Sharing the spectrum among mobile network operators (MNOs) is a promising approach to improve the spectrum utilization and to increase the monetary income of MNOs. In this paper, we model a nonorthogonal spectrum sharing system for a large-scale cellular network where multiple seller MNOs lease their licensed sub-bands to several buyer MNOs. We first analyze the per-user expected rate and the per-MNO expected profit using stochastic geometry. Then, we formulate the joint problem of power control and licensed sub-band sharing to maximize the expected profit of all MNOs as a multiobjective optimization problem (MOOP) under the users' quality of service requirement and the nonnegative return on investment constraints. To transform the MOOP into a single objective form, we use a combination of the $\epsilon$-constraint and weighted sum methods. However, the transformed problem is nonconvex because of the presence of binary variables and nonconvex rate functions in the objective function and constraints. We address this problem by using a penalty function and approximating the nonconvex rate functions by a constrained stochastic successive convex approximation method. Finally, the numerical results show the correctness and performance of the proposed algorithm under various conditions.
翻译:移动网络操作员(MNOs)之间共享频谱是改善频谱利用和提高MNOs货币收入的一个很有希望的方法。 在本文中,我们为大型蜂窝网络模拟一个非横向频谱共享系统,多卖方MNOs将许可的分带租赁给多买方MNOs。我们首先分析用户预期费率和每MNO的预期利润,然后利用随机几何方法分析每用户预期费率和每MNO的预期利润。然后,我们提出权力控制和特许分带共享的共同问题,以最大限度地增加所有MNO的预期利润,作为用户服务质量要求和投资限制的非负差回报下的一个多目标优化问题(MOOP)。为了将MOOP转换成一个单一的客观形式,我们使用美元约束和加权总和方法的组合。然而,由于在客观功能和制约中存在二进变量和不连接率功能,我们用惩罚功能和对非convex率功能的预期利润(MOOP)作为多目标优化问题加以处理。我们用一种约束功能和对非convex率功能进行控制,用一种限制的功能,通过限制的数值排序后算方法显示各种结果。