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1. 南京邮电大学通信与信息工程学院,江苏 南京 210003
2. 国防科技大学电子对抗学院,安徽 合肥 230037
3. 国防科技大学六十三研究所, 江苏 南京 210003
[ "李艳丽(1996− ),女,南京邮电大学硕士生,主要研究方向为无线通信、通信信号处理" ]
[ "林志(1992− ),男,国防科技大学讲师,主要研究方向为卫星通信、阵列信号处理、凸优化理论等" ]
[ "王子宁(1997− ),男,南京邮电大学博士生,主要研究方向为通信信号处理、无线通信" ]
[ "许拔(1981− ),男,国防科技大学六十三研究所高级工程师,主要研究方向为通信抗干扰技术、通信信号处理技术" ]
[ "程铭(1991− ),男,南京邮电大学讲师,主要研究方向为毫米波通信、大规模MIMO和智能反射面应用" ]
[ "欧阳键(1983− ),男,南京邮电大学副教授,主要研究方向为无人机通信、物理层安全" ]
网络出版日期:2021-08,
纸质出版日期:2021-08-20
移动端阅览
李艳丽, 林志, 王子宁, 等. 基于无人机中继的星地认知网络波束成形算法[J]. 电信科学, 2021,37(8):27-37.
Yanli LI, Zhi LIN, Zining WANG, et al. Beamforming algorithm for cognitive satellite and terrestrial network based on UAV relay[J]. Telecommunications science, 2021, 37(8): 27-37.
李艳丽, 林志, 王子宁, 等. 基于无人机中继的星地认知网络波束成形算法[J]. 电信科学, 2021,37(8):27-37. DOI: 10.11959/j.issn.1000-0801.2021202.
Yanli LI, Zhi LIN, Zining WANG, et al. Beamforming algorithm for cognitive satellite and terrestrial network based on UAV relay[J]. Telecommunications science, 2021, 37(8): 27-37. DOI: 10.11959/j.issn.1000-0801.2021202.
针对基于无人机中继的星地认知网络,提出了两种波束成形(beamforming
BF)算法,通过对各种干扰进行抑制,实现系统间的频谱共享。具体而言,在基于无人机中继的卫星网络作为次级网络、地面网络作为主网络的情况下,以无人机最大发射功率和主用户所受干扰为约束条件,建立次级用户信干噪比最大化准则的优化问题;接下来在已知次级用户统计信道状态信息的条件下,提出一种基于迭代的BF算法对优化问题进行求解;更进一步,为了降低迭代算法的实现复杂度,提出了一种基于迫零的BF算法。最后,计算机仿真验证了所提两种波束成形方案的正确性与有效性。
Two beamforming (BF) schemes to achieve spectrum sharing by suppressing inter-system interferences in cognitive satellite and terrestrial networks were proposed
where the satellite and UAV cooperative network was used as the secondary network
while the terrestrial network was used as the primary network.Specifically
considering that only the statistical channel state information was available
a constrained optimization problem was formulated to maximize the signal-to- interference-plus-noise ratio of the secondary user under the constraints of the maximum transmit power at the UAV and the interference power of the primary user.Then
an iteration-based BF scheme was proposed to solve the constrained optimization problem.To reduce the computational complexity of the iterative algorithm
a zero-forcing based BF scheme was further proposed.Finally
computer simulations verify the correctness and effectiveness of the proposed BF schemes.
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刘鑫胜 . 无人机网络的性能分析与优化研究 [D ] . 北京:北京邮电大学 , 2019 .
LIU X S . Research on performance analysis and optimization of UAV network [D ] . Beijing:Beijing University of Posts and Telecommunications , 2019 .
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HE Z J , AI Y , YAN S , et al . Performance evaluation of capacity and coverage in UAV communication networks [J ] . Telecommunications Science , 2017 , 33 ( 10 ): 65 - 70 .
FOTOUHI A , QIANG H R , DING M , et al . Survey on UAV cellular communications:practical aspects,standardization advancements,regulation,and security challenges [J ] . IEEE Communications Surveys & Tutorials , 2019 , 21 ( 4 ): 3417 - 3442 .
SHARMA P K , DEEPTHI D , KIM D I . Outage probability of 3-D mobile UAV relaying for hybrid satellite-terrestrial networks [J ] . IEEE Communications Letters , 2020 , 24 ( 2 ): 418 - 422 .
HUANG Q Q , LIN M , WANG J B , et al . Energy efficient beamforming schemes for satellite-aerial-terrestrial networks [J ] . IEEE Transactions on Communications , 2020 , 68 ( 6 ): 3863 - 3875 .
LI Z D , WANG Y , LIU M , et al . Energy efficient resource allocation for UAV-assisted space-air-ground Internet of remote things networks [J ] . IEEE Access , 2019 , 7 : 145348 - 145362 .
JAIN R , TEMPLIN F . Requirements,challenges and analysis of alternatives for wireless datalinks for unmanned aircraft systems [J ] . IEEE Journal on Selected Areas in Communications , 2012 , 30 ( 5 ): 852 - 860 .
PAN Y , DA X Y , HU H , et al . Energy-efficiency optimization of UAV-based cognitive radio system [J ] . IEEE Access , 2019 ( 7 ): 155381 - 155391 .
何智勇 . 认知无线电中一种改进的AVC频谱感知算法 [J ] . 电信科学 , 2017 , 33 ( 2 ): 98 - 103 .
HE Z Y . Modified absolute value cumulating spectrum sensing algorithm in cognitive radio [J ] . Telecommunications Science , 2017 , 33 ( 2 ): 98 - 103 .
LIN Z , LIN M , DE COLA T , et al . Supporting IoT with rate-splitting multiple access in satellite and aerial-integrated networks [J ] . IEEE Internet of Things Journal , 2021 , 8 ( 14 ): 11123 - 11134 .
HU H , LIANG Y C , ZHANG H , et al . Cognitive radio with self-power recycling [J ] . IEEE Transactions on Vehicular Technology , 2017 , 66 ( 7 ): 6201 - 6214 .
彭青 , 李银伟 , 郭志军 . 认知 MIMO 系统中波束成形和功率的联合控制博弈算法 [J ] . 电信科学 , 2015 , 31 ( 8 ): 45 - 51 .
PENG Q , LI Y W , GUO Z J . Joint beamforming and power control algorithm for cognitive MIMO system via game theory [J ] . Telecommunications Science , 2015 , 31 ( 8 ): 45 - 51 .
RUAN Y H , LI Y Z , ZHANG R , et al . Cooperative resource management for cognitive satellite-aerial-terrestrial integrated networks towards IoT [J ] . IEEE Access , 2020 ( 8 ): 35759 - 35769 .
MUSAVIAN L , AISSA S , LAMBOTHARAN S . Effective capacity for interference and delay constrained cognitive radio relay channels [J ] . IEEE Transactions on Wireless Communications , 2010 , 9 ( 5 ): 1698 - 1707 .
LIN M , OUYANG J , ZHU W P . Joint beamforming and power control for device-to-device communications underlaying cellular networks [J ] . IEEE Journal on Selected Areas in Communications , 2016 , 34 ( 1 ): 138 - 150 .
HE S W , HUANG Y M , JIN S , et al . Coordinated beamforming for energy efficient transmission in multicell multiuser systems [J ] . IEEE Transactions on Communications , 2013 , 61 ( 12 ): 4961 - 4971 .
ZHANG X J , LEE J . Low complexity MIMO scheduling with channel decomposition using capacity upperbound [J ] . IEEE Transactions on Communications , 2008 , 56 ( 6 ): 871 - 876 .
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