In this work, we propose a globally optimal joint successive interference cancellation (SIC) ordering and power allocation (JSPA) algorithm for the sum-rate maximization problem in downlink multi-cell non-orthogonal multiple access (NOMA) systems. The proposed algorithm is based on the exploration of base stations (BSs) power consumption, and closed-form of optimal powers obtained for each cell. Although the optimal JSPA algorithm scales well with larger number of users, it is still exponential in the number of cells. For any suboptimal decoding order, we propose a low-complexity near-optimal joint rate and power allocation (JRPA) strategy in which the complete rate region of users is exploited. Furthermore, we design a near-optimal semi-centralized JSPA framework for a two-tier heterogeneous network such that it scales well with larger number of small-BSs and users. Numerical results show that JRPA highly outperforms the case that the users are enforced to achieve their channel capacity by imposing the well-known SIC necessary condition on power allocation. Moreover, the proposed semi-centralized JSPA framework significantly outperforms the fully distributed framework, where all the BSs operate in their maximum power budget. Therefore, the centralized JRPA and semi-centralized JSPA algorithms with near-to-optimal performance are good choices for larger number of cells and users.
翻译:在这项工作中,我们提出了全球最佳的联合连续取消干扰(SIC)订单和电力分配(JSPA)算法,用于在低端连接多细胞非垂直多功能接入系统(NOMA)系统下行的超速最大化问题;提议的算法基于对基站(BS)电耗的探索,以及每个单元获得的最佳权力的封闭形式;虽然JSPA最佳的算法规模与更多的用户相当,但在细胞数量上仍然成倍增长;对于任何不优化的分解顺序,我们建议采用低兼容性近最佳联合利率和电力分配(JRPA)战略,利用用户的完整比例区域;此外,我们设计了一个接近最佳的半集中化的JSPA框架,用于一个两层混合的网络,使其与更多的小型和用户相匹配; 数字结果显示,JRPA极优化的用户为达到其频道能力而被迫达到其频道能力,在分配权力分配上设置了众所周知的极好的条件;此外,拟议的半中央化的JPA框架大大超越了他们整个中央预算框架。