Applying Sparse Array in Massive MIMO via Convex optimization

Lou, Mengting; Jin, Jing; Wang, Hanning; Wang, Xinbo; Yuan, Yifei

doi:10.1109/apmc47863.2020.9331675

Cited by 2 publications

(2 citation statements)

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“…Sophisticated beamforming and precoding were studied in [18][19][20]. The use of irregular arrays for MaMIMO systems was discussed in [21,22], and several synthesis algorithms have been proposed in the literature to solve this task effectively [23][24][25][26][27][28]. Another promising approach is the abandoning of the "cell" concept in the so-called cell-free massive MIMO [29][30][31].…”

Section: Introductionmentioning

confidence: 99%

Controllable Local Propagation Environment to Maximize the Multiplexing Capability of Massive MIMO Systems

et al. 2023

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The capability of controlling and modifying wireless propagation channels is one of the prerogatives of beyond-5G systems. In this paper, we propose the use of a controllable local propagation environment surrounding the terminals, and analyze its positive effect on the multiplexing capability of massive MIMO systems. In particular, we focus on using a few switched passive elements surrounding each terminal. In this way, the modification of the propagation environment is not realized by means of a single structure, as in reconfigurable intelligent surfaces (RIS), but is achieved by the cooperative work of all the terminals. By employing numerical simulations, we show that the proposed system outperforms its non-reconfigurable counterpart in terms of the number of contemporary connected users. Moreover, the optimized system enables a substantial increase in the minimum received power by the terminals, thus guaranteeing superior channel fairness.

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Section: Introductionmentioning

confidence: 99%

Controllable Local Propagation Environment to Maximize the Multiplexing Capability of Massive MIMO Systems

et al. 2023

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“…This array achieved a lower peak side lobe level (PSLL) and narrower 3 dB beam width with 8 fewer elements compared to the corresponding 16-element uniform linear array (ULA). M. Lou et al adopted the single pattern convex optimization (CO)-based synthesis and evaluated the system performance of the sparse arrays in mobile communication [20]. Further, they proposed a synthesis based on joint convex optimization (JCO) to construct a codebook for beamforming.…”

Section: Introductionmentioning

confidence: 99%

A Sparse Design for Aperture-Level Simultaneous Transmit and Receive Arrays

Wei

Xie

et al. 2022

Electronics

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The aperture-level simultaneous transmit and receive (ALSTAR) system uses full digital architecture with an observation channel to achieve remarkably effective isotropic isolation (EII). However, the number of observation channels must be the same as the number of transmit channels, which increases the system’s complexity. To balance the system cost and performance of the ALSTAR, this paper proposes a joint design of sparse arrays and beamforming, which are achieved by a genetic algorithm and an alternating optimization algorithm, respectively. In the sparse design, we introduce beamforming technology to guarantee the EII while decreasing the corresponding elements of observation channel that contribute slightly to the EII. The simulation results are presented for a 32-element array that achieves 185.87 dB of the EII with 1000 W of transmit power. In the cases of sparsity rates at 0.875 and 0.75 (≥0.6), i.e., the number of observation channels decreases by 12.5% (2/16) and 25% (4/16), the reductions in EII do not exceed 1 dB and 3 dB, respectively. However, the EII decreases rapidly with a sparsity rate less than 0.25. Results demonstrate that our proposed joint design of sparse arrays and beamforming can reduce the system cost with little performance loss of EII.

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Applying Sparse Array in Massive MIMO via Convex optimization

Cited by 2 publications

References 10 publications

Controllable Local Propagation Environment to Maximize the Multiplexing Capability of Massive MIMO Systems

Controllable Local Propagation Environment to Maximize the Multiplexing Capability of Massive MIMO Systems

A Sparse Design for Aperture-Level Simultaneous Transmit and Receive Arrays

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