面向物联网业务绿色接入的异构蜂窝网络优化

Heterogeneous cellular network optimization for green access of IoT traffics

物联网是未来赛博使能业务的重要支撑平台.蜂窝网络则被认为是广泛分布在部署区域中的物联网终端数据接入的主要渠道,尤其在广域覆盖方面具有难以替代的价值.在满足覆盖要求的条件下,降低蜂窝网络基站的下行发射功率在绿色通信方面具有重要的研究意义.由此提出了一种基于优化目标平滑近似和均方根传播策略的梯度下降算法,在满足物联网业务覆盖率的条件下最小化基站的总下行发射功率.首先,使用罚函数方法将复杂约束条件的异构蜂窝网络优化问题转化为简单约束形式的优化问题;其次,将不可导的目标函数通过平滑近似转化为可导形式,并给出其对天线下倾角和下行功率参数的梯度解析形式;最后,使用均方根传播梯度下降算法进行转化后的目标函数优化.仿真实验结果表明该算法可以在满足覆盖率指标的条件下最小化基站的总下行发射功率,与现有元启发算法和普通梯度下降算法相比,具有良好的收敛速度,并能更好地抑制优化过程中振荡.

The Internet of Things(IoT) has become an essential supporting platform for the present and future cyber-enabled services. Cellular networks is considered as the main channel of the data access for IoT terminals distributed in the region of interest, and they have an irreplaceable value, especially in wide-area coverage. Thus, it has a significant application value to reduce the downlink transmit power consumption of base stations under the restrictions of the coverage requirements for the green communication in heterogeneous cellular networks. A gradient descent algorithm was proposed based on smooth approximation and root mean square propagation. The algorithm could minimize the total downlink power consumption of base stations while satisfying the IoT service coverage. First, the penalty function method was used to simplify such an optimization problem with complicated constraints to a new one with simple constraints. Then, the non-derivative objective function was transformed by an approximation method into a derivable form. We also presented the close-form of the gradient of the objective function with respect to both the azimuths of the antennas installed in the base stations and the downlink transmit power levels related to these antennas. Finally, the gradient descent algorithm with root mean square propagation was used to execute the optimization of the newly approximated but smoothed version of the original objective function. Simulation experiments were conducted, and the results show that the proposed algorithm can significantly reduce the total power consumption of the downlink radio frequency transmit under the restrictions of the coverage ratio requirements in the region of interest. Furthermore, not only is the convergence speed of the proposed algorithm very fast, but also the oscillation phenomenon that occurs during the iterative procedure steps of the optimization is greatly suppressed by the proposed algorithm compared with the meta-heuristic algorithms and ordinary gradient descent method.