In this paper, we study a RAN resource-slicing problem for energy-efficient communication in an orthogonal frequency division multiple access (OFDMA) based millimeter-wave (mmWave) downlink (DL) network consisting of enhanced mobile broadband (eMBB) and ultra-reliable low-latency communication (URLLC) services. Specifically, assuming a fixed set of predefined beams, we address an energy efficiency (EE) maximization problem to obtain the optimal beam selection, Resource Block (RB), and transmit power allocation policy to serve URLLC and eMBB users on the same physical radio resources. The problem is formulated as a mixed-integer non-linear fractional programming (MINLFP) problem considering minimum data rate and latency in packet delivery constraints. By leveraging the properties of fractional programming theory, we first transform the formulated non-convex optimization problem in fractional form into a tractable subtractive form. Subsequently, we solve the transformed problem using a two-loop iterative algorithm. The main resource-slicing problem is solved in the inner loop utilizing the difference of convex (DC) programming and successive convex approximation (SCA) techniques. Subsequently, the outer loop is solved using the Dinkelbach method to acquire an improved solution in every iteration until it converges. Our simulation results illustrate the performance gains of the proposed methodology with respect to baseline algorithms with the fixed and mixed resource grid models.

翻译：本文研究了基于正交频分多址（OFDMA）的毫米波（mmWave）下行链路（DL）网络中，面向增强移动宽带（eMBB）与超可靠低时延通信（URLLC）业务的高能效通信RAN资源切片问题。具体而言，在固定预定义波束集合的假设下，我们提出能效（EE）最大化问题，以获取最优波束选择、资源块（RB）及发射功率分配策略，从而实现URLLC与eMBB用户在相同物理无线资源上的服务复用。考虑最小数据速率与数据包传输时延约束，该问题被建模为混合整数非线性分式规划（MINLFP）问题。我们利用分式规划理论性质，首先将分式形式的非凸优化问题转化为易处理的减式形式，随后通过双循环迭代算法求解转化后的问题：内循环利用凸差（DC）规划与逐次凸近似（SCA）技术求解主资源切片问题，外循环采用Dinkelbach方法每轮迭代获取改进解直至收敛。仿真结果表明，与采用固定及混合资源网格模型的基线算法相比，所提方法在性能上具有显著增益。