Revenue-Maximizing Resource Allocation for Multitenant Cell-Free Massive MIMO Networks

Abstract

Cell-free massive multiple-input--multiple-output (MIMO) (CF-mMIMO) is a distributed massive MIMO network architecture, which leads to a better ability to resist shadow fading than centralized massive MIMO. When network slicing is applied to CF-mMIMO networks in order to serve multiple tenants, the deployment flexibility of CF-mMIMO networks could be further improved. Nevertheless, how to effectively allocate resources in network slicing based CF-mMIMO networks is still a challenging problem to be tackled. In this article, we present a novel resource allocation scheme for network slicing based multi-tenant CF-mMIMO networks to maximize the infrastructure operator’s revenue while maintaining the quality of network services. Specifically, the resource allocation scheme is first formulated as an optimization problem, which is NP-hard and nonconvex. Then, the problem is decomposed into two subproblems. For the first subproblem, we propose a joint user clustering and power control coefficient allocation algorithm, which not only maintains fairness among users but also improves the access rate of CF-mMIMO networks. For the second subproblem, the interior-point method is adopted. In our article, extensive simulations are carried out to prove the effectiveness of the proposed resource allocation scheme. Our experimental results indicate that the proposed scheme leads to a lower outage probability and a higher infrastructure provider’s revenue than existing approaches.