Joint Access Point Selection and Interference Cancellation for Cell-Free Massive MIMO
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Cell Free Massive MIMO is a highly promising approach to enhance network capacity by moving a large number of distributed access points closer to mobile users while utilizing simple matched filtering and conjugate beamforming. Recent work on centralized implementation of this approach using minimum mean-squared-error (MMSE) receiver shows significant capacity increase, but at the cost of high computational complexity which may be impractical for beyond 5G systems. We propose a significantly lower complexity alternative where the central processing unit (CPU) exploits readily available knowledge of users' channel estimates to perform joint process of combining selected strongest AP signals for each user and canceling the sum of interfering users' estimates. We provide complexity and sum spectral efficiency (SE) analyses and illustrative examples to answer why this approach yields higher performances compared with the other alternatives. Extensive numerical results are then provided to confirm substantial capacity and complexity gains while outperforming MMSE using fewer APs.
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