Volterra series

About: Volterra series is a research topic. Over the lifetime, 2731 publications have been published within this topic receiving 46199 citations.

An Overview of Volterra Series Based Behavioral Modeling of RF/Microwave Power Amplifiers

Abstract: This paper presents an overview of recently-developed, simplified Volterra series based, behavioral modeling approaches for radio frequency and microwave power amplifiers. Various model topologies and model pruning strategies are discussed, together a presentation of their comparative advantages and limitations.

On transfer function representations for homogeneous nonlinear systems

Abstract: For stationary, homogeneous, nonlinear systems described via the Volterra functional representation, the Laplace transform of the system kernel is commonly used as a "transfer function." Corresponding to the symmetric and triangular forms of the kernel, special forms are obtained for the transfer function. We propose a new form for both the time-domain and transform-domain representation of homogeneous systerns. Properties of these so-called regular forms in relation to the other two forms and in regard to input/output computation, stability, and bilinear realization theory are discussed.

Soft-Demapping for Short Reach Optical Communication: A Comparison of Deep Neural Networks and Volterra Series

Abstract: In optical fiber communication, optical and electrical components introduce nonlinearities, which require effective compensation to attain highest data rates. In particular, in short reach communication, components are the dominant source of nonlinearities. Volterra series are a popular countermeasure for receiver-side equalization of nonlinear component impairments and their memory effects. However, Volterra equalizer architectures are generally very complex. This article investigates soft deep neural network (DNN) architectures as an alternative for nonlinear equalization and soft-decision demapping. On coherent 92GBd dual polarization 64QAM back-to-back measurements performance and complexity is experimentally evaluated. The proposed bit-wise soft DNN equalizer (SDNNE) is compared to a 5th order Volterra equalizer at a 15% overhead forward error correction (FEC) limit. At equal performance, the computational complexity is reduced by 65%. At equal complexity, the performance is improved by 0.35 dB gain in optical signal-to-noise-ratio (OSNR).

An Efficient Scheme for Nonlinear Modeling and Predistortion in Mixed-Signal Systems

Abstract: A novel identification and predistortion scheme of weakly nonlinear systems for mixed-signal devices, which takes into account practical implementation aspects, is presented. It is well known that for the identification of weakly nonlinear systems, despite the spectral regrowth, it suffices to sample the input-output (I/O) data of the system at the Nyquist rate of the input signal. Many applications such as linearization and mixed-signal simulations require system models at a higher sampling rate than Nyquist. Up to now, the construction of such high-rate models has been done by oversampling the corresponding I/O data. This leads to high computational complexity, ill posedness of the estimation, and high demand on the analog-to-digital-converter sampling rate for the implementation. This brief discusses an efficient way to obtain high-rate models and predistorters from low-rate models and shows the validity of the proposed scheme for a very-high-speed-digital-subscriber-line power amplifier, where an adjacent channel power supression of 20 dB is achieved

200-m/500-Mbps underwater wireless optical communication system utilizing a sparse nonlinear equalizer with a variable step size generalized orthogonal matching pursuit.

Abstract: Linear and nonlinear impairments in underwater wireless optical communication (UWOC) systems caused by the limited bandwidth and nonlinearity of devices severely degrade the system performance. In this paper, we propose a sparse Volterra series model-based nonlinear post equalizer with greedy algorithms to mitigate the nonlinear impairments and the inter-symbol interference (ISI) in a UWOC system. A variable step size generalized orthogonal matching pursuit (VSgOMP) algorithm that combines generalized orthogonal matching pursuit (gOMP) and adaptive step size method is proposed and employed to compress the Volterra equalizer with low computational cost. A maximum data rate of 500 Mbps is realized with the received optical power of −32.5 dBm in a 7-m water tank. In a 50-m swimming pool, a data rate of 500 Mbps over 200-m underwater transmission is achieved with a BER lower than the forward error correction (FEC) threshold of 3.8 × 10−3. The number of kernels of the sparse Volterra equalizer is reduced to 70% of that of the traditional Volterra equalizer without significant BER performance degradation. Compared with orthogonal matching pursuit (OMP) scheme and regularized orthogonal match pursuit (ROMP) scheme, the VSgOMP scheme reduces the running time by 68.6% and 29.2%, respectively. To the best of our knowledge, this is the first time that a sparse Volterra equalizer combined with VSgOMP algorithm is employed for the nonlinear equalization in a long-distance high-speed UWOC system.