Spectral and Energy Efficiency of IRS-Assisted MISO Communication with Hardware Impairments
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Abstract (arXiv)
In this letter, we analyze the spectral and energy efficiency of an intelligent reflecting surface (IRS)-assisted multiple-input single-output (MISO) downlink system with hardware impairments. An extended error vector magnitude (EEVM) model is utilized to characterize the impact of radio-frequency (RF) impairments at the access point (AP) and phase noise is considered for the imperfect IRS. We show that the spectral efficiency is limited due to the hardware impairments even when the numbers of AP antennas and IRS elements grow infinitely large, which is in contrast with the conventional case with ideal hardware. Moreover, the performance degradation at high SNR is shown to be mainly affected by the AP hardware impairments rather than the phase noise of IRS. We further obtain the optimal transmit power in closed form for energy efficiency maximization. Simulation results are provided to verify these results.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). First posted on arXiv 21 Apr 2020.
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Citing papers per year: 2024: 2; 2025: 1.
3 papers.
- 2024IRS-Enhanced Secure Semantic Communication Networks: Cross-Layer and Context-Awared Resource Allocationcited by 1
- 2024Reinforcement Learning for Rate Maximization in IRS-aided OWC Networkscited by 0
- 2025Adaptive Learning for IRS-Assisted Wireless Networks: Securing Opportunistic Communications Against Byzantine Eavesdropperscited by 0
- 2025Adaptive Learning for IRS-Assisted Wireless Networks: Securing Opportunistic Communications Against Byzantine Eavesdroppers11 Aug 2025
- 2024IRS-Enhanced Secure Semantic Communication Networks: Cross-Layer and Context-Awared Resource Allocation4 Nov 2024
- 2024Reinforcement Learning for Rate Maximization in IRS-aided OWC Networks7 Sep 2024