Achievable information rates calculation for optical OFDM few-mode fiber long-haul transmission systems

Abstract

We propose a method to estimate the lower bound of achievable information rates (AIRs) of high speed orthogonal frequency-division multiplexing (OFDM) in spatial division multiplexing (SDM) optical long-haul transmission systems. The estimation of AIR is based on the forward recursion of multidimensional super-symbol efficient sliding-window Bahl-Cocke-Jelinek-Raviv (BCJR) algorithm. We consider most of the degradations of fiber links including nonlinear effects in few-mode fiber (FMF). This method does not consider the SDM as a simple multiplexer of independent data streams, but provides a super-symbol version for AIR calculation over spatial channels. This super-symbol version of AIR calculation algorithm, in principle, can be used for arbitrary multiple-input-multiple-output (MIMO)-SDM system with channel memory consideration. We illustrate this method by performing Monte Carlo simulations in a complete FMF model. Both channel model and algorithm for calculation of the AIRs are described in details. We also compare the AIRs results for QPSK/16QAM in both single mode fiber (SMF)- and FMF-based optical OFDM transmission.

Recent Advances in DSP Techniques for Mode Division Multiplexing Optical Networks with MIMO Equalization: A Review

“…The high-speed orthogonal frequency-division multiplexing (OFDM) in SDM optical long-haul transmission systems serves as another important aspect of MIMO equalization techniques [36]. The complex multiplications per bit for various equalizer types in terms of modal dispersion for a 2000-km transmission distance and 10 × 10 MIMO is shown in Figure 10, where an FMF with three modes with two polarizations (LP 01 , LP 11a , LP 11b , LP 21a , LP 21b ) results in the number of tributaries being 10.…”

Improved Lower Bounds on Mutual Information Accounting for Nonlinear Signal–Noise Interaction

“…We have taken uniform sampling of these particles to form a distribution. There exist other approaches such as nonuniform quantization [8] to estimate the PDFs. 6 There is residual memory left after SBS-SDBP [28] as matched filter followed by sampling is a linear technique and may not be the optimal processing for the nonlinear fiber-optic channel [32], [33].…”

“…The complexity of this simulationbased technique increases exponentially with channel memory and requires knowledge of the channel model. There are at least three different ways in which the problem of the exponential memory for the BCJR algorithm is currently addressed: limiting the memory by truncation [7], [8]; using digital backpropagation (DBP) before the BCJR algorithm [11], [12]; or using low-complexity variations of the BCJR algorithm to reduce the complexity. By employing one of these techniques, the information rate obtained will be a lower bound on the maximum achievable information rate.…”

“…For the fiber-optic channel, the most commonly used approach to lower-bound the MI is to approximate the original forward channel with an auxiliary forward channel [5], [7], [8], [10], [13], [19]- [21]. A receiver that is optimal for an auxiliary forward channel is used to process the data generated from the original forward channel and to compute an information rate.…”

Capacity achieving nonbinary LDPC coded non-uniform shaping modulation for adaptive optical communications

“…The system diagram and coded modulation blocks are presented in Section 2. Section 3 described proposed the mutual information directed constellation design with non-uniform shaping [8][9][10][11]. In Section 4, the generalized nonbinary LDPC code is studied for the matched size constellations, generalized in the sense that it is applicable to any prime power.…”