![]() The experimental findings imply that NN‐DPD convincingly learns the RoF nonlinearities which may not suit a volterra based model, and hence may offer a favorable trade‐off in terms of computational overhead and DPD performance. The efficacy of the DPD is examined by reporting adjacent channel power ratio, mean square error, and error vector magnitude. Furthermore, the experimental evaluation is carried out for long term evolution 20‐MHz 256‐QAM modulation signal using 1310 nm distributed feedback laser, and standard single‐mode fiber to establish a comparison between NN based RoF link and volterra based generalized memory polynomial using ILA. The proposed method using NNs evades issues associated with ILA and utilizes a NN to first model the RoF link and then training a NN based predistorter by backpropagating through the RoF NN model. DPD is generally performed with volterra based procedures that utilizes indirect learning architecture (ILA) that can become complex and expensive computationally. This letter presents a novel neural network (NN) based digital predistortion (DPD) technique to obliterate the signal impairments and nonlinearities in radio over fiber (RoF) systems. The optically enabled 14 ULA successfully establishes a 64-QAM wireless communication link at 2.2 Gbaud (13.2 Gbps) while beam steering up to 50° with an error vector magnitude below 7.6%. Additionally, optical beamforming was successfully demonstrated by steering the RAU’s beam towards angles up to 51.8°, without grating lobes. The measured AEs are excellently matched in the GHz band, exhibit high isolation (>15 dB) in the operating band, and feature a stable peak gain of 6.8☐.72 dBi with a beamwidth of at least 95%. The separately packaged OBFN implements true-time-delay beamforming by means of four switchable optical delay lines that are capable of discretely tuning the delay difference between AEs with a resolution of 1.6 ps, up to a maximum delay of 49.6 ps to fully exploit the ULAs full grating-lobe-free scan range. Each AE is compactly integrated and co-optimized with a dedicated opto-electrical transmit chain, maximizing the RAU’s performance, including beamforming flexibility and energy efficiency, while minimizing its size. They adopt an improved aperture-coupled feeding scheme to achieve high efficiency, high isolation and minimal back radiation over a broad frequency band. The antenna elements (AEs) of the ULA are implemented in air-filled substrate integrated-waveguide technology. It leverages an optical beamforming network (OBFN), implemented on a silicon photonics integrated circuit, and a broadband optically enabled 1x4 uniform linear array (ULA. The experimental results are presented in terms of adjacent channel power ratio, error vector magnitude, number of estimated coefficients and multiplications suggesting that MSA‐DPD method achieves a better performance as compared to CPWL and GMP models with much lesser complexity meeting the 3GPP Release 17 requirements.Ī low-complexity and efficient mmWave-over-fiber remote antenna unit (RAU) is proposed for broadband transmission and wide-angle squint-free beam steering in the full GHz n257 5G band. The proposed MSA‐DPD method is compared with the CPWL and generalized memory polynomial method. A dual drive Mach Zehnder modulator having two distinct RF signals modulates a 1310 nm optical carrier using distributed feedback laser for 22 km of standard single mode fiber. The 5G NR standard at 20 GHz with 50 MHz bandwidth and flexible‐waveform signal at 3 GHz with 20 MHz bandwidth is used. The proposed MSA‐DPD method is derived from the canonical piecewise linear (CPWL) based model by employing MSA functions, which can result in reduction of the number of multiplication operations and the model complexity. This paper presents a novel magnitude‐selective affine (MSA) based digital predistortion (DPD) method for the performance investigation of multiband 5G new radio (NR) based analog radio over fiber link.
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