该文针对大规模MIMO FDD下行系统，联合考虑信道估计与数据传输两个阶段的资源分配问题，提出一种能效资源分配算法。该方法以最大化能效为目标，以导频时长、导频功率和数据功率为参量，在指定发射功率和频谱效率约束的条件下建立优化模型。由于目标函数无精确解析形式，借助确定性等价原理对其近似并求得闭合表达式。进而，利用分数规划将原分式形式目标函数等价转换为减式形式，再利用目标函数的下界将非凸优化问题逐步释放为相对容易求解的等效问题，最终获得一种3层迭代能效资源优化算法。仿真结果验证了所提算法的有效性，且具有较快的收敛速度。%An energy-efficient resource allocation method is provided for the downlink massive Multiple-Input Multiple-Output (MIMO) Frequency Division Duplexing (FDD) system, which jointly evaluates the channel estimation stage and data transmission stage. The optimization problem is established based on the Energy Efficiency (EE) maximization by adjusting the pilot duration, pilot power and data power under the constraint of total transmit energy and spectral efficiency requirement. Since the analytical expression of the involved objective function is intractable, a closed-form expression is deduced using deterministic equivalent approximation technology. Based on this, the original non-convex fractional optimization problem is transformed into an equivalent problem in subtractive form by the means of fraction programming. Then, a lower bound of the transformed objective function is employed, which induces a relatively easy-to-solve equivalent problem. Finally, a three-layer iterative algorithm is developed. Numerical results validate the effectiveness and relatively fast convergence speed of the proposed algorithm.
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