離散相移IRS輔助放大轉(zhuǎn)發(fā)中繼網(wǎng)絡(luò)的性能分析

董榕恩; 謝中毅; 馬海波; 趙飛龍; 束鋒

doi:10.11999/JEIT240236

離散相移IRS輔助放大轉(zhuǎn)發(fā)中繼網(wǎng)絡(luò)的性能分析

doi: 10.11999/JEIT240236

1.
海南大學(xué)信息與通信工程學(xué)院 ?？? 570228
2.
紫金山實驗室南京 210094
3.
中國移動通信集團(tuán)海南有限公司 ?？? 571250

基金項目: 國家自然科學(xué)基金(U22A2002, 62071234)，海南省科技專項基金(ZDKJ2021022)，海南大學(xué)科研啟動項目(KYQD(ZR)-21008)，海南大學(xué)信息技術(shù)協(xié)同創(chuàng)新中心項目(XTCX2022XXC07)

詳細(xì)信息

作者簡介:
董榕恩：女，博士后，研究方向為方向調(diào)制、IRS輔助的無線網(wǎng)絡(luò)

謝中毅：男，碩士生，研究方向為IRS輔助的無線通信

馬海波：男，高級工程師，研究方向為無線通信

趙飛龍：男，教授級高級工程師，研究方向為電磁波傳播及其應(yīng)用、移動通信、算力網(wǎng)絡(luò)等

束鋒：男，博士生導(dǎo)師，研究方向為智能無線通信、信息安全、大規(guī)模MIMO測向等

通訊作者:
束鋒　shufeng0101@163.com

中圖分類號: TN92
計量
- 文章訪問數(shù): 212
- HTML全文瀏覽量: 50
- PDF下載量: 42
- 被引次數(shù): 0
出版歷程
- 收稿日期: 2024-03-13
- 修回日期: 2024-07-17
- 網(wǎng)絡(luò)出版日期: 2024-08-27
- 刊出日期: 2025-01-31

Performance Analysis of Discrete-Phase-Shifter IRS-aided Amplify-and-Forward Relay Network

1.
School of Information and Communication Engineering, Hainan University, Haikou 570228, China
2.
Purple Mountain Laboratories, Nanjing 210094, China
3.
China Mobile Group Hainan Co., Ltd., Haikou 571250, China

Funds: The National Natural Science Foundation of China (U22A2002, 62071234), Hainan Province Science and Technology Special Fund (ZDKJ2021022), The Scientific Research Fund Project of Hainan University (KYQD(ZR)-21008), The Collaborative Innovation Center of Information Technology, Hainan University (XTCX2022XXC07)

摘要

摘要: 作為一種通過算法智能地控制信號反射來重構(gòu)無線通信環(huán)境的新技術(shù)，智能反射面(IRS)近年來受到了廣泛關(guān)注。與傳統(tǒng)的中繼系統(tǒng)相比，IRS輔助的中繼系統(tǒng)可有效節(jié)約成本和能耗，并顯著提高系統(tǒng)性能。然而，配備離散移相器的IRS會導(dǎo)致相位量化誤差，從而降低接收機(jī)的接收性能。為了分析IRS相位量化誤差導(dǎo)致的性能損失，該文基于弱大數(shù)定律和瑞利分布，在瑞利信道下，推導(dǎo)了關(guān)于移相器量化比特數(shù)的雙IRS輔助放大轉(zhuǎn)發(fā)中繼網(wǎng)絡(luò)的信噪比性能損失與可達(dá)速率的閉合表達(dá)式。此外，基于Taylor級數(shù)展開表達(dá)式，推導(dǎo)了其近似性能損失閉合表達(dá)式。仿真結(jié)果表明，系統(tǒng)的信噪比和可達(dá)速率性能損失隨著量化比特數(shù)的增加而逐漸減小，而隨著 IRS 相移元件數(shù)的增加而逐漸增大。當(dāng)量化比特數(shù)為4時，系統(tǒng)的信噪比和可達(dá)速率性能損失分別小于0.06 dB 和0.03 bit/(s·Hz)。
- 智能反射面 /
- 放大轉(zhuǎn)發(fā)中繼 /
- 信噪比 /
- 可達(dá)速率
Abstract: 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 = 1 024, 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 = 1 024 and M = 128 outperforms that of N = 128 and M = 1 024. 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.
- Intelligent Reflecting Surface (IRS) /
- Amplify-and-forward relay /
- Signal-to-Noise Ratio (SNR) /
- Achievable rate

HTML全文

圖 1 雙IRS輔助放大轉(zhuǎn)發(fā)中繼的系統(tǒng)模型圖

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圖 2 信噪比性能損失隨IRS-1陣元個數(shù)變化曲線圖

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圖 3 可達(dá)速率隨IRS-1陣元個數(shù)變化曲線圖

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圖 4 可達(dá)速率隨量化比特數(shù)變化曲線圖

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