Alireza Fadakar;Yuchen Zhang;Hui Chen;Musa Furkan Keskin;Henk Wymeersch;Andreas F. Molisch
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引用次数: 0
Abstract
Electromagnetically reconfigurable fluid antenna system (ER-FAS) introduces additional degrees of freedom in the electromagnetic (EM) domain by dynamically steering perantenna radiation patterns, thereby enhancing power efficiency in wireless links. Unlike prior works on spatially reconfigurable FAS, which adjust element positions, ER-FAS provides direct control over each element's EM characteristics to realize ondemand beampattern shaping. While existing studies have exploited ER-FAS to boost spectral efficiency, this paper explores its application for downlink localization. We consider a multiple-input single-output (MISO) system in which a multiantenna ER-FAS at the base station serves a singleantenna user equipment (UE). We consider two reconfigurability paradigms: (i) a synthesis model where each antenna generates desired beampatterns from a finite set of EM basis functions, and (ii) a finite-state selection model in which each antenna selects a pattern from a predefined set of patterns. For both paradigms, we formulate the joint baseband (BB) and EM precoder design to minimize the UE position error bound. In the synthesis case we derive low-dimensional closed-form expressions for both the BB and EM precoders. For the finite-state model we obtain closed-form BB structures and propose a low-complexity block-coordinate-descent algorithm for EM pattern selection. Analytical bounds and extensive simulations show that the proposed hybrid designs for ER-FAS substantially improve UE positioning accuracy over traditional non-reconfigurable arrays.
期刊介绍:
The IEEE Journal of Selected Topics in Signal Processing (JSTSP) focuses on the Field of Interest of the IEEE Signal Processing Society, which encompasses the theory and application of various signal processing techniques. These techniques include filtering, coding, transmitting, estimating, detecting, analyzing, recognizing, synthesizing, recording, and reproducing signals using digital or analog devices. The term "signal" covers a wide range of data types, including audio, video, speech, image, communication, geophysical, sonar, radar, medical, musical, and others.
The journal format allows for in-depth exploration of signal processing topics, enabling the Society to cover both established and emerging areas. This includes interdisciplinary fields such as biomedical engineering and language processing, as well as areas not traditionally associated with engineering.