S Jin, B Ai
IEEE Transactions on Signal Processing, 2021ieeexplore.ieee.org
Cell-free massive multiple-input multiple-output (MIMO) employs a large number of
distributed access points (APs) to serve a small number of user equipments (UEs) via the
same time/frequency resource. Due to the strong macro diversity gain, cell-free massive
MIMO can considerably improve the achievable sum-rate compared to conventional cellular
massive MIMO. However, the performance of cell-free massive MIMO is upper limited by
inter-user interference (IUI) when employing simple maximum ratio combining (MRC) at …
Cell-free massive multiple-input multiple-output (MIMO) employs a large number of distributed access points (APs) to serve a small number of user equipments (UEs) via the same time/frequency resource. Due to the strong macro diversity gain, cell-free massive MIMO can considerably improve the achievable sum-rate compared to conventional cellular massive MIMO. However, the performance of cell-free massive MIMO is upper limited by inter-user interference (IUI) when employing simple maximum ratio combining (MRC) at receivers. To harness IUI, the expanded compute-and-forward (ECF) framework is adopted. In particular, we propose power control algorithms for the parallel computation and successive computation in the ECF framework, respectively, to exploit the performance gain and then improve the system performance. Furthermore, we propose an AP selection scheme and the application of different decoding orders for the successive computation. Finally, numerical results demonstrate that ECF frameworks outperform the conventional CF and MRC frameworks in terms of achievable sum-rate.
ieeexplore.ieee.org
以上显示的是最相近的搜索结果。 查看全部搜索结果