Computing Task Offloading and Resource Allocation in UAV-Enabled Backscatter Communications
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摘要: 针对边缘计算网络中用户能量短缺问题，该文提出一种无人机(UAV)辅助的反向散射通信网络计算任务卸载和资源分配方案。首先，通过联合考虑飞行轨迹、用户的计算频率、任务卸载比例、无人机及用户的发射功率、反向散射时间分配以及主动通信时间分配，构建最小化无人机总能耗优化问题。其次，利用交替优化算法，将原非凸问题分解为两个子问题，并通过连续凸逼近方法将原问题转化为凸问题进行求解。仿真结果表明，所提算法使得无人机能耗显著减少，且具有良好的收敛性。Abstract: In order to alleviate problem of users’ energy shortage in edge computing networks, a computing task offloading and resource allocation scheme in Unmanned Aerial Vehicle (UAV)-assisted backscatter communication network is proposed. Firstly, a problem for minimizing the total energy consumption of UAV is formulated by the joint design of UAV trajectory, calculation frequency of users, task offloading ratio, the transmission power of the UAV and users, backscattering time allocation and active communication time allocation. Then, through alternate iteration method, the original non-convex problem is divided into two subproblems which are solved by the successive convex approximation method. Numerical results demonstrate that the proposed algorithm reduces effectively the UAV energy consumption and has good convergence performance.
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算法1 交替优化算法 输入：初始化$ \left( {{\boldsymbol{P}}\,{\text{,}}\,{\boldsymbol{q}}\,{\text{,}}\,{{\boldsymbol{P}}_k}\,{\text{,}}\,{\boldsymbol{f}}\,{\text{,}}\,\rho {\text{,}}\,\,\tau {\text{,}}\,{\boldsymbol{t}}} \right) $ for $i = 1:I$ 步骤1：固定$ \left\{ {{\boldsymbol{q}},{\boldsymbol{f}},{\boldsymbol{t}}} \right\} $时，求解凸优化问题； 步骤2：固定$ \left\{ {{\boldsymbol{P}},{{\boldsymbol{P}}_k},\rho ,\tau } \right\} $时，求解凸优化问题； 输出$ \left( {{\boldsymbol{P}}\,{\text{,}}\,{\boldsymbol{q}}\,{\text{,}}\,{{\boldsymbol{P}}_k}\,{\text{,}}\,{\boldsymbol{f}}\,{\text{,}}\,\rho {\text{,}}\,\,\tau {\text{,}}\,{\boldsymbol{t}}} \right) $。 
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