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Sparse Array Architectures for Wireless Communication and Radar Applications.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Sparse Array Architectures for Wireless Communication and Radar Applications./
作者:	Amani, Navid.
面頁冊數:	1 online resource (87 pages)
附註:	Source: Dissertations Abstracts International, Volume: 83-09, Section: B.
Contained By:	Dissertations Abstracts International83-09B.
標題:	Sparsity. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28974230click for full text (PQDT)
ISBN:	9798780654537

Sparse Array Architectures for Wireless Communication and Radar Applications.
Amani, Navid.

Sparse Array Architectures for Wireless Communication and Radar Applications. - 1 online resource (87 pages)

Source: Dissertations Abstracts International, Volume: 83-09, Section: B.

Thesis (Ph.D.)--Chalmers Tekniska Hogskola (Sweden), 2021.

Includes bibliographical references

This thesis focuses on sparse array architectures for the next generation of wireless communication, known as fifth-generation (5G), and automotive radar direction-of-arrival (DOA) estimation. For both applications, array spatial resolution plays a critical role to better distinguish multiple users/sources. Two novel base station antenna (BSA) configurations and a new sparse MIMO radar, which both outperform their conventional counterparts, are proposed. We first develop a multi-user (MU) multiple-input multiple-output (MIMO) simulation platform which incorporates both antenna and channel effects based on standard network theory. The combined transmitter-channel-receiver is modeled by cascading Z-matrices to interrelate the port voltages/currents to one another in the linear network model. The herein formulated channel matrix includes physical antenna and channel effects and thus enables us to compute the actual port powers. This is in contrast with the assumptions of isotropic radiators without mutual coupling effects which are commonly being used in the Wireless Community. Since it is observed in our model that the sum-rate of a MU-MIMO system can be adversely affected by antenna gain pattern variations, a novel BSA configuration is proposed by combining field-of-view (FOV) sectorization, array panelization and array sparsification. A multi-panel BSA, equipped with sparse arrays in each panel, is presented with the aim of reducing the implementation complexities and maintaining or even improving the sum-rate. We also propose a capacity-driven array synthesis in the presence of mutual coupling for a MU-MIMO system. We show that the appearance of grating lobes is degrading the system capacity and cannot be disregarded in a MU communication, where space division multiple access (SDMA) is applied. With the aid of sparsity and aperiodicity, the adverse effects of grating lobes and mutual coupling are suppressed and capacity is enhanced. This is performed by proposing a two-phase optimization. In Phase I, the problem is relaxed to a convex optimization by ignoring the mutual coupling and weakening the constraints. The solution of Phase I is used as the initial guess for the genetic algorithm (GA) in phase II, where the mutual coupling is taken into account. The proposed hybrid algorithm outperforms the conventional GA with random initialization.A novel sparse MIMO radar is presented for high-resolution single snapshot DOA estimation. Both transmit and receive arrays are divided into two uniform arrays with increased inter-element spacings to generate two uniform sparse virtual arrays. Since virtual arrays are uniform, conventional spatial smoothing can be applied for temporal correlation suppression among sources. Afterwards, the spatially smoothed virtual arrays satisfy the co-primality concept to avoid DOA ambiguities. Physical antenna effects are incorporated in the received signal model and their effects on the DOA estimation performance are investigated.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2023

Mode of access: World Wide Web

ISBN: 9798780654537Subjects--Topical Terms:

3680690
Sparsity.
Index Terms--Genre/Form:

542853
Electronic books.

Sparse Array Architectures for Wireless Communication and Radar Applications.
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245 1 0 $a Sparse Array Architectures for Wireless Communication and Radar Applications.
264 0 $c 2021
300 $a 1 online resource (87 pages)
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500 $a Source: Dissertations Abstracts International, Volume: 83-09, Section: B.
500 $a Advisor: Maaskant, R.; Smolders, A.B.; Ivashina, M.V.; Johannsen, U.; Jensen, M.A.
502 $a Thesis (Ph.D.)--Chalmers Tekniska Hogskola (Sweden), 2021.
504 $a Includes bibliographical references
520 $a This thesis focuses on sparse array architectures for the next generation of wireless communication, known as fifth-generation (5G), and automotive radar direction-of-arrival (DOA) estimation. For both applications, array spatial resolution plays a critical role to better distinguish multiple users/sources. Two novel base station antenna (BSA) configurations and a new sparse MIMO radar, which both outperform their conventional counterparts, are proposed. We first develop a multi-user (MU) multiple-input multiple-output (MIMO) simulation platform which incorporates both antenna and channel effects based on standard network theory. The combined transmitter-channel-receiver is modeled by cascading Z-matrices to interrelate the port voltages/currents to one another in the linear network model. The herein formulated channel matrix includes physical antenna and channel effects and thus enables us to compute the actual port powers. This is in contrast with the assumptions of isotropic radiators without mutual coupling effects which are commonly being used in the Wireless Community. Since it is observed in our model that the sum-rate of a MU-MIMO system can be adversely affected by antenna gain pattern variations, a novel BSA configuration is proposed by combining field-of-view (FOV) sectorization, array panelization and array sparsification. A multi-panel BSA, equipped with sparse arrays in each panel, is presented with the aim of reducing the implementation complexities and maintaining or even improving the sum-rate. We also propose a capacity-driven array synthesis in the presence of mutual coupling for a MU-MIMO system. We show that the appearance of grating lobes is degrading the system capacity and cannot be disregarded in a MU communication, where space division multiple access (SDMA) is applied. With the aid of sparsity and aperiodicity, the adverse effects of grating lobes and mutual coupling are suppressed and capacity is enhanced. This is performed by proposing a two-phase optimization. In Phase I, the problem is relaxed to a convex optimization by ignoring the mutual coupling and weakening the constraints. The solution of Phase I is used as the initial guess for the genetic algorithm (GA) in phase II, where the mutual coupling is taken into account. The proposed hybrid algorithm outperforms the conventional GA with random initialization.A novel sparse MIMO radar is presented for high-resolution single snapshot DOA estimation. Both transmit and receive arrays are divided into two uniform arrays with increased inter-element spacings to generate two uniform sparse virtual arrays. Since virtual arrays are uniform, conventional spatial smoothing can be applied for temporal correlation suppression among sources. Afterwards, the spatially smoothed virtual arrays satisfy the co-primality concept to avoid DOA ambiguities. Physical antenna effects are incorporated in the received signal model and their effects on the DOA estimation performance are investigated.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2023
538 $a Mode of access: World Wide Web
650 4 $a Sparsity. $3 3680690
650 4 $a Wireless communications. $3 3554231
650 4 $a Receivers & amplifiers. $3 3559205
650 4 $a Propagation. $3 3680519
650 4 $a Wireless networks. $3 1531264
650 4 $a Satellite communications. $3 3694420
650 4 $a Internet access. $3 3410690
650 4 $a Genetic algorithms. $3 533907
650 4 $a Optimization. $3 891104
650 4 $a Signal processing. $3 533904
650 4 $a Antennas. $3 3681648
650 4 $a Transmitters. $3 3680766
650 4 $a Arrays. $3 3681398
650 4 $a Growth rate. $3 3562870
650 4 $a Radar. $3 594027
650 4 $a Entrance examinations. $3 3686607
650 4 $a Aerospace engineering. $3 1002622
650 4 $a Artificial intelligence. $3 516317
650 4 $a Computer science. $3 523869
650 4 $a Electrical engineering. $3 649834
650 4 $a Engineering. $3 586835
650 4 $a Physics. $3 516296
655 7 $a Electronic books. $2 lcsh $3 542853
690 $a 0538
690 $a 0800
690 $a 0984
690 $a 0544
690 $a 0537
690 $a 0605
710 2 $a ProQuest Information and Learning Co. $3 783688
710 2 $a Chalmers Tekniska Hogskola (Sweden). $3 1913472
773 0 $t Dissertations Abstracts International $g 83-09B.
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28974230 $z click for full text (PQDT)