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The dissertation aims to analyze different Radio over Fiber systems for the front-haul applications. Particularly, analog radio over fiber (A-RoF) are simplest and suffer from nonlinearities, therefore, mitigating such nonlinearities through digital predistortion are studied. In particular for the long haul A-RoF links, direct digital predistortion...
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... In this context, microwave photonics techniques such as radio over fiber (RoF) systems are the backbone of fed analog or digital signals in optical FH using RoF systems. RoF systems provide cost effective and beneficial solutions by escalating the extent of wireless links for short, medium and long reach networks [3,4]. Other than their significant highlights, such as impunity to electromagnetic interventions, low-loss and broad bandwidth, RoF links are liable to nonlinearities which can be solved using linearization methods [5][6][7]. ...
... Other than their significant highlights, such as impunity to electromagnetic interventions, low-loss and broad bandwidth, RoF links are liable to nonlinearities which can be solved using linearization methods [5][6][7]. RoF has many forms, such as analog radio over fiber (A-RoF) [1,3,4], digital radio over In this context, microwave photonics techniques such as radio over fiber (RoF) systems are the backbone of fed analog or digital signals in optical FH using RoF systems. RoF systems provide cost effective and beneficial solutions by escalating the extent of wireless links for short, medium and long reach networks [3,4]. ...
... RoF has many forms, such as analog radio over fiber (A-RoF) [1,3,4], digital radio over In this context, microwave photonics techniques such as radio over fiber (RoF) systems are the backbone of fed analog or digital signals in optical FH using RoF systems. RoF systems provide cost effective and beneficial solutions by escalating the extent of wireless links for short, medium and long reach networks [3,4]. Other than their significant highlights, such as impunity to electromagnetic interventions, low-loss and broad bandwidth, RoF links are liable to nonlinearities which can be solved using linearization methods [5][6][7]. ...
This paper demonstrates an unprecedented novel neural network (NN)-based digital predistortion (DPD) solution to overcome the signal impairments and nonlinearities in Analog Optical fronthauls using radio over fiber (RoF) systems. DPD is realized with Volterra-based procedures that utilize indirect learning architecture (ILA) and direct learning architecture (DLA) that becomes quite complex. The proposed method using NNs evades issues associated with ILA and utilizes an NN to first model the RoF link and then trains an NN-based predistorter by backpropagating through the RoF NN model. Furthermore, the experimental evaluation is carried out for Long Term Evolution 20 MHz 256 quadraturre amplitude modulation (QAM) modulation signal using an 850 nm Single Mode VCSEL and Standard Single Mode Fiber to establish a comparison between the NN-based RoF link and Volterra-based Memory Polynomial and Generalized Memory Polynomial using ILA. The efficacy of the DPD is examined by reporting the Adjacent Channel Power Ratio and Error Vector Magnitude. 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.
... In this context, microwave photonics techniques such as radio over fiber (RoF) systems are the backbone of fed analog or digital signals in optical FH using RoF systems. RoF systems provide cost effective and beneficial solutions by escalating the extent of wireless links for short, medium and long reach networks [3,4]. Other than their significant highlights, such as impunity to electromagnetic interventions, low-loss and broad bandwidth, RoF links are liable to nonlinearities which can be solved using linearization methods [5][6][7]. ...
... Other than their significant highlights, such as impunity to electromagnetic interventions, low-loss and broad bandwidth, RoF links are liable to nonlinearities which can be solved using linearization methods [5][6][7]. RoF has many forms, such as analog radio over fiber (A-RoF) [1,3,4], digital radio over In this context, microwave photonics techniques such as radio over fiber (RoF) systems are the backbone of fed analog or digital signals in optical FH using RoF systems. RoF systems provide cost effective and beneficial solutions by escalating the extent of wireless links for short, medium and long reach networks [3,4]. ...
... RoF has many forms, such as analog radio over fiber (A-RoF) [1,3,4], digital radio over In this context, microwave photonics techniques such as radio over fiber (RoF) systems are the backbone of fed analog or digital signals in optical FH using RoF systems. RoF systems provide cost effective and beneficial solutions by escalating the extent of wireless links for short, medium and long reach networks [3,4]. Other than their significant highlights, such as impunity to electromagnetic interventions, low-loss and broad bandwidth, RoF links are liable to nonlinearities which can be solved using linearization methods [5][6][7]. ...
... Due to simplicity, cost effective, and already widely spread legacy infrastructure, makes A-RoF a better choice as compared to more efficient and costly solutions such as D-RoF and S-DRoF. 3 Though, by choosing A-RoF, one has to pay the price for improving the performance of A-RoF systems by reducing the nonlinearities in it. ...
... Efficiently reducing these nonlinearities through linearization techniques has critical importance. In previous years, different linearization methods have been proposed, 3,5,6,[14][15][16][17][18][19][20] however, DPD demonstrated itself as a successful technique in mollifying the impairments in RoF systems. [16][17][18] Traditional volterra based methods such as memory polynomial (MP) and generalized MP (GMP) were used successfully in References 16-20 reducing the laser nonlinearities. ...
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. DPD is generally performed with volterra based procedures that utilizes indirect learning architecture (ILA) that can become complex and expensive computationally. 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. 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 efficacy of the DPD is examined by reporting adjacent channel power ratio, mean square error, and error vector magnitude. 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.
... In order to accommodate broadband wireless services from various radio access technologies (RATs), both analog and digital fronthaul architectures have been investigated. Analog-radio over fiber (A-RoF) technologies, the essential block diagram of which can be appreciated in Fig. 2, considering the green (A-RoF) branches, feature low-cost, spectral efficiency, simplicity of realization, and can be applied both in outdoor and in-building scenarios, exploiting different kinds of optical fibers [11][12][13][14][15][16]. However, the A-RoF solution suffers from non-linearities introduced by both microwave and optical parts [17][18][19][20][21][22][23][24][25]. ...
Sigma-delta radio over fiber (ΣΔ-RoF) is an expedient technology for next-generation networks including 5G cloud/centralized radio access networks (C-RAN). In this article, we demonstrate a realistic experimental scenario for ΣΔ-RoF link targeting C-RAN fronthaul
applications, by using baseband second-order 1-bit sigma-delta modulation (ΣΔ-M). The experimental set-up validates the LTE 20 MHz signals having modulation order of 256-quadrature amplitude modulation for a carrier frequency of 3 GHz, up to 10 km of standard single mode fiber. A detailed analysis of the ΣΔ-RoF system performance is reported by adjacent channel leakage ratio and error vector magnitude. Furthermore, an experimental study is evaluated where ΣΔ-RoF is compared with its counterparts. It is deduced that ΣΔ-RoF corroborates the present range of C-RAN fronthaul networks and can be a promising candidate for future mobile haul applications.
We present A-typical machine learning (ML) based digital predistortion (DPD) solution for performance enhancement in analog optical front-hauls (OFH) for internet of things (IoT) based applications. Volterra based DPD has been realized in the past which becomes quite cumbersome due to complexity and choice of coefficients. Whereas the traditional Artificial Neural Networks techniques require time and optimization to determine the best model configuration. The proposed support vector regression (SVR) method is used that alleviates the nonlinearities and uplifts the OFH performance optimally. In this work, the experimental evaluation is made for 5G new radio (NR) signal having 256 quadrature amplitude modulation using 1550 nm Mach Zehnder Modulator and dispersion compensation fiber having 1 km link length. The experimental results suggest that SVR-DPD results in performance enhancement as compared to traditional volterra methods such as generalized memory polynomial, hence proving to be exceptionally operational.
This paper reports the performance evaluation and realization of fifth generation (5G) new radio (NR) multiband signals employing Analog Radio-over-Fiber based optical link as a front haul. The proposed 5G NR signals comprise of 3 GHz flexible waveforms and 23 GHz–400 MHz bandwidth. The EVM performance for the system meets the 3GPP Release 16. Furthermore, EVM performance for received optical power is evaluated up to 400 MHz bandwidth. Besides, we perform an evaluation for coexisting 5G and 4G systems with cleaner and lower EVM in limits for offset greater than 15 MHz.
Machine learning (ML) methodologies gave an innovative and realistic direction to cope up with nonlinearity issues in fiber optics communication. In this paper, a 40-Gb/s signal based Radio over Fiber (RoF) system is experimentally evaluated for 70 km of standard single mode fiber length which utilizes support vector machine (SVM) decision method to indicate an effective nonlinearity mitigation. The influence of different impairments in the system is evaluated that includes the influences of Mach-Zehnder Modulator nonlinearities, in-phase and quadrature phase skew of the modulator, input signal power and noise due to amplified spontaneous emission. By employing SVM, the results demonstrated in terms of bit error rate and eye linearity suggest that impairments are significantly reduced and licit input signal power span of 5dBs is enlarged to 15 dBs.
Recently there is a growing concern regarding potential health hazards linked with 5G deployment and radio frequency emitted by these stations. It becomes fundamentally important to scientifically address these concerns. In this paper, the health risks incorporated with 5G are discussed critically in the light of scientific work and debunk these tittle-tattles where required. We confute scientifically the “5G appeal”, discuss effects of 5G on health, its implications on privacy, pandemics, ecosystem and role of world health organization in fighting these narratives. Finally, we provide future direction to negate these false claims linked with 5G.
