Papers for
telecommunications system designers
Papers whose findings have a practical use for this group, as judged from the abstract. Open a paper to read what it means in practice.
Efficient nonlinear self-interference cancellation with uplink training
Pilot-Projected Nonlinear Self-Interference Estimation with Simultaneous Uplink Training
Abstract: This paper considers nonlinear digital self-interference (SI) cancellation and uplink-channel estimation for single-antenna in-band full-duplex radios when a desired uplink pilot is present during SI training. In this setting, a rich nonlinear SI dictionary can absorb part of the structured pilot response, while its large and correlated set of basis functions can make reliable SI estimation difficult, particularly with limited training. During SI-coefficient estimation, we treat the unknown uplink channel as a nuisance parameter and eliminate it to obtain an equivalent reduced SI estimation problem on the orthogonal complement of the pilot convolution subspace. Since the projected nonlinear dictionary can remain ill conditioned, we develop two complementary full-dictionary estimators: a pilot-projected ridge estimator with Bayesian-information-criterion tuning (PP-RidgeBIC), which uses global ridge shrinkage, and a pilot-projected group-sparse Bayesian estimator (PP-GSBE), which learns branch-dependent Bayesian shrinkage from the data. These estimators offer two complementary operating points: PP-RidgeBIC favors computational efficiency, whereas PP-GSBE provides greater adaptivity to heterogeneous nonlinear SI components. Simulations show substantial gains in SI cancellation and uplink reception over non-projected and hard-selection alternatives; notably, PP-GSBE suppresses the residual SI below the noise floor with moderate training and consistently provides the strongest performance under nonlinear model mismatch.
Capacity bounds improve optical channel limits under power rules
Capacity Bounds for Optical Interference Channels Subject to Average Power Constraints
Abstract: Accurate information-theoretic analysis of multiuser wavelength-division multiplexed (WDM) optical links is complicated by Kerr nonlinearity and chromatic dispersion. Existing capacity bounds for first-order regular perturbative (RP) channel models have relied on per-symbol peak power constraints to simplify the underlying extremal analysis. In this paper, we replace these peak constraints with the more practically relevant average input power constraints and study the resulting RP WDM interference channel. Unlike the peak-constrained formulation, an exact finite signal-to-noise ratio (SNR) analysis under average power leads in general to a nonconvex, high-dimensional optimization problem with no closed-form solution. We show that the problem admits a tractable characterization in the high-SNR regime. Using a genie-aided argument, we derive closed-form single-user high-SNR capacity bounds for the RP interference channel and identify constant-amplitude interferer signaling as extremal. Furthermore, under an empirically validated non-negativity condition on the dominant RP kernels and within a truncated first-order RP model, we establish a finite-SNR extremality result, yielding a single-user capacity characterization within the RP model under average power constraints. Building on these single-user corner points, we construct an all-helpsone achievable region via time sharing, which strictly improves upon treating nonlinear interference as noise. Numerical results and split-step Fourier simulations of the nonlinear Schrodinger equation channel confirm that the qualitative conclusions persist over practical launch powers. The results provide new insight into extremal signaling and multiuser trade-offs for nonlinear WDM systems within the RP approximation.