Digital predistortion of a full-duplex Radio-over-Fiber mobile fronthaul link with feedback loop

Mateo, Carlos; Clemente, Jesús; García-Dúcar, Paloma; Carro, Pedro L.; Mingo, J. de; Salinas, Í.

doi:10.1109/iwcmc.2017.7986493

Cited by 9 publications

(14 citation statements)

References 15 publications

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“…The table summarizes the method employed, type of linearization, category, parameters evaluated, advantages and disadvantages of respective methods. Along with the numerous techniques listed above, mitigation of the impairments of RoF system have also been studied previously [24][25][26][27][28][29][30][31][32][33][34][35]. A feedforward scheme has also been analyzed [26,27] but is complex and to counter these problems, optical methods such as dual parallel modulation [28], mixed polarization [29,30], etc.…”

Section: Literature Reviewmentioning

confidence: 99%

“…It can also emulate the nonlinear behavior of Power Amplifiers to an extent which is why it has been used to model Power Amplifiers previously. The equation is as follows [24][25][26][27][28][29][30][31][32][33][34][35]:…”

Section: Memory Polynomial Model (Mp)mentioning

confidence: 99%

“…Here, we will now use it to aid linearization of RoF links using the Digital predistortion method. If we observe the equation below, we see that, the GMP model, in contrast with MP, holds both, memory of diagonal terms along with crossing terms as well, which is why it outperforms MP and in the coming sections, we will evaluate comparisons with GMP only having established it is superior to MP [1,[24][25][26][27][28][29][30][31][32][33][34][35]:…”

Section: Generalized Memory Polynomial (Gmp)mentioning

confidence: 99%

“…However, "out of the box" approach which can achieve better performance is always interesting addition to the topic. Recently, it was shown in [26][27][28] that out of all the possible architectures, CPWL method outperforms the other models such as memory polynomial (MP) and generalized memory polynomial (GMP). CPWL is an obvious choice due to the performance enhancement that it brings, however it has a lot of complexity and overheads.…”

Section: Models Based On Canonical Piece Wise Linearizationmentioning

confidence: 99%

“…CPWL is an obvious choice due to the performance enhancement that it brings, however it has a lot of complexity and overheads. The CPWL model can be expressed as [28]:…”

Section: Models Based On Canonical Piece Wise Linearizationmentioning

confidence: 99%

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Experimental Demonstration and Performance Enhancement of 5G NR Multiband Radio over Fiber System Using Optimized Digital Predistortion

et al. 2021

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This paper presents an experimental realization of multiband 5G new radio (NR) optical front haul (OFH) based radio over fiber (RoF) system using digital predistortion (DPD). A novel magnitude-selective affine (MSA) based DPD method is proposed for the complexity reduction and performance enhancement of RoF link followed by its comparison with the canonical piece wise linearization (CPWL), decomposed vector rotation method (DVR) and generalized memory polynomial (GMP) methods. Similarly, a detailed study is shown followed by the implementation proposal of novel neural network (NN) for DPD followed by its comparison with MSA, CPWL, DVR and GMP methods. In the experimental testbed, 5G NR standard at 20 GHz with 50 MHz bandwidth and flexible-waveform signal at 3 GHz with 20 MHz bandwidth is used to cover enhanced mobile broad band and small cells scenarios. A dual drive Mach Zehnder Modulator having two distinct radio frequency signals modulates a 1310 nm optical carrier using distributed feedback laser for 22 km of standard single mode fiber. The experimental results are presented in terms of adjacent channel power ratio (ACPR), error vector magnitude (EVM), number of estimated coefficients and multiplications. The study aims to identify those novel methods such as MSA DPD are a good candidate to deploy in real time scenarios for DPD in comparison to NN based DPD which have a slightly better performance as compared to the proposed MSA method but has a higher complexity levels. Both, proposed methods, MSA and NN are meeting the 3GPP Release 17 requirements.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Memory Polynomial Model (Mp)mentioning

confidence: 99%

Section: Generalized Memory Polynomial (Gmp)mentioning

confidence: 99%

Section: Models Based On Canonical Piece Wise Linearizationmentioning

confidence: 99%

“…CPWL is an obvious choice due to the performance enhancement that it brings, however it has a lot of complexity and overheads. The CPWL model can be expressed as [28]:…”

Section: Models Based On Canonical Piece Wise Linearizationmentioning

confidence: 99%

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