Pricing‐based power allocation in cloud radio access network with multiple access technology selection

• Published in: Transactions on emerging telecommunications technologies Vol. 34; no. 2
• Main Authors: Ansari, Ali Asghar, Eslami, Mohsen, Dehghani, Mohammad Javad
• Format: Journal Article
• Language: English
• Published: 01.02.2023
• ISSN: 2161-3915; 2161-3915
• DOI: 10.1002/ett.4687

In this article, we consider an uplink economy‐efficient resource allocation framework in a multicellular cloud radio access network (C‐RAN) architecture with network virtualization, where a mobile network operator (MNO) interacts with a number of mobile virtual network operators (MVNOs) with a predetermined business model. OFDMA and Massive MIMO multiple access technologies have been assumed to be available for each MVNO at two different prices. In this setup, we propose a multi‐access technology selection approach (MATSA) with the objective of maximizing delivered rate to end users, reducing operation costs and maximizing MVNOs' profit subject to a set of constraints, which leads to a nonconvex resource allocation problem with very high computational complexity. The utility function is defined as the difference between the total throughput and the utilization cost for each technology. To tackle this problem, we apply complementary geometric programming (CGP) and successive convex approximation (SCA), that results in a two‐step iterative solution. Simulation results demonstrate superiority of the proposed approach compared to a similar scenario with predetermined multi‐access technology, especially for large numbers of users. We consider uplink economy‐efficient power allocation and technology selection in a multi‐cell virtual wireless network with cloud radio access network (C‐RAN) architecture, where a mobile network operator (MNO) interacts with a number of mobile virtual network operators (MVNOs) with a predetermined business model. We use optimization techniques to solve the problem.