Search arXivSearch

arXiv · 2210.11597

Multi-objective Design of Uniform Sparse MIMO Arrays

Abstract

The problem of multi-objective design of sparse MIMO arrays for better multitarget detection capabilities is considered. A novel approach for efficient utilization of the antenna design resources; namely, the number of available array elements, and array aperture are studied for the angular beamforming performance metrics such as, beam width, the peak to sidelobe ratio (PSLR), and grating lobe limited field of view. The limiting constraints, the physical size of elements, and mutual coupling are also considered. Thinning of fully populated uniform MIMO antenna arrays to form effective uniform sparse arrays (USA), as the term proposed here, are examined as for their capability of improving usable field of view (uFOV), beamwidth (BW), and peak-to-side lobe-ratio (PSLR) using fewer physical antenna elements, simultaneously. Sparse arrays require much less array elements to outperform uniform linear (ULA) and rectangular arrays (URA) for their beamwidths. Further, a rigorious design procedure considering the physical size limitations is currently unavailable. Here, we present a practical design architecture of such a uniform sparse array under multiple contradicting objectives. Angular resolution performances of the novel uniform sparse arrays are compared with the standard ULA and URAs. It is shown that design of an array with small inter-element spacings avoiding any grating lobes is possible even when the physical size of the elements are very large. Expanding the available elements to a much larger apertures provides much better angular resolution. However, it is also shown that these advantages come with the cost of increased side lobes. Both the simulated and the measured results demonstrate the superiority of the proposed uniform sparse array design compared to classical fully populated uniform arrays.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Suleyman Gokhun Tanyer, Paul Dent, Murtaza Ali, Curtis Davis, SenthinelKumar Rajagopal, Peter Driessen. 2022-10-20. Multi-objective Design of Uniform Sparse MIMO Arrays. https://arxiv.org/abs/2210.11597

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Multi-Carrier Rydberg Atomic Quantum Receivers with Enhanced Bandwidth Feature for Communication and Sensing

Rydberg atomic quantum receivers (RAQRs) have attracted significant attention in recent years due to their ultra-high sensitivity. Although capable of precisely detecting the amplitude and phase of weak signals, conventional RAQRs face inherent limitations in accurately receiving wideband RF signals, due to the discrete nature of atomic energy levels and their intrinsic instantaneous bandwidth constraints. These limitations hinder their direct application to multi-carrier communication and sensing. To address this issue, this paper proposes a multi-carrier Rydberg atomic quantum receiver (MC-RAQR) structure with five energy levels. We derive the amplitude and phase of the MC-RAQR and extract the baseband electrical signal for signal processing. In terms of multi-carrier communication and sensing, we analyze the channel capacity and accuracy of angle of arrival (AoA) and distance parameters, respectively. Numerical results validate our proposed model, showing that the MC-RAQR can achieve up to a bandwidth of 11.7 MHz, which is 17-fold larger than the conventional RAQRs. As a result, the channel capacity and the resolution for multi-target sensing are improved significantly. Specifically, the channel capacity of MC-RAQR is 110-fold and 2.8-fold larger than the classical RF receivers and RAQRs, respectively. For sensing performance, the RMSE of AoA estimation for MC-RAQR exhibits 7.6-fold reduction, compared with the conventional RAQRs. Furthermore, the RMSE of distance estimation is $634$-fold smaller than that of the root-CRB of classical RF receivers, showing the superior performance of the MC-RAQR. This demonstrates its compatibility with waveforms such as orthogonal frequency-division multiplexing (OFDM) and its significant advantages for multi-carrier signal reception.

eess.SP

Channel Estimation in MIMO Systems Aided by Microwave Linear Analog Computers (MiLACs)

Microwave linear analog computers (MiLACs) have recently emerged as a promising solution for future gigantic multiple-input multiple-output (MIMO) systems, enabling beamforming with greatly reduced hardware and computational cost. However, channel estimation for MiLAC-aided systems remains an open problem. Conventional least squares (LS) and minimum mean square error (MMSE) estimation rely on intensive digital computation, which undermines the computational advantage offered by MiLACs. In this letter, we propose efficient LS and MMSE channel estimation schemes for MiLAC-aided MIMO systems. By designing the training precoder and combiner implemented by lossless and reciprocal MiLACs, the proposed schemes perform LS and MMSE estimation in the analog domain, leaving only simple digital scaling. They achieve identical estimation performance to their digital counterparts while significantly reducing computational complexity. Numerical results verify the effectiveness of the proposed schemes.

eess.SP

Joint Subcarrier Phase Recovery for Nonlinearity Mitigation

We propose a low-complexity phase recovery scheme that simultaneously mitigates laser phase noise and fiber nonlinearity across several subcarriers. In a long single-span link with Raman amplification, the scheme achieves 0.9 dB gain with 99 real multiplications per complex symbol.

eess.SP