可旋转混合式智能反射面通信的能效优化研究

张广驰; 郭翾; 王璐遥; 崔苗; 付豪

doi:10.11999/JEIT260119

可旋转混合式智能反射面通信的能效优化研究

doi: 10.11999/JEIT260119 cstr: 32379.14.JEIT260119

张广驰¹,
郭翾¹,
王璐遥¹,
崔苗^1, ,,
付豪¹

广东工业大学信息工程学院广州 510006

基金项目: 广东省基础与应用基础研究基金(No. 2026A1515011208)，广东省科技计划(No.2022A0505050023)

详细信息

作者简介:
张广驰：男，教授，研究方向为无线通信与人工智能

郭翾：男，硕士研究生，研究方向为智能反射面

王璐遥：男，博士研究生，研究方向为无线通信与通感一体化

崔苗：女，副教授，研究方向为新一代无线通信技术

付豪：男，副教授，研究方向为通感一体化和无人机空地网络

通讯作者:
崔苗　cuimiao@gdut.edu.cn

中图分类号: TN929.5
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出版历程
- 修回日期: 2026-04-23
- 录用日期: 2026-04-23
- 网络出版日期: 2026-05-16

Research on Energy Efficiency Optimization of Rotatable Hybrid Intelligent Reflecting Surface Communication

Guangdong University of Technology, Guangzhou 510006, China

Funds: Guangdong Basic and Applied Basic Research Foundation (2026A1515011208), Guangdong Science and Technology Plan Project (2022A0505050023)

摘要

摘要: 智能反射面(RIS)作为第六代移动通信中的关键技术之一，主要通过智能重构无线信道来改善通信的服务质量。然而，传统固定式RIS在面对非正对信号时存在角度失配损耗和高电路能耗问题，难以满足绿色通信的低功耗要求。本文研究一种基于可旋转混合式智能反射面(H-RIS)辅助的通信系统，旨在通过联合优化基站发射功率、子阵列开关状态、物理旋转角度及电子相移以解决机械旋转与开关控制下的下行通信资源分配问题，实现频谱效率与系统功耗的有效折衷。针对该非凸的混合整数非线性规划(MINLP)优化问题，本文采用基于块坐标下降(BCD)的交替优化框架进行求解：首先，提出一种基于信道贡献度的排序策略以降低二元开关变量的搜索复杂度；其次，利用Dinkelbach算法将原分式目标函数转化为参数化减式形式进行功率优化；最后，通过黄金分割搜索法迭代求解旋转角度与电子相移。仿真结果表明，所提方案能根据用户位置灵活调整H-RIS的面板朝向与激活规模，在保证通信质量的同时，能够显著降低系统冗余功耗。
- 旋转混合式智能反射面 /
- 资源分配 /
- 能量效率 /
- 开关控制 /
- 块坐标下降法
Abstract: Objective With the evolution of 6G communication networks, reconfigurable intelligent surfaces (RIS) have emerged as a pivotal technology for reshaping wireless environments and enhancing spectral efficiency. However, conventional fixed RIS architectures face two critical challenges in practical deployment: the “angle mismatch” loss, where the effective aperture significantly diminishes when users are located at large angles from the RIS normal, and the “energy consumption bottleneck,” caused by the high cumulative power consumption of radio frequency (RF) circuits and static control elements in large-scale arrays. Existing research often treats mechanical rotation and element switching in isolation, lacking a unified framework to balance the trade-off between mechanical/circuit energy consumption and communication gain. To address these limitations, this paper investigates a rotatable and switchable hybrid RIS (H-RIS) assisted downlink communication system. The primary objective is to maximize the system’s energy efficiency (EE) by jointly optimizing the base station transmit power, subarray activation states, physical rotation angles, and electronic phase shifts. This approach aims to introduce mechanical rotation degrees of freedom to compensate for path loss and employ dynamic switching mechanisms to reduce redundant power consumption, thereby achieving sustainable green communication. Methods A joint optimization framework is established for the H-RIS aided single-user multiple-input single-output (MISO) system. The system model explicitly accounts for the dynamic power consumption induced by mechanical rotation and the static power consumption of active subarrays. The resulting optimization problem is formulated as a non-convex mixed-Integer non-linear programming (MINLP) problem, involving coupled binary variables (activation status) and continuous variables (power, angles, phases). To solve this challenging problem, a block coordinate descent (BCD)-based alternating optimization (AO) algorithm is proposed to decouple the variables into three sub-problems.Firstly, to tackle the exponential complexity caused by binary switching variables, a channel contribution-based ranking strategy is developed. By performing eigenvalue decomposition on the cascaded channel correlation matrix, the priority of each subarray is quantified, reducing the search space from exponential to linear.Secondly, for the power allocation sub-problem, the non-convex fractional objective function is transformed into a parametric subtractive form using the Dinkelbach algorithm, which is then solved via the interior-point method.Thirdly, for the physical rotation and electronic phase optimization, the problem is decomposed into single-variable sub-problems. A Golden Section Search algorithm is employed to iteratively find the optimal rotation angle and phase shift for each subarray within bounded constraints, ensuring the monotonic convergence of the objective function. Results and Discussions Extensive simulations are conducted to evaluate the performance of the proposed H-RIS scheme compared with benchmark schemes, including “Only-Rotation” (always on), “Only-Switching” (fixed angle), and “Conventional” (fixed and always on).The simulation results regarding the maximum transmit power P_max(Fig. 2 and Fig. 3) demonstrate that the proposed method achieves the highest energy efficiency across the entire power range. Specifically, in the low power regime, the proposed algorithm intelligently turns off redundant subarrays where the rate gain cannot offset the circuit power cost, thereby significantly outperforming the “Only-Rotation” scheme which suffers from high static power consumption.The impact of user distance is also analyzed (Fig. 4 and Fig. 5). Results indicate that the proposed scheme maintains high spectral efficiency comparable to the “Only-Rotation” scheme by dynamically adjusting the rotation angles to align with the Line-of-Sight (LoS) path, effectively compensating for the angle mismatch loss observed in the “Only-Switching” and “Conventional” schemes.Furthermore, the activation pattern of the subarray varies in a “U” shape with distance (Table 1), which allows for flexible adjustment of array size and orientation according to user-RIS geometry. Conclusions This paper proposes an energy-efficient transmission scheme for H-RIS aided communication systems by integrating mechanical rotation and dynamic switching capabilities. A low-complexity BCD-based algorithm is developed to jointly optimize the transceiver design. The results confirm that introducing mechanical rotation significantly mitigates the angle mismatch loss, while the proposed channel contribution-based switching strategy effectively eliminates redundant energy consumption. The proposed H-RIS architecture offers a superior trade-off between spectral efficiency and energy efficiency compared to traditional fixed RIS architectures, providing a viable solution for future green 6G networks.
- Reconfigurable Intelligent Surface (RIS) /
- Hybrid RIS (H-RIS) /
- Energy Efficiency /
- Switch Control /
- Alternating Optimization

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图 1 H-RIS辅助下行链路通信的系统

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图 2 不同算法的频谱效率随功率Pmax的变化图

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图 3 不同算法的能量效率随功率Pmax的变化图

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图 4 不同算法的频谱效率随用户水平距离的变化图

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图 5 不同算法的能量效率随用户水平距离的变化图

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1 基于BCD的能量效率最大化算法

初始化：输入信道矩阵 $ {\boldsymbol{H}}_{\boldsymbol{B}\boldsymbol{R}},{\boldsymbol{H}}_{\boldsymbol{R}\boldsymbol{U}} $，最大发射功率 $ {P}_{\text{max}} $，收敛容限 $ \epsilon $，随机初始化旋转角度 $ \boldsymbol{\theta } $ 和电子相移 $ {\boldsymbol{\varPhi }} $，令迭代计数 $ t=0 $
while $ \left\| {\eta }^{\left(t\right)}-{\eta }^{\left(t-1\right)}\right\| \gt $ 且 $ t\leq {I}_{max} $ do
• 基于当前物理旋转角度 $ {\phi }^{\left(t\right)} $，更新等效级联信道
• 根据式(12)计算子阵列信道贡献度权重，生成优先级排序索引 $ {S}_{sort} $
• for 候选激活数量 $ l =1 $ to $ {N}_{sub} $ do
• 激活 $ {S}_{\text{sort}} $ 中优先级最高的前$ l $个子阵列，其余关闭
• 构建参数化Dinkelbach子问题，利用内点法迭代求解当前最优发射功率 $ {\boldsymbol{w}}_{l} $
• 计算当前配置下的系统能效 $ {\eta }_{l} $
• end for
• 选取使能效 $ {\eta }_{l} $ 最大的激活状态 $ {\boldsymbol{a}}^{\left(t+1\right)} $ 和功率 $ {\boldsymbol{w}}^{\left(t+1\right)} $
• 固定 $ {\boldsymbol{a}}^{\left(t+1\right)} $ 和 $ {\boldsymbol{w}}^{\left(t+1\right)} $，利用黄金分割搜索法更新物理旋转角度 $ {\boldsymbol{\theta }}^{\left(t+1\right)} $
• 固定其他变量，利用黄金分割搜索法更新电子相移 $ {{\boldsymbol{\varPhi }}}^{\left(t+1\right)} $
• $ t \leftarrow t +1 $
end while
输出：最优波束赋形向量 $ {\boldsymbol{w}}^{} $，旋转角度 $ {\boldsymbol{\theta }}^{} $，电子相移 $ {{\boldsymbol{\varPhi }}}^{} $ 及开关状态 $ {\boldsymbol{a}}^{} $

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表 1 角度(绝对物理角度)与开关动态变化表

子阵列序号	初始角度(rad)	40 m	70 m	100 m	130 m	160 m
1	–1.1327	0.5411	0.4868	0.4655	0.4538	0.4468
2	–1.1327	0.5372	0.4828	0.4603	0.4503	0.4433
3	–1.1327	0.1784	0.4828	0.4603	0.4486	0.4416
4	–1.1327	0.3199	0.4849	0.4674	0.4576	0.4503
5	–1.1327	0.5353	0.4849	0.4603	0.4486	0.4416
6	–1.1327	0.5392	0.483	0.4653	0.4518	0.4433
7	–1.1327	0.2793	OFF	OFF	OFF	0.4451
8	–1.1327	0.3456	OFF	OFF	OFF	0.4433
9	–1.1327	0.5324	OFF	OFF	OFF	0.4416
10	–1.1327	0.5411	OFF	OFF	OFF	0.4433
11	–1.1327	0.2897	OFF	OFF	OFF	OFF
12	–1.1327	0.5353	OFF	OFF	OFF	OFF
13	–1.1327	0.543	OFF	OFF	OFF	OFF
14	–1.1327	OFF	OFF	OFF	OFF	OFF
15	–1.1327	OFF	OFF	OFF	OFF	OFF
16	–1.1327	OFF	OFF	OFF	OFF	OFF

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