密集低軌衛(wèi)星網(wǎng)絡(luò)輔助地面通信的魯棒波束賦形方法

鄭斌; 曾令昕; 黃輝; 王曉洪; 丁昌峰; 王金元

doi:10.11999/JEIT240732

密集低軌衛(wèi)星網(wǎng)絡(luò)輔助地面通信的魯棒波束賦形方法

doi: 10.11999/JEIT240732 cstr: 32379.14.JEIT240732

1.
中國(guó)星網(wǎng)網(wǎng)絡(luò)應(yīng)用有限公司重慶 401123
2.
南京郵電大學(xué)通信與信息工程學(xué)院南京 210003

基金項(xiàng)目: 重慶市自然科學(xué)聯(lián)合基金項(xiàng)目(CSTB2023NSCQ-LZX0121)，南京郵電大學(xué)引進(jìn)人才科研啟動(dòng)基金項(xiàng)目(自然科學(xué))(NY223024)，東南大學(xué)移動(dòng)通信全國(guó)重點(diǎn)實(shí)驗(yàn)室開(kāi)放研究基金資助課題(2024D11)，交通物聯(lián)網(wǎng)技術(shù)湖北省重點(diǎn)實(shí)驗(yàn)室開(kāi)放基金

詳細(xì)信息

作者簡(jiǎn)介:
鄭斌：男，高級(jí)工程師，研究方向?yàn)榛鶐酒?、衛(wèi)星通信算法

曾令昕：男，高級(jí)工程師，研究方向?yàn)樯漕l芯片、衛(wèi)星通信算法

黃輝：女，高級(jí)工程師，研究方向?yàn)樾l(wèi)星通信算法、數(shù)字信號(hào)處理與實(shí)現(xiàn)

王曉洪：女，高級(jí)工程師，研究方向?yàn)樾l(wèi)星通信、衛(wèi)星導(dǎo)航信號(hào)處理

丁昌峰：男，講師，研究方向?yàn)樾l(wèi)星通信、邊緣計(jì)算和通感一體化技術(shù)等

王金元：男，副教授，研究方向?yàn)榭梢?jiàn)光通信、無(wú)線通信資源優(yōu)化等

通訊作者:
丁昌峰　cfding@njupt.edu.cn

中圖分類號(hào): TN927.2
計(jì)量
- 文章訪問(wèn)數(shù): 314
- HTML全文瀏覽量: 112
- PDF下載量: 62
- 被引次數(shù): 0
出版歷程
- 收稿日期: 2024-08-26
- 修回日期: 2025-02-11
- 網(wǎng)絡(luò)出版日期: 2025-02-19
- 刊出日期: 2025-03-01

Robust Beamforming Method for Dense LEO Satellite Network Assisted Terrestrial Communication

1.
China Satellite Network Exploration Co., Ltd., Chongqing 401123, China
2.
School of Communications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210003, China

Funds: Chongqing Natural Science Joint Fund Project (CSTB2023NSCQ-LZX0121), The Natural Science Research Start-up Foundation of Recruiting Talents of Nanjing University of Posts and Telecommunications (NY223024). The Open Research Fundation of National Mobile Communications Research Laboratory, Southeast University (2024D11), The Open Research Fundation of Hubei Key Laboratory of Transportation Internet of Things, China

摘要

摘要: 面向密集低軌道衛(wèi)星網(wǎng)絡(luò)輔助的星地?zé)o線通信系統(tǒng)，該文提出一種基于非完美信道狀態(tài)信息的多低軌衛(wèi)星魯棒波束賦形方法來(lái)改善頻譜效率。具體地，在多低軌衛(wèi)星全頻復(fù)用場(chǎng)景下，提出了一個(gè)多衛(wèi)星下行通信系統(tǒng)和速率最大化問(wèn)題，并聯(lián)合考慮衛(wèi)星發(fā)射功率、衛(wèi)星與用戶關(guān)聯(lián)關(guān)系，以及饋線鏈路容量約束。為了求解該優(yōu)化問(wèn)題，原優(yōu)化問(wèn)題被分解成衛(wèi)星-用戶關(guān)聯(lián)和衛(wèi)星傳輸波束賦形兩個(gè)子問(wèn)題，然后使用加權(quán)最小均方誤差方法和連續(xù)凸近似方法對(duì)問(wèn)題進(jìn)行求解。仿真結(jié)果驗(yàn)證了即使在非理想信道條件下，該文所提出的多星頻率復(fù)用和魯棒波束賦形設(shè)計(jì)方法能有效提高系統(tǒng)吞吐量。
- 密集LEO衛(wèi)星 /
- MIMO /
- 魯棒波束賦形 /
- 頻率復(fù)用
Abstract: A robust beamforming method based on imperfect Channel State Information (CSI) is proposed for dense Low-Earth Orbit (LEO) satellite network-assisted terrestrial wireless communication systems to enhance spectral efficiency. Specifically, in scenarios where multiple LEO satellites use full frequency reuse, a multi-LEO satellite downlink sum rate maximization problem is formulated, considering constraints on satellite transmit power, satellite-User Terminal (UT) association, and satellite feeder link capacity. To solve the optimization problem, it is decomposed into two subproblems: satellite-UT association and satellite transmit beamforming. Weighted minimum mean-squared error and successive convex approximation methods are then employed to address the non-convex challenges. Simulation results confirm that the proposed multi-satellite full frequency reuse scheme and robust beamforming design effectively improve system throughput, even under non-ideal channel conditions. Objective As the LEO satellite constellation becomes denser, spectrum resources will become scarcer, and co-channel interference among satellites will intensify. Therefore, transmission methods with higher spectrum efficiency are needed. To mitigate the effects of severe satellite-terrestrial wireless channels and enhance system throughput, multi-beam beamforming and phased-array antennas are employed in LEO satellites to achieve higher antenna gain. However, most existing studies assume perfect knowledge of CSI, which is often impractical. Therefore, considering the complex satellite-terrestrial channel conditions and channel estimation errors, a robust beamforming method is preferable. Under dense satellite constellations, the increasing number of satellites and the presence of inter-satellite co-channel interference make the design of robust transmission methods for multi-LEO satellite networks essential. Thus, this paper aims to investigate the design of an efficient robust beamforming method for dense LEO satellite networks under given channel uncertainty. Methods To enable frequency reuse across multiple LEO satellites, this paper proposes a dense LEO satellite network architecture that incorporates a gateway or Geostationary Earth Orbit (GEO) satellite as the centralized controller. In this system architecture, multiple LEO satellites can reuse spectrum, thereby improving spectral efficiency. Additionally, a system sum-rate maximization problem is formulated, considering imperfect Angular-Of-Arrival (AoA) based CSI. The problem incorporates constraints on satellite-user association, multi-satellite downlink transmit beamforming, and satellite feeder link capacity. Results and Discussions The simulation results show that the system sum-rate increases with the satellite transmit power budget, as higher transmit power improves received signal quality (Fig. 3). Additionally, the proposed robust beamforming method significantly enhances the system sum-rate compared to existing methods (Fig. 3). Furthermore, the results indicate that the communication rate of the UT is constrained by satellite feeder link capacity, and higher feeder link capacity leads to an increase in the system sum-rate (Fig. 4). However, the rate of increase in the system sum-rate slows once the satellite feeder link capacity exceeds a certain threshold. The results also reveal that larger AoA uncertainty reduces the system sum-rate, highlighting the significant impact of AoA uncertainty on system performance (Fig. 5). Lastly, increasing the number of antennas effectively improves channel quality and further increases the system sum-rate (Fig. 6). Conclusions This paper investigates a robust beamforming method for dense LEO satellite networks and proposes a full frequency reuse scheme to enhance spectral efficiency and increase system throughput. Given the challenges in obtaining accurate CSI, an angular-information-based channel uncertainty model is adopted to reflect non-ideal channel conditions. A system sum-rate maximization problem is then formulated to evaluate system performance, considering satellite-UT association and satellite transmit beamforming. To address the non-convex optimization problem, the WMMSE and SCA methods are employed. Simulation results demonstrate that channel uncertainty significantly impacts system performance. When channel uncertainty is small, the performance gap between the proposed robust beamforming method and the ideal CSI case is minimal. Furthermore, the proposed multi-LEO satellite robust beamforming method outperforms other existing schemes.
- Dense LEO satellites /
- MIMO /
- Robust beamforming /
- Frequency reuse

HTML全文

圖 1 密集LEO衛(wèi)星輔助地面通信網(wǎng)絡(luò)模型

下載: 全尺寸圖片幻燈片

圖 2 衛(wèi)星和UT的幾何關(guān)系

下載: 全尺寸圖片幻燈片

圖 3 系統(tǒng)和速率與衛(wèi)星發(fā)射功率的關(guān)系

下載: 全尺寸圖片幻燈片

圖 4 系統(tǒng)和速率與衛(wèi)星發(fā)射功率以及回程鏈路容量的關(guān)系

下載: 全尺寸圖片幻燈片

圖 5 系統(tǒng)和速率與AoA不確定性$\varDelta $的關(guān)系

下載: 全尺寸圖片幻燈片

圖 6 系統(tǒng)和速率與衛(wèi)星天線數(shù)量的關(guān)系

下載: 全尺寸圖片幻燈片

1 求解問(wèn)題式(9)的迭代優(yōu)化算法

1：初始化:給定可行的波束賦形向量$\left\{ {{\boldsymbol{w}}_{s,i}^{\left( 0 \right)}} \right\}$和二進(jìn)制關(guān)聯(lián)值$\left\{ {a_{i,s}^{\left( 0 \right)}} \right\}$，設(shè)置容差$\varepsilon \gt 0$，迭代索引$n = 0$，最大迭代次數(shù)${N_{\max }}$。
2：repeat
3：根據(jù)式(10)，將不確定信道進(jìn)行均勻離散化；
4：給定$\left\{ {{\boldsymbol{w}}_{s,i}^{\left( n \right)}} \right\}$，更新$v_{s,i}^{{\text{opt}}}$, $ u_{s,i}^{{\text{opt}}} $和$e_{s,i}^{{\text{opt}}}$，得到式(14)中的$ {\tilde R_{s,i}} $；
5：給定$\left\{ {{\boldsymbol{w}}_{s,i}^{\left( n \right)}} \right\}$和$\left\{ {a_{i,s}^{\left( n \right)}} \right\}$，利用內(nèi)點(diǎn)法求解問(wèn)題式(15)得到$\left\{ {a_{i,s}^{\left( {n + 1} \right)}} \right\}$。
6：給定$\left\{ {a_{i,s}^{\left( {n + 1} \right)}} \right\}$，得到式(16)中的$ {\tilde R_{s,i}} $；
7：給定$\left\{ {{\boldsymbol{w}}_{s,i}^{\left( n \right)}} \right\}$和$\left\{ {a_{i,s}^{\left( {n + 1} \right)}} \right\}$，采用式(19)，得到${\tilde R_{s,i}}$的上界$\tilde R_{s,i}^{\mathrm{U}}$；
8：給定$\left\{ {{\boldsymbol{w}}_{s,i}^{\left( n \right)}} \right\}$和$\left\{ {a_{i,s}^{\left( {n + 1} \right)}} \right\}$，利用內(nèi)點(diǎn)法求解問(wèn)題式(20)得到$\left\{ {{\boldsymbol{w}}_{s,i}^{\left( {n + 1} \right)}} \right\}$。
9：設(shè)置$ n = n + 1 $。
10：Until：目標(biāo)函數(shù)式(9)收斂或者$n = {N_{\max }}$。

下載: 導(dǎo)出CSV

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