: In this paper, we consider an uplink economy-efficient resource allocation in a multicellular virtual wireless network with a C-RAN architecture where a MNO interacts with a number of MVNOs with a predetermined business model. In each cell of this system, two types of
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: In this paper, we consider an uplink economy-efficient resource allocation in a multicellular virtual wireless network with a C-RAN architecture where a MNO interacts with a number of MVNOs with a predetermined business model. In each cell of this system, two types of multiple access technologies, namely OFDMA and Massive MIMO, are available for MVNO at two different prices. In this setup, we propose a multi access technology selection approach (MATSA) with the objective to reduce operating costs and maximize the profit of the MVNOs subject to a set of constraints, and formulate this resource allocation problem with the new utility function. Due to the existence of continuous and binary variables in the formulated optimization problem and also the interference between cells in data rate functions, this optimization problem will be non-convex with very high computational complexity. To tackle this problem, by applying the complementary geometric programming (CGP) and the successive convex approximation (SCA), an effective two-step iterative algorithm is developed to convert the optimization problem into two sub problems with the aim to find optimum technology selection and power consumption parameters for each user in two steps, respectively. The simulation results demonstrate that our proposed approach (MATSA) with novel utility function is more efficient than the traditional approach, in terms of increasing total EE and reducing total power consumption. The simulation results illustrate that the profit of the MVNOs is enhanced more than 13% compared to that of the traditional approach.
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