IRS-assisted millimeter-wave massive MIMO with transmit antenna selection for IoT networks

Elganimi, Tassir Y, Rabie, Khaled M ORCID: https://orcid.org/0000-0002-9784-3703 and Nauryzbayev, Galymzhan (2023) IRS-assisted millimeter-wave massive MIMO with transmit antenna selection for IoT networks. In: 2023 IEEE 97th Vehicular Technology Conference, 20 June 2023 - 23 June 2023, Florence, Italy.

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Abstract

An intelligent reflecting surface (IRS)-assisted millimeter-wave (mmWave) massive multiple input multiple output (MIMO) system with transmit antenna selection (TAS) using orthogonal space-time block codes (OSTBC) scheme is proposed in this paper. This system combines TAS and IRS with hybrid analog-digital beamforming (HBF) for 60 GHz mmWave communications in order to exploit the benefits of TAS, OSTBC, analog beamforming (ABF), and transmit digital precoding techniques. The proposed system, however, benefits from the transmit diversity gain of OSTBC scheme as well as from the signal-to-noise ratio (SNR) gains of both the beamformer and the IRS technology. The simulation results show that TAS-OSTBC system with zero-forcing precoding outperforms the conventional TAS-OSTBC scheme. Furthermore, the bit error rate (BER) performance significantly improves as the number of antenna array elements increases due to providing a beamforming gain. In addition, increasing the number of reflecting elements further enhances the BER performance. It is also found from the simulation results that the TAS-OSTBC system with hybrid precoding has better performance than that of TAS-OSTBC with ABF, and IRS-assisted systems significantly outperform the conventional systems without the IRS technology. This makes the proposed IRS-assisted system an appealing solution for internet-of-things (IoT) networks.