基于统计 CSI 的空中智能反射面辅助大规模 MIMO 系统传输优化方案

doi:10.11959/j.issn.2096-3750.2023.00349

摘要/Abstract

摘要： 智能反射面（IRS）被认为是下一代移动通信的核心技术，其在增强网络覆盖、频谱效率、能源效率和部署成本方面具有显著优势。空中智能反射面（AIRS）结合了空中平台的高移动性和智能反射面提供的优质链路特性，可以有效解决复杂通信场景中基站与用户之间易受障碍物阻挡的问题，从而增强网络覆盖。针对 AIRS 辅助的多用户大规模多输入多输出（MIMO）系统，研究了基站波束成形、AIRS 部署位置与相移设计的联合优化问题。在已知统计信道状态信息（CSI）的条件下，提出了一种基于块坐标下降法（BCD）的系统遍历和速率优化方案。首先，建立了一个联合优化基站端波束成形、AIRS 的部署位置与 AIRS 相移的复杂优化模型。其次，通过 BCD下降算法，将非凸优化问题解耦成三个易于处理的子问题。最后分别采用拉格朗日乘子法、松弛变量法和 RMSProp 梯度下降算法求解子问题。仿真结果表明，所提出的优化方案有效地提高了系统的遍历和速率，并且具有较好的收敛性。

关键词: 大规模 MIMO, 空中智能反射面, 统计信道状态信息, 位置优化, 波束成形

Abstract: The intelligent reflecting surface (IRS) is considered a core technology of next-generation mobile communication. It has significant advantages in enhancing network coverage, spectrum efficiency, energy efficiency, and deployment cost. The aerial intelligent reflecting surface (AIRS), which combines the high mobility of the air platform and the high-quality link characteristics provided by the intelligent reflecting surface, can effectively assist the transmission from the base station to the users in complex communication scenarios and enhance the network coverage. A joint optimization problem of the transmit beamforming, as well as the placement and passive beamforming for the AIRS was studied for AIRS assisted multi-user massive multiple input multiple output (MIMO) systems. Under the condition that the statistical channel state information (CSI) is known, an optimization scheme of system ergodic sum rate based on block coordinate descent (BCD) was proposed. Firstly, an optimization model was established by jointly optimizing the transmit beamforming at base station, the placement and the passive beamforming for AIRS. Secondly, the nonconvex optimization problem was decoupled into three subproblems that are easy to deal with by BCD descent algorithm. Finally, Lagrange multiplier method, relaxation variable method and RMSProp gradient descent algorithm were used to solve the subproblems respectively. The simulation results show that the proposed optimization scheme can effectively improve the ergodic sum rate of the system with good convergence properties.

Key words: Massive MIMO, Aerial intelligent reflecting surface, Statistical CSI, Location optimization, Beam forming

马露洁梁彦李飞. 基于统计 CSI 的空中智能反射面辅助大规模 MIMO 系统传输优化方案[J]. 物联网学报, doi: 10.11959/j.issn.2096-3750.2023.00349.

MA Lujie LIANG Yan LI Fei. The transmission optimization scheme of aerial intelligent reflecting surface-aided massive MIMO systems based on statistical CSI[J]. Chinese Journal on Internet of Things, doi: 10.11959/j.issn.2096-3750.2023.00349.

参考文献

[1] ZHANG Z Q, XIAO Y, MA Z, et al. 6G wireless networks: vision, requirements, architecture, and key
technologies[J]. IEEE Vehicular Technology Magazine, 2019, 14(3): 28-41.
[2] DI RENZO M, ZAPPONE A, DEBBAH M, et al. Smart radio environments empowered by reconfigurable
intelligent surfaces: how it works, state of research, and the road ahead[J]. IEEE Journal on Selected Areas in
Communications, 2020, 38(11): 2450-2525.
[3] BJRNSON E, WYMEERSCH H, MATTHIESEN B, et al. Reconfigurable intelligent surfaces: a signal
processing perspective with wireless applications[J]. IEEE Signal Processing Magazine, 2022, 39(2): 135-158.
[4] WU Q Q, ZHANG R. Intelligent reflecting surface enhanced wireless network via joint active and passive
beamforming[J]. IEEE Transactions on Wireless Communications, 2019, 18(11): 5394-5409.
[5] DAI J Y, TANG W K, CHEN M Z, et al. Wireless communications based on information metasurfaces[J]. EEE
Transactions on Microwave Theory and Techniques, 2021, 69(3): 1493-1510.
[6] TANG W K, DAI J Y, CHEN M A, et al. MIMO transmission through reconfigurable intelligent surface:
System design, analysis, and implementation[J]. IEEE Journal on Selected Areas in Communications, 2020,
38(11): 2683–269
[7] WU Q Q, ZHANG R. Towards smart and reconfigurable environment: intelligent reflecting surface aided
wireless network[J]. IEEE Communications Magazine, 2020, 58(1): 106-112.
[8] PRADHAN C D, LI A, SONG L Y, et al. Reconfigurable intelligent surface (RIS)-enhanced two-way OFDM
communications[J]. IEEE Transactions on Vehicular Technology, 2020, 69: 16270-16275.
[9] LIU P L, LI Y, CHENG W, et al. Intelligent reflecting surface aided NOMA for millimeter-wave massive
MIMO with lens antenna array[J]. IEEE Transactions on Vehicular Technology, 2021, 70(5): 4419-4434.
[10] YU X H, XU D F, SUN Y, et al. Robust and secure wireless communications via intelligent reflecting
surfaces[J]. IEEE Journal on Selected Areas in Communications, 2020, 38(11): 2637-2652.
[11] LU H Q, ZENG Y, JIN S, et al. Enabling panoramic full-angle reflection via aerial intelligent reflecting
surface[C]//Proceedings of 2020 IEEE International Conference on Communications Workshops (ICC
Workshops). Piscataway: IEEE Press, 2020: 1-6.
[12] LU H Q, ZENG Y, JIN S, et al. Aerial intelligent reflecting surface: joint placement and passive beamforming
design with 3D beam flattening[J]. IEEE Transactions on Wireless Communications, 2021, 20(7): 4128-4143.
[13]ODEYEMI K O, OWOLAWI P A, OLAKANMI O O. Reconfigurable intelligent surface-assisted HAPS
relaying communication networks for multiusers under AF protocol: a performance analysis[J]. IEEE Access,
2022, 10: 14857-14869.
[14] LI Y J, YIN C, DO-DUY T, et al. Aerial reconfigurable intelligent surface-enabled URLLC UAV systems[J].
IEEE Access, 2021, 9: 140248-140257.
[15] ZENG Y, ZHANG R, LIM T J. Wireless communications with unmanned aerial vehicles: opportunities and
challenges[J]. IEEE Communications Magazine, 2016, 54(5): 36-42.
[16] ALFATTANI S, JAAFAR W, HMAMOUCHE Y, et al. Aerial platforms with reconfigurable smart surfaces for
5G and beyond[J]. IEEE Communications Magazine, 2021, 59(1): 96-102.
[17] AL-HOURANI A, KANDEEPAN S, LARDNER. Optimal LAP altitude for maximum coverage[J]. IEEE
Wireless Communications Letters, 2014, 3(6): 569-572.
[18] MOHAMED E M, HASHIMA S, HATANO K. Energy aware multiarmed bandit for millimeter wave-based
UAV mounted RIS network[J]. IEEE Wireless Communications Letters, 2022, 11(6): 1293-1297.
[19] ABDALLA A S, MAROJEVIC V. DDPG learning for aerial RIS-assisted MU-MISO communications[C]//
2022 IEEE 33rd Annual International Symposium on Personal, Indoor and Mobile Radio Communications
(PIMRC). Piscataway: IEEE Press, 2022: 701-70.
[20] SHANG B D, BENTLEY E S, LIU L J. UAV swarm-enabled aerial reconfigurable intelligent surface: modeling,
analysis, and optimization[J]. IEEE Transactions on Communications, 2022, 99: 1-1.
[21] ZHOU T, XU K, XIA X C, et al. Achievable rate optimization for aerial intelligent reflecting surface-aided
cell-free massive MIMO system[J]. IEEE Access, 2020, 9: 3828-3837.
[22] MA Z F, AI B, HE R S, et al. Modeling and analysis of MIMO multipath channels with aerial intelligent
reflecting surface[J]. IEEE Journal on Selected Areas in Communications, 2022, 40(10): 3027-3040.
[23] ZHANG J Z, ZHANG Y, ZHONG C J, et al. Robust design for intelligent reflecting surfaces assisted MISO
systems[J]. IEEE Communications Letters, 2020, 24(10): 2353-2357.
[24] 薛继实,梁彦,李汀, 等.统计和瞬时 CSI 混合的 3D MIMO 预编码[J]. 信号处理, 2020, 36(02):283-289.
XUE J S, LIANG Y, LI T, et al. 3D MIMO precoding with mixed statistical and instantaneous CSI[J]. Journal of
Signal Processing, 2022, 36(02):283-289.
[25] TAHA A, ALRABEIAH M, ALKHATEEB A. Enabling large intelligent surfaces with compressive sensing
and deep learning[J]. IEEE Access, 2021, 9: 44304-44321.
[26] ZHENG B X, ZHANG R. Intelligent reflecting surface-enhanced OFDM: channel estimation and reflection
optimization[J]. IEEE Wireless Communications Letters, 2020, 9(4): 518-522.
[27] XU K Z, ZHANG J, YANG X, et al. On the sum-rate of RIS-assisted MIMO multiple-access channels over
spatially correlated rician fading[J]. IEEE Transactions on Communications, 2021, 69(12): 8228-8241.
[28] HAN Y, TANG W K, JIN S, et al. Large intelligent surface-assisted wireless communication exploiting
statistical CSI[J]. IEEE Transactions on Vehicular Technology, 2019, 68(8): 8238-8242.
[29] HU X L, WANG J W, ZHONG C J. Statistical CSI based design for intelligent reflecting surface assisted MISO
systems[J]. Science China Information Sciences, 2020, 63(12): 222303.
[30] RAZAVIYAYN M, HONG M Y, LUO Z Q. A unified convergence analysis of block successive minimization
methods for nonsmooth optimization[J]. Siam Journal on Optimization, 2013, 23(2): 1126-1153.
[31] ZHANG Q, JIN S, WONG K K, et al. Power scaling of uplink massive MIMO systems with arbitrary-rank
channel means[J]. IEEE Journal of Selected Topics in Signal Processing, 2014, 8(5): 966-981.
[32] SHEN K M, YU W. Fractional programming for communication systems—part I: power control and
beamforming[J]. IEEE Transactions on Signal Processing, 2018, 66(10): 2616-2630.
[33] CAO Y S, LV T J, NI W. Intelligent reflecting surface aided multi-user mmWave communications for coverage
enhancement[C]//Proceedings of 2020 IEEE 31st Annual International Symposium on Personal, Indoor and
Mobile Radio Communications. Piscataway: IEEE Press, 2020: 1-6.
[34] 曹智禹. 智能反射表面增强的多用户通信系统的优化设计[D]. 成都：电子科技大学, 2021.
CAO Z Y. Optimal design of reconfigurable intelligent surfaces enhanced multi-user communication systems[D].
Chengdu: University of Electronic Science and Technology of China, 2021.
[35] VIERING I, HOFSTETTER H, UTSCHICK W. Spatial long-term variations in urban , rural and indoor
environments[J]. Proc 5th Meeting of COST273, 2002: 1-10.