Robust Secure Resource Allocation Algorithm for Heterogeneous Networks with Hardware Impairments
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摘要: 针对多蜂窝多用户异构网络中收发机处信号畸变、用户信息泄露和传输中断等问题，该文提出一种基于硬件损伤的异构网络鲁棒安全资源分配算法。考虑小蜂窝用户最小安全速率约束、小蜂窝基站最大发射功率约束和宏用户干扰功率约束，建立了基于有界信道不确定性的能效最大化资源分配模型。基于Dinkelbach法、最坏准则法和连续凸近似理论，将原非凸资源分配问题等价转换为凸优化问题，并利用拉格朗日对偶算法得到解析解。仿真结果表明，与现有算法相比，所提算法具有较好的能效和鲁棒性。Abstract: To solve the problems of signal distortion at the transceivers, information leakage and transmission interruption of users in multi-cell multi-user heterogeneous networks, a robust secure resource allocation algorithm is proposed with distortion noises. Considering the constraints of the minimum secure rate of each small-cell user, the maximum transmit power of each base station and the cross-tier interference power of each macro-cell user, an energy efficiency maximization-based resource allocation model is formulated under bounded channel uncertainties. The original non-convex optimization problem is converted into an equivalent convex one by using the Dinkelbach’s method, the worst-case method and the successive convex approximation method. And the analytical solution is obtained by using Lagrangian dual function method. Simulation results demonstrate that the proposed algorithm has better energy efficiency and robustness by comparing it with the existing algorithms.
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算法1 小蜂窝迭代能效资源分配算法 初始化系统参数：$ M $, $ N $, $ {U_n} $, $ {\bar h_{i,n}} $, $ {\bar g_{i,n}} $, $ h_{i,n}^{\text{E}} $, $ g_n^{\text{E}} $,$ {\bar G_{m,n}} $, $ {p_m} $,
$ {P_c} $, $ I_m^{{\text{th}}} $, $ R_{i,n}^{{\text{min}}} $, $ P_n^{\max } $, $ {\varepsilon _m} $,$ {\beta _{i,n}} $, $ {\alpha _{i,n}} $；定义辅助变量${\eta _{\rm{E}}}$；定义最
大迭代次数$ D $和收敛精度$ \varpi $；初始化外层迭代次数$ d = 0 $；
(1) While $\left| {\frac{ {\displaystyle\sum\limits_{n = 1}^N {\displaystyle\sum\limits_{i = 1}^{ {U_n} } { { {\hat R}_{i,n} }(d)} } } }{ {\displaystyle\sum\limits_{n = 1}^N {\displaystyle\sum\limits_{i = 1}^{ {U_n} } { {p_{i,n} }(d)} + {P_n}(d)} } } - {\eta _{\rm{E}}}(d - 1)} \right| > \varpi$和
$d \le D$，do(2) 初始化拉格朗日乘子及对应步长；定义内层最大迭代次数
$L$，初始化内层迭代次数$l = 0$；(3) 循环 (4) For $ m = 1:1:M $ (5) For $ n = 1:1:N $ (6) For $ i = 1:1:{U_n} $ (7) 根据式(42)计算最优发射功率$p_{i,n}^*$； (8) 根据式(44)计算${Z_n}$； (9) 根据式(45)—式(47)更新拉格朗日乘子${\mu _n}(l)$,
${\lambda _m}(l)$和${\varpi _{i,n}}(l)$；(10) End For (11) End For (12) End For (13) 更新$l = l + 1$； (14) Until收敛或$l = L$； (15) 更新
$d = d + 1$和${\eta _{\rm{E}}}(d) = \frac{ {\displaystyle\sum\limits_{n = 1}^N {\displaystyle\sum\limits_{i = 1}^{ {U_n} } { { {\hat R}_{i,n} }(d - 1)} } } }{ {\displaystyle\sum\limits_{n = 1}^N {\displaystyle\sum\limits_{i = 1}^{ {U_n} } { {p_{i,n} }(d - 1)} + {P_n}(d - 1)} } }$；(16) End While 
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