面向能效的低轨卫星联合跳波束调度和功率分配算法

梁承超; 段瑞吉; 麻世庆; 唐伦; 陈前斌

doi:10.11999/JEIT220392

面向能效的低轨卫星联合跳波束调度和功率分配算法

doi: 10.11999/JEIT220392

重庆邮电大学通信与信息工程学院重庆 400065

基金项目: “十三五”民用航天技术预先研究(D030301)，国家自然科学基金(62001076, 62071078)

详细信息

作者简介:
梁承超：男，教授，博士，研究方向无线通信、卫星组网、网络架构与协议

段瑞吉：男，硕士生，研究方向为空天地一体化、星地融合、凸优化算法

麻世庆：男，硕士生，研究方向为空天地一体化、星地融合、机器学习算法

唐伦：男，教授，博士生导师，主要研究方向为空天地一体化、下一代无线通信网络、软件定义无线网络等

陈前斌：男，教授，博士生导师，主要研究方向为空天地一体化、多媒体信息处理与传输、异构蜂窝网络等

通讯作者:
陈前斌　chenqb@cqupt.edu.cn

中图分类号: TN929.5
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出版历程
- 收稿日期: 2022-04-02
- 修回日期: 2022-11-14
- 网络出版日期: 2022-11-15
- 刊出日期: 2023-02-07

Joint Beam Hopping Scheduling and Power Allocation of LEO Satellites Oriented Energy Efficiency

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

Funds: 135 Civil Aerospace Technology Advance Research Project (D030301), The National Natural Science Foundation of China (62001076, 62071078)

摘要

摘要: 该文针对低轨(LEO)卫星载荷容量受限且功率资源稀缺的问题，面向搭载跳波束(BH)天线的低轨卫星通信系统，提出一种联合跳波束调度和功率分配机制，在满足用户服务质量需求的前提下降低卫星通信载荷功耗，提高卫星通信系统能效。首先建立时延受限下联合考虑波束调度和功率分配的卫星功耗最小化模型。针对网络拓扑的时变特性，基于李雅普诺夫优化方法，将原多时隙优化问题转化为单时隙优化问题，然后采用交替优化的方法获得单时隙问题的次优解。其中，证明波束调度子问题是凸问题，同时通过逐次凸近似和对数变换将功率分配子问题转为凸问题，并提出相应算法获得子问题最优解。仿真结果表明，提出的策略在保证用户平均时延要求的同时，降低了低轨卫星系统平均功耗，并且可通过调整控制参数实现时延和功耗的动态平衡。
- 低轨卫星 /
- 能效 /
- 跳波束 /
- 功率分配 /
- 李雅普诺夫优化方法
Abstract: In Low Earth Orbit (LEO) satellite networks, the capacity of satellite payload is limited strictly, and onboard power resource is extremely scarce. Thus, a joint Beam Hopping (BH) scheduling and power allocation scheme is proposed to reduce onboard power resources consumption for the LEO system with BH antennas, while meeting quality of service requirements of users, so that the energy efficiency of the satellite communication system can be improved. Firstly, the joint beam scheduling and power allocation problem with delay constraints is formulated to minimize the power consumption of the satellite system. Considering the time-varying topological characteristics of the system, the original multi-slot optimization problem is transformed into a single-slot optimization problem based on the Lyapunov optimization method, and then the alternate optimization method is employed to obtain the sub-optimal solution of the single-slot problem. Specifically, the beam scheduling subproblem is proved to be convex, the power distribution subproblem is transformed into convex by successive convex approximation and logarithmic transformation, and the corresponding algorithm is proposed to obtain the optimal solution of the subproblems. Simulation results show that the proposed scheme can reduce the onboard power consumption of the satellite while ensuring the average time delay requirement of the users, and the dynamic balance of the delay and the power consumption can be achieved by adjusting the control parameter.
- LEO satellites /
- Energy efficiency /
- Beam hopping /
- Power allocation /
- Lyapunov optimization method

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图 1 基于跳波束的低轨卫星通信架构

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图 2 资源调度过程的性能参数变化

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图 3 系统性能随控制参数的变化趋势

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图 4 系统性能随数据到达率的变化趋势

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算法1　联合波束调度和功率分配算法
(1) 输入：各用户初始队列长度$ {Q_u}(0) $，最大时间平均时延$ {D_{u,\max }} $，控制参数$ V $，问题式(19)与式(21)分别的原对偶内点法阈值$ {\xi _1} $和$ {\xi _2} $，SCA算法的阈值$ {\zeta _{{\text{sca}}}} $，交替优化算法阈值$ {\zeta _{{\text{alt}}}} $
(2) For $t = 1,2, \cdots, T$ do
(3) 　　按照上文给出的方法给功率分配和波束调度的初始可行解$ {{{p}}^{\left( 0 \right)}} $和$ {{{x}}^{\left( 0 \right)}} $，并计算式(17)的目标函数值${f_{{\rm{P}}3} }\left( { { {{p} }^{\left( 0 \right)} },{ {{x} }^{\left( 0 \right)} } } \right)$
(4) 　　While $\left\| { {f_{{\rm{P}}3} }\left( { { {{p} }^{\left( k \right)} },{ {{x} }^{\left( k \right)} } } \right) - {f_{{\rm{P}}3} }\left( { { {{p} }^{\left( {k - 1} \right)} },{ {{x} }^{\left( {k - 1} \right)} } } \right)} \right\| > {\zeta _{ {\text{alt} } } }$ do
(5) 　　　　给定$ {{{p}}^{\left( k \right)}} $，并以$ {{{x}}^{\left( k \right)}} $为初始迭代点，通过内点算法解决式(19)，当对偶间隙小于$ {\xi _1} $时内点法终止，其最优解为$ {{{x}}^{\left( {k + 1} \right)}} $
(6) 　　　　根据$ {{{x}}^{\left( {k + 1} \right)}} $和$ {{{p}}^{\left( k \right)}} $计算$ \omega _u^{(k,0)} $和P6目标函数的最优值$f_{{\rm{P}}6}^*\left( { { {{p} }^{\left( {k,0} \right)} },{ {{x} }^{\left( k \right)} } } \right)$，进而获得SCA近似参数$ c_{u,n}^{(k,0)} $和$ v_{u,n}^{(k,0)} $
(7) 　　　　While $\left\| { {f_{{\rm{P}}6} }\left( { { {{p} }^{\left( {k,l} \right)} },{ {{x} }^{\left( {k + 1} \right)} } } \right) - {f_{{\rm{P}}6} }\left( { { {{p} }^{\left( {k,l - 1} \right)} },{ {{x} }^{\left( {k + 1} \right)} } } \right)} \right\| > {\zeta _{ {\text{sca} } } }$ do
(8) 　　　　　　依据$ {{{p}}^{\left( {k,l} \right)}} $计算$ c_{u,n}^{(k,l + 1)} $和$ v_{u,n}^{(k,l + 1)} $
(9) 　　　　　　通过内点算法解决问题P6，当对偶间隙小于$ {\xi _2} $时停止，其最优解为$ {{{p}}^{\left( {k,l{\text{ + }}1} \right)}} $，同时令$ l = l + 1 $
(10) 　　　　　 End while
(11) 　　　　　 $ {{{p}}^{\left( {k + 1} \right)}} \leftarrow {{{p}}^{\left( {k,l} \right)}} $，并且计算${f_{{\rm{P}}3} }\left( { { {{p} }^{\left( {k + 1} \right)} },{ {{x} }^{\left( {k + 1} \right)} } } \right)$，同时令$ k = k + 1 $
(12) 　　　 End while
(13) 　根据式(6)和式(10)更新$ {Q_u}(t + 1) $和$ {Y_u}(t + 1) $
(14) End for
(15) 输出：每个调度时隙的(近似)最优波束调度策略和功率策略

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表 1 多波束低轨卫星场景参数设定

低轨卫星网络参数	取值	低轨卫星网络参数	取值
卫星轨道高度	1200 km	系统子信道数W	100
卫星波束个数B	7	下行链路工作频率f	26.5 GHz
服务小区总数N	37	卫星发射天线增益$ {G_0} $	30.5 dBi
小区半径	90 km	噪声功率密度N₀	–174 dBm/Hz
用户数U	200	卫星最大发射功率$ {p_{\max }} $	200 W
用户分布	平面热点分布	单用户的最大发射功率$ {p_{u,\max }} $	5 W
热点分布参数(a,c)	(80,6)	多波束天线半波束角	$ {4.4^ \circ } $
子信道带宽$ \Delta f $	180 kHz	数据流到达速率均值$ {\lambda _u} $	[1,2.5] Mbps

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