Handling nonlinear power amplifiers in massive MIMO : system-level tradeoffs

With the rapid growth of mobile communication systems, massive multiple-input multiple-output (MIMO) technology plays a key role in enhancing communication systems to meet growing data traffic demands. However, scaling the technology further challenges the system designers to balance design tradeoffs in order to provide efficient and low-cost communication systems. This requires efficient hardware as well as low-complexity digital signal processing techniques at the physical layer. Power amplifiers are most critical components in radio transmitters as they account for most of the power consumption and contribute significantly to system cost and complexity. Although massive MIMO reduces the per-antenna transmit power requirement, achieving high efficiency in power amplifiers remains a challenge due to the trade-off between efficiency and linearity and signal attributes such as high peak-to-average power ratio. This work investigates the behavior of PAs in this regard particularly the nonlinear distortion emissions from base stations and explores the digital signal processing methods that improve PA efficiency in OFDM based massive MIMO systems. Linear precoding techniques have been considered in frequency-selective channels scenario with a particular emphasis on low complexity signal peak reduction methods that exploit the large number of antennas. By combining distortion-based peak reduction methods with compensation strategies and regularized precoding, the proposed approach mitigates the performance loss associated with such methods in the presence of nonlinear PAs. The results demonstrate improved performance while maintaining low complexity, enabling the use of cost-effective and low-power analog components. The findings contribute towards the development of more sustainable and energy-efficient massive MIMO networks, supporting future wireless communication systems that improve both performance and efficiency.