不完美信道狀態(tài)信息下的多輸入單輸出共生無(wú)線電系統(tǒng)資源分配算法

徐勇軍; 王名揚(yáng); 田秦語(yǔ); 張海波; 薛青

doi:10.11999/JEIT231366

不完美信道狀態(tài)信息下的多輸入單輸出共生無(wú)線電系統(tǒng)資源分配算法

doi: 10.11999/JEIT231366 cstr: 32379.14.JEIT231366

重慶郵電大學(xué)通信與信息工程學(xué)院重慶 400065

基金項(xiàng)目: 國(guó)家自然科學(xué)基金(U23A20279, 62271094)，重慶市自然科學(xué)基金重點(diǎn)項(xiàng)目(CSTB2022NSCQ-LZX0009, CSTB2023NSCQ-LZX0079)，重慶市教委科技重點(diǎn)項(xiàng)目(KJZD-K202200601)，重慶郵電大學(xué)高等科學(xué)研究院項(xiàng)目(E011A2022324)

詳細(xì)信息

作者簡(jiǎn)介:
徐勇軍：男，教授，博士生導(dǎo)師，研究方向?yàn)榉聪蛏⑸渫ㄐ拧⒅悄芊瓷涿?、資源分配等

王名揚(yáng)：女，碩士生，研究方向?yàn)楣采鸁o(wú)線電、資源分配等

田秦語(yǔ)：男，碩士生，研究方向?yàn)橹悄芊瓷涿?、共生無(wú)線電等

張海波：男，副教授，研究方向?yàn)闊o(wú)線資源管理等

薛青：女，講師，研究方向?yàn)楹撩撞ㄍㄐ诺?/p>

通訊作者:
徐勇軍　xuyj@cqupt.edu.cn

1¹⁾ 在不完美CSI下，由于共生系統(tǒng)的優(yōu)化，主次系統(tǒng)中都存在優(yōu)化變量和不完美CSI，同時(shí)需要保證每類用戶的最低速率，因此問(wèn)題求解難度較大。
中圖分類號(hào): TN929.5
計(jì)量
- 文章訪問(wèn)數(shù): 346
- HTML全文瀏覽量: 128
- PDF下載量: 83
- 被引次數(shù): 0
出版歷程
- 收稿日期: 2023-12-11
- 修回日期: 2024-11-22
- 網(wǎng)絡(luò)出版日期: 2024-11-28
- 刊出日期: 2024-12-01

Resource Allocation Algorithm for Multiple-Input Single-Output Symbiotic Radio with Imperfect Channel State Information

School of Communications and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China

Funds: The National Natural Science Foundation of China (U23A20279, 62271094), The Key Fund of Natural Science Foundation of Chongqing (CSTB2022NSCQ-LZX0009, CSTB2023NSCQ-LZX0079), The Scientific and Technological Research Program of Chongqing Municipal Education Commission (KJZD-K202200601), The Institute for Advanced Sciences, Chongqing University of Posts and Telecommunication (E011A2022324)

摘要

摘要: 針對(duì)信道估計(jì)誤差會(huì)導(dǎo)致傳統(tǒng)最優(yōu)資源分配算法失效的問(wèn)題，該文提出一種基于不完美信道狀態(tài)信息(CSI)的多輸入單輸出(MISO)共生無(wú)線電系統(tǒng)魯棒資源分配算法。考慮每個(gè)用戶最小吞吐量約束、傳輸時(shí)間約束、基站最大發(fā)射功率約束和用戶反射系數(shù)約束，基于有界信道不確定性模型，建立了一個(gè)傳輸時(shí)間、波束成形向量和反射系數(shù)聯(lián)合優(yōu)化的魯棒吞吐量最大化資源分配問(wèn)題。利用拉格朗日對(duì)偶、變量替換和交替優(yōu)化方法將原問(wèn)題轉(zhuǎn)換成凸優(yōu)化問(wèn)題求解。仿真結(jié)果表明，與傳統(tǒng)非共生資源分配算法相比，所提算法的吞吐量提升11.7%，中斷概率減小5.31%。
- 共生無(wú)線電 /
- 魯棒資源分配 /
- 吞吐量最大化
Abstract: To overcome the effect of channel estimation errors on the ineffectiveness of conventional optimal resource allocation algorithms, a robust resource allocation algorithm with imperfect Channel State Information(CSI) is proposed in Multiple-Input Single-Output(MISO) symbiotic radio systems. Considering the constraints of the minimum throughput of users, transmission time, maximum transmit power of the base station, and the reflection coefficients of users, based on bounded channel uncertainties, a robust throughput-maximization resource allocation problem is formulated by jointly optimizing transmission time, beamforming vectors, and reflection coefficients. The original problem is transformed into a convex problem by applying the Lagrange dual theory, the variable substitution, and the alternating optimizing methods. Simulation results verified that the throughput of the proposed algorithm is improved by 11.7% and the outage probability is reduced by 5.31% by comparing it with the non-robust resource allocation algorithm.
- Symbiotic Radio(SR) /
- Robust resource allocation /
- Throughput maximization

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圖 1 系統(tǒng)模型

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圖 2 算法流程圖

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圖 3 本文算法的收斂性能

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圖 4 不同算法系統(tǒng)總吞吐量與天線數(shù)量的關(guān)系

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圖 5 不同算法系統(tǒng)總吞吐量與反向散射設(shè)備數(shù)量的關(guān)系

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圖 6 不同算法下系統(tǒng)總吞吐量與估計(jì)誤差上界的關(guān)系

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圖 7 不同算法下系統(tǒng)總吞吐量與最大發(fā)射功率門限的關(guān)系

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圖 8 不同算法下的中斷概率性能對(duì)比

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表 1 相關(guān)工作總結(jié)

文獻(xiàn)	網(wǎng)絡(luò)類型	用戶數(shù)	CSI	優(yōu)化變量			目標(biāo)函數(shù)
文獻(xiàn)	網(wǎng)絡(luò)類型	用戶數(shù)	CSI	傳輸時(shí)間	反射系數(shù)	波束成形	目標(biāo)函數(shù)
[5]	SISO SR	單用戶	完美	×	√	×	Max:加權(quán)和速率
[6]	MISO SR	單用戶	完美	×	×	√	Min:傳輸功率,Max:能效
[7]	MISO SR	多用戶	完美	√	√	×	Max:能效
[8]	MISO NOMA-TDMA SR	多用戶	完美	√	√	×	Max:最小吞吐量
[9]	MISO 全雙工+NOMA-TDMA SR	多用戶	完美	√	√	×	Max:最小吞吐量
[10]	SISO RIS+SR	多用戶	完美	×	√	×	Max:能效
[11]	MISO RIS+SR	單用戶	完美	×	√	√	Max:能效
[12]	MISO RIS+SR+NOMA	多用戶	完美	√	×	×	Max:資源效率
[13]	SISO RIS+UAV+SR	單用戶	完美	×	×	×	Min:加權(quán)和誤碼率
[14]	MISO SR	多用戶	完美	×	√	×	Min: SNR
[15]	MISO SR+竊聽(tīng)者	單用戶	完美	×	√	×	Max:保密速率
[16]	MIMO RIS+SR	單用戶	完美	×	√	×	Min:傳輸功率
[17]	MISO RIS+SR	單用戶	不完美	×	×	√	Min:傳輸功率
[18]	MISO RIS+SR	單用戶	不完美	×	√	√	Min:傳輸功率
本文	MISO SR	多用戶	不完美	√	√	√	Max:吞吐量

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1 基于迭代的魯棒吞吐量最大化算法

初始化系統(tǒng)參數(shù)：$K$, ${\delta ^2}$, $N$, $B$, $T$；初始化迭代次數(shù)$l = 0$；　定義最大迭代次數(shù)${L_{\max }}$和收斂精度$\varpi $；
(1) WHILE 　　$ \left\| {\displaystyle\sum\nolimits_{k = 1}^K {{{\left( {R_k^{\text{u}} + R_k^{\text}} \right)}^{(l)}}} - \displaystyle\sum\nolimits_{k = 1}^K {{{\left( {R_k^{\text{u}} + R_k^{\text}} \right)}^{(l - 1)}}} } \right\| \ge \varpi $ 或　　$l \le {L_{\max }}$ DO
(2) 設(shè)置迭代次數(shù)$l = l + 1$；
(3) 固定$t_k^{(l - 1)}$和$\theta _k^{(l - 1)}$，根據(jù)式(26)計(jì)算${{{\boldsymbol{W}}}^{(l)}}$；若${{{\boldsymbol{W}}}^{(l)}}$的秩　　為1，則使用特征值分解法得到最優(yōu)解；若${{{\boldsymbol{W}}}^{(l)}}$的秩大于1，　　采用高斯隨機(jī)化方法得到近似解；
(4) 固定${{{\boldsymbol{W}}}^{(l)}}$，根據(jù)式(32)求解$t_k^{(l)}$和$\theta _k^{(l)}$；
(5) 更新吞吐量$ \displaystyle\sum\nolimits_{k = 1}^K {\left( {R_k^{\text{u}} + R_k^{\text}} \right)} $。
(6) END WHILE

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