Backscatter-NOMA Enabled Hybrid Multicast-Unicast Cooperative Transmission Scheme
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摘要: 针对协作中继通信系统频谱效率低和链路利用率低的问题,面向多播、单播业务共存场景,该文提出一种反向散射NOMA赋能的混合多播-单播协作传输方案。机会式选择一个多播用户作为协作节点,将其接收信号的一部分功率用于自身解码,剩余功率反向散射以增强其余用户的接收质量。为提升系统性能,通过联合优化基站功率分配系数、协作用户反向散射系数和协作节点选择变量,在保障多播服务质量的前提下,实现单播用户最小可达速率的最大化。为解决上述高度非凸联合优化问题,该文设计一种协作用户选择准则并提出了一种迭代算法来获取原问题的最优解。仿真结果验证了所提迭代算法的快速收敛性,相较于传统非协作传输方案,所提方案可将单播用户最小可达速率提升11.5%,有效保证多业务服务质量。Abstract: In order to address the low spectral efficiency and inefficient link utilization problem in cooperative relay communication system, a Backscatter-NOMA enabled hybrid multicast-unicast cooperative transmission scheme is proposed for the scenario of coexistence of multicast and unicast services. A multicast user is opportunistically selected as a cooperative node, which used a part of the power of the received signal for its own decoding, and backscatter the residual power to enhance the reception quality of other users. To improve system performance, the minimum achievable rate for unicast users is maximized by jointly optimizing the base station power allocation coefficients, cooperative user backscatter coefficients and cooperative node selection variables, while guaranteeing the quality of service for multicast. To solve the above highly non-convex joint optimization problem, a cooperative user selection criterion was designed and an iterative algorithm was proposed to obtain the optimal solution to the original problem. The simulation results verify the fast convergence of the proposed iterative algorithm, which can improve the minimum achievable rate of unicast users by 11.5% compared to the non-cooperative transmission scheme, and effectively ensure the quality of multi-service.
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1 基于连续凸近似的优化算法
1. 初始化:给定$n = {\text{1}}$, $\varDelta = 1$, ${{\varGamma }}_1^{\left( 0 \right)} = {{\varGamma }}_2^{\left( 0 \right)} = \cdots = {{\varGamma }}_N^{\left( 0 \right)} = 10$,
${{v}}_1^{\left( 0 \right)} = {{v}}_2^{\left( 0 \right)} = \cdots = {{v}}_N^{\left( 0 \right)} = 1.2$, $\lambda _1^{\left( 0 \right)} = \lambda _2^{\left( 0 \right)} = \cdots = \lambda _N^{\left( 0 \right)} = 1.5$,
$\tau = 0.001$, ${R^{{\text{(0)}}}} = 0$。2. while $\varDelta > \tau $ do 3. 求解问题P2,得到${R^{{\text{(}}n{\text{)}}}}$, ${{\varGamma }}_1^{\left( n \right)},{{\varGamma }}_2^{\left( n \right)} ,\cdots, {{\varGamma }}_N^{\left( n \right)}$和
${{v}}_1^{\left( n \right)},{{v}}_2^{\left( n \right)}, \cdots ,{{v}}_N^{\left( n \right)}$;4. $n \leftarrow n + 1$; 5. 更新$\varDelta = \left| {{R^{{\text{(}}n{\text{)}}}} - {R^{{\text{(}}n - 1{\text{)}}}}} \right|$; 6. 根据式(25)更新$\lambda _1^{\left( n \right)},\lambda _2^{\left( n \right)}, \cdots ,\lambda _N^{\left( n \right)}$; 7. end 8. 输出:最优速率${R^*}$。 -
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