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Advanced Interference Mitigation Techniques for Cellular-Connected Drone Communication.
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Advanced Interference Mitigation Techniques for Cellular-Connected Drone Communication./
作者:
Mei, Weidong.
出版者:
Ann Arbor : ProQuest Dissertations & Theses, : 2021,
面頁冊數:
153 p.
附註:
Source: Dissertations Abstracts International, Volume: 84-04, Section: B.
Contained By:
Dissertations Abstracts International84-04B.
標題:
Design optimization. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29352894
ISBN:
9798352687192
Advanced Interference Mitigation Techniques for Cellular-Connected Drone Communication.
Mei, Weidong.
Advanced Interference Mitigation Techniques for Cellular-Connected Drone Communication.
- Ann Arbor : ProQuest Dissertations & Theses, 2021 - 153 p.
Source: Dissertations Abstracts International, Volume: 84-04, Section: B.
Thesis (Ph.D.)--National University of Singapore (Singapore), 2021.
This item must not be sold to any third party vendors.
The popularity of drones or unmanned aerial vehicles (UAVs) has increased rapidly over the last decade. To support their large-scale deployment, a new wireless networking paradigm, namely, cellular-connected UAV, has received an upsurge of interests recently. Specifically, cellular base stations (BSs) and spectrum are used to serve UAVs as new aerial user equipments (UEs) for significantly enhancing their communication performance. However, different from the terrestrial UEs, the high altitude of UAV results in line-of-sight (LoS) dominant channels with both its serving and non-serving BSs in a wide area, which will cause strong aerial-ground interferences that could severely impair the communications of both UAVs and terrestrial UEs. Conventional interference mitigation techniques designed for terrestrial networks are generally ineffective in resolving the new UAV-terrestrial interference problem. To tackle the above challenge, this thesis proposes new interference mitigation solutions to achieve spectrum efficient operation of the cellular network with co-existing UAVs and terrestrial UEs.First, we consider the uplink transmission from a UAV to cellular BSs and propose a new aerial-ground inter-cell interference coordination (ICIC) technique to mitigate its strong uplink interference to existing co-channel terrestrial UEs. To investigate the optimal ICIC design and air-ground performance trade-off, we maximize the weighted sum-rate of the UAV and existing terrestrial UEs by jointly optimizing the UAV’s BS associations and power allocations over multiple resource blocks (RBs). However, this problem is non-convex and difficult to be solved optimally. We first propose a centralized ICIC design to obtain a locally optimal solution by applying the successive convex approximation method. As the centralized ICIC requires global information of the network and substantial information exchange among an excessively large number of BSs, we further propose a decentralized ICIC scheme of significantly lower complexity and signaling overhead for implementation, by dividing the cellular BSs into small-size clusters and exploiting the LoS-induced macro-diversity for exchanging information between the UAV and cluster-head BSs only. Numerical results show that the proposed centralized and decentralized ICIC schemes both achieve a near-optimal performance, and draw important design insights based on practical system setups.Second, as the aerial-ground ICIC only treats the UAV’s interference as noise at each co-channel terrestrial BS, we propose to apply the non-orthogonal multiple access (NOMA) technique with successive interference cancellation to further improve its performance. However, for our considered system, traditional NOMA with only local interference cancellation at individual BSs, termed non-cooperative NOMA, may only yield very marginal gain over the orthogonal multiple access (OMA). This is because there are a large number of co-channel BSs due to the LoS UAV-BS channels and thus the rate performance of the UAV is severely limited by the BS with the worst channel condition with it. To mitigate the UAV’s uplink interference without significantly compromising its achievable rate, a new cooperative NOMA scheme is proposed by exploiting the existing backhaul links among BSs. Specifically, some BSs with better channel conditions are selected to decode the UAV’s signals first, and then forward the decoded signals to their backhaul-connected BSs for interference cancellation. To investigate the optimal design of cooperative NOMA, we maximize the weighted sum-rate of the UAV and terrestrial UEs by jointly optimizing the UAV’s rate and power allocations over multiple RBs as well as their associated BSs.
ISBN: 9798352687192Subjects--Topical Terms:
1372602
Design optimization.
Advanced Interference Mitigation Techniques for Cellular-Connected Drone Communication.
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The popularity of drones or unmanned aerial vehicles (UAVs) has increased rapidly over the last decade. To support their large-scale deployment, a new wireless networking paradigm, namely, cellular-connected UAV, has received an upsurge of interests recently. Specifically, cellular base stations (BSs) and spectrum are used to serve UAVs as new aerial user equipments (UEs) for significantly enhancing their communication performance. However, different from the terrestrial UEs, the high altitude of UAV results in line-of-sight (LoS) dominant channels with both its serving and non-serving BSs in a wide area, which will cause strong aerial-ground interferences that could severely impair the communications of both UAVs and terrestrial UEs. Conventional interference mitigation techniques designed for terrestrial networks are generally ineffective in resolving the new UAV-terrestrial interference problem. To tackle the above challenge, this thesis proposes new interference mitigation solutions to achieve spectrum efficient operation of the cellular network with co-existing UAVs and terrestrial UEs.First, we consider the uplink transmission from a UAV to cellular BSs and propose a new aerial-ground inter-cell interference coordination (ICIC) technique to mitigate its strong uplink interference to existing co-channel terrestrial UEs. To investigate the optimal ICIC design and air-ground performance trade-off, we maximize the weighted sum-rate of the UAV and existing terrestrial UEs by jointly optimizing the UAV’s BS associations and power allocations over multiple resource blocks (RBs). However, this problem is non-convex and difficult to be solved optimally. We first propose a centralized ICIC design to obtain a locally optimal solution by applying the successive convex approximation method. As the centralized ICIC requires global information of the network and substantial information exchange among an excessively large number of BSs, we further propose a decentralized ICIC scheme of significantly lower complexity and signaling overhead for implementation, by dividing the cellular BSs into small-size clusters and exploiting the LoS-induced macro-diversity for exchanging information between the UAV and cluster-head BSs only. Numerical results show that the proposed centralized and decentralized ICIC schemes both achieve a near-optimal performance, and draw important design insights based on practical system setups.Second, as the aerial-ground ICIC only treats the UAV’s interference as noise at each co-channel terrestrial BS, we propose to apply the non-orthogonal multiple access (NOMA) technique with successive interference cancellation to further improve its performance. However, for our considered system, traditional NOMA with only local interference cancellation at individual BSs, termed non-cooperative NOMA, may only yield very marginal gain over the orthogonal multiple access (OMA). This is because there are a large number of co-channel BSs due to the LoS UAV-BS channels and thus the rate performance of the UAV is severely limited by the BS with the worst channel condition with it. To mitigate the UAV’s uplink interference without significantly compromising its achievable rate, a new cooperative NOMA scheme is proposed by exploiting the existing backhaul links among BSs. Specifically, some BSs with better channel conditions are selected to decode the UAV’s signals first, and then forward the decoded signals to their backhaul-connected BSs for interference cancellation. To investigate the optimal design of cooperative NOMA, we maximize the weighted sum-rate of the UAV and terrestrial UEs by jointly optimizing the UAV’s rate and power allocations over multiple RBs as well as their associated BSs.
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