摘要
作为一种通过算法智能地控制信号反射来重构无线通信环境的新技术,智能反射面(IRS)近年来受到了广泛关注。与传统的中继系统相比,IRS辅助的中继系统可有效节约成本和能耗,并显著提高系统性能。然而,配备离散移相器的IRS会导致相位量化误差,从而降低接收机的接收性能。为了分析IRS相位量化误差导致的性能损失,该文基于弱大数定律和瑞利分布,在瑞利信道下,推导了关于移相器量化比特数的双IRS辅助放大转发中继网络的信噪比性能损失与可达速率的闭合表达式。此外,基于Taylor级数展开表达式,推导了其近似性能损失闭合表达式。仿真结果表明,系统的信噪比和可达速率性能损失随着量化比特数的增加而逐渐减小,而随着IRS相移元件数的增加而逐渐增大。当量化比特数为4时,系统的信噪比和可达速率性能损失分别小于0.06 dB和0.03 bit/(s·Hz)。
Objective Most existing research assumes that the Intelligent Reflecting Surface(IRS)is equipped with continuous phase shifters,which neglects the phase quantization error.However,in practice,IRS devices are typically equipped with discrete phase shifters due to hardware and cost constraints.Similar to the performance degradation caused by finite quantization bit shifters in directional modulation networks,discrete phase shifters in IRS systems introduce phase quantization errors,potentially affecting system performance.This paper analyzes the performance loss and approximate performance loss in a double IRS-aided amplify-and-forward relay network,focusing on Signal-to-Noise Ratio(SNR)and achievable rate under Rayleigh fading channels.The findings provide valuable guidance on selecting the appropriate number of quantization bit for IRS in practical applications.Methods Based on the weak law of large numbers,Euler’s formula,and Rayleigh distribution,closed-form expressions for the SNR performance loss and achievable rate of the discrete phase shifter IRS-aided amplify-and-forward relay network are derived.Additionally,corresponding approximate expressions for the performance loss are derived using the first-order Taylor series expansion.Results and Discussions The SNR performance loss at the destination is evaluated as a function of the number of IRS-1 elements(N),assuming that the number of IRS-2 elements(M)equals N(Fig.2).It is evident that,regardless of whether the scenario involves actual or approximate performance loss,the SNR performance loss decreases as the number of quantization bit(k)increases but increases as N grows.When k=1,the gap between the actual performance loss and the approximate performance loss widens with increasing N.This gap becomes negligible when k is greater than or equal to 2.Notably,when k=4,the SNR performance loss is less than 0.06 dB.Furthermore,both the SNR performance loss and approximate performance loss gradually decelerate as N increases towards a larger scale.The achievable rate at the destination is evaluated as a function of the N,where M equals N(Fig.3).It can be observed that,in all scenarios—whether there is no performance loss,with performance loss,or approximate performance loss—the achievable rate increases gradually as N increases.This is because both IRS-1 and IRS-2 provide greater performance gains as N grows.When k=1,the difference in achievable rate between the performance loss and approximate performance loss scenarios increases with N.As k increases,the achievable rate with performance loss and approximate performance loss converge towards the no-performance-loss scenario.For example,when N=1024,the performance loss in achievable rate is about 0.15 bit/(s·Hz)at k=2 and only 0.03 bit/(s·Hz)at k=3.The achievable rate is evaluated as a function of k(Fig.4).The performance loss in achievable rate increases with N and M.When k=3,the achievable rate with performance loss and approximate performance loss decrease by 0.04 bit/(s·Hz)compared to the no performance loss scenario.When k=1,the differences in achievable rate between the no performance loss,performance loss,and approximate performance loss scenarios grow with increasing N and M.Remarkably,the achievable rate for the system with N=1024 and M=128 outperforms that of N=128 and M=1024.This suggests that increasing N provides a more significant improvement in rate performance than increasing M.Conclusions This paper investigates a double IRS-assisted amplify-and-forward relay network and analyzes the system performance loss caused by phase quantization errors in IRS equipped with discrete phase shifters under Rayleigh fading channels.Using the weak law of large numbers,Euler’s formula,and Rayleigh distribution,closed-form expressions for SNR performance loss and achievable rate are derived.Approximate performance loss expressions are also derived based on a first-order Taylor series expansion.Simulation results show that the performance losses in SNR and achievable rate decrease with increasing quantization bit,but increase with the number of IRS elements.When the number of quantization bit is 4,the performance losses in SNR and achievable rate are less than 0.06 dB and 0.03 bit/(s·Hz),respectively,suggesting that the system performance loss is negligible when using 4-bit phase quantization shifters.
作者
董榕恩
谢中毅
马海波
赵飞龙
束锋
DONG Rongen;XIE Zhongyi;MA Haibo;ZHAO Feilong;SHU Feng(School of Information and Communication Engineering,Hainan University,Haikou 570228,China;Purple Mountain Laboratories,Nanjing 210094,China;China Mobile Group Hainan Co.,Ltd.,Haikou 571250,China)
出处
《电子与信息学报》
北大核心
2025年第1期138-146,共9页
Journal of Electronics & Information Technology
基金
国家自然科学基金(U22A2002,62071234)
海南省科技专项基金(ZDKJ2021022)
海南大学科研启动项目(KYQD(ZR)-21008)
海南大学信息技术协同创新中心项目(XTCX2022XXC07)。
关键词
智能反射面
放大转发中继
信噪比
可达速率
Intelligent Reflecting Surface(IRS)
Amplify-and-forward relay
Signal-to-Noise Ratio(SNR)
Achievable rate
