Multiple input single output aerial base station‐assisted networks: Joint 3D beam‐forming, aerial base station assignment, 3D placement, and radio resource allocation
In this article, we propose a novel method according to which joint aerial base station (ABS) assignment, three‐dimensional placement (3DP), three‐dimensional beam‐forming (3DB), and radio resource allocation are considered for multiple input single output (MISO) ABS‐based networks with orthogonal f...
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| Published in | Transactions on emerging telecommunications technologies Vol. 33; no. 4 |
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| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
01.04.2022
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| Online Access | Get full text |
| ISSN | 2161-3915 2161-3915 |
| DOI | 10.1002/ett.4140 |
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| Abstract | In this article, we propose a novel method according to which joint aerial base station (ABS) assignment, three‐dimensional placement (3DP), three‐dimensional beam‐forming (3DB), and radio resource allocation are considered for multiple input single output (MISO) ABS‐based networks with orthogonal frequency division multiple access (OFDMA) technology. We aim to maximize the instantaneous data rate subject to some practical constraints. In light of the fact that our optimization problem is mixed‐integer nonlinear programming (MINLP) with high computational complexity, we propose a low complex and practical approach. Therefore, we resort to an alternate method by which the main optimization problem decomposes into three subproblems. Then we solve the resulting subproblems via linear approximation method, matching theory, and mesh adaptive direct search (MADS) algorithm. In order to shed light on our proposed approach, we decompose the proposed scenario into some cases with fewer optimization variables and compare them with our main problem. Our proposed approach boosts the instantaneous data rate compared to the decomposed cases with fewer optimization variables. Via simulation, we study the effect of various parameters like numbers of users, ABSs, and maximum transmission powers on the network performance. Finally, we analyze the network performance for suburban and urban environments considering various number of ABSs.
we propose a novel method according to which joint aerial base station (ABS) assignment, three‐dimensional placement (3DP), three‐dimensional beam‐forming (3DB), and radio resource allocation are considered for multiple input single output (MISO) ABS‐based networks with orthogonal frequency division multiple access (OFDMA) technology. We maximize the instantaneous data rate subject to some practical constraints and solve this problem via a linear approximation method, matching theory, and mesh adaptive direct search (MADS) algorithm. |
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| AbstractList | In this article, we propose a novel method according to which joint aerial base station (ABS) assignment, three‐dimensional placement (3DP), three‐dimensional beam‐forming (3DB), and radio resource allocation are considered for multiple input single output (MISO) ABS‐based networks with orthogonal frequency division multiple access (OFDMA) technology. We aim to maximize the instantaneous data rate subject to some practical constraints. In light of the fact that our optimization problem is mixed‐integer nonlinear programming (MINLP) with high computational complexity, we propose a low complex and practical approach. Therefore, we resort to an alternate method by which the main optimization problem decomposes into three subproblems. Then we solve the resulting subproblems via linear approximation method, matching theory, and mesh adaptive direct search (MADS) algorithm. In order to shed light on our proposed approach, we decompose the proposed scenario into some cases with fewer optimization variables and compare them with our main problem. Our proposed approach boosts the instantaneous data rate compared to the decomposed cases with fewer optimization variables. Via simulation, we study the effect of various parameters like numbers of users, ABSs, and maximum transmission powers on the network performance. Finally, we analyze the network performance for suburban and urban environments considering various number of ABSs. In this article, we propose a novel method according to which joint aerial base station (ABS) assignment, three‐dimensional placement (3DP), three‐dimensional beam‐forming (3DB), and radio resource allocation are considered for multiple input single output (MISO) ABS‐based networks with orthogonal frequency division multiple access (OFDMA) technology. We aim to maximize the instantaneous data rate subject to some practical constraints. In light of the fact that our optimization problem is mixed‐integer nonlinear programming (MINLP) with high computational complexity, we propose a low complex and practical approach. Therefore, we resort to an alternate method by which the main optimization problem decomposes into three subproblems. Then we solve the resulting subproblems via linear approximation method, matching theory, and mesh adaptive direct search (MADS) algorithm. In order to shed light on our proposed approach, we decompose the proposed scenario into some cases with fewer optimization variables and compare them with our main problem. Our proposed approach boosts the instantaneous data rate compared to the decomposed cases with fewer optimization variables. Via simulation, we study the effect of various parameters like numbers of users, ABSs, and maximum transmission powers on the network performance. Finally, we analyze the network performance for suburban and urban environments considering various number of ABSs. we propose a novel method according to which joint aerial base station (ABS) assignment, three‐dimensional placement (3DP), three‐dimensional beam‐forming (3DB), and radio resource allocation are considered for multiple input single output (MISO) ABS‐based networks with orthogonal frequency division multiple access (OFDMA) technology. We maximize the instantaneous data rate subject to some practical constraints and solve this problem via a linear approximation method, matching theory, and mesh adaptive direct search (MADS) algorithm. |
| Author | Azizi, Arman Mokari, Nader |
| Author_xml | – sequence: 1 givenname: Arman orcidid: 0000-0002-9906-3479 surname: Azizi fullname: Azizi, Arman email: armanazizi@modares.ac.ir organization: Tarbiat Modares University – sequence: 2 givenname: Nader orcidid: 0000-0001-5364-8888 surname: Mokari fullname: Mokari, Nader email: nader.mokari@modares.ac.ir organization: Tarbiat Modares University |
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