When Probabilistic Shaping Realizes Improper Signaling for Hardware Distortion Mitigation

TL;DR

This paper demonstrates that probabilistic shaping can effectively mitigate hardware distortions in communication systems by optimizing symbol probabilities, outperforming traditional uniform and geometric shaping methods.

Contribution

It introduces a novel probabilistic shaping approach for improper signaling to combat hardware distortions, including an iterative optimization algorithm and hybrid shaping design.

Findings

Probabilistic shaping significantly reduces error probability.

Hybrid shaping combines benefits of PS and GS for better performance.

Up to tenfold improvement in throughput and error rates achieved.

Abstract

Hardware distortions (HWD) render drastic effects on the performance of communication systems. They are recently proven to bear asymmetric signatures; and hence can be efficiently mitigated using improper Gaussian signaling (IGS), thanks to its additional design degrees of freedom. Discrete asymmetric signaling (AS) can practically realize the IGS by shaping the signals' geometry or probability. In this paper, we adopt the probabilistic shaping (PS) instead of uniform symbols to mitigate the impact of HWD and derive the optimal maximum a posterior detector. Then, we design the symbols' probabilities to minimize the error rate performance while accommodating the improper nature of HWD. Although the design problem is a non-convex optimization problem, we simplified it using successive convex programming and propose an iterative algorithm. We further present a hybrid shaping (HS) design to gain the combined benefits of both PS and geometric shaping (GS). Finally, extensive numerical results and Monte-Carlo simulations highlight the superiority of the proposed PS over conventional uniform constellation and GS. Both PS and HS achieve substantial improvements over the traditional uniform constellation and GS with up to one order magnitude in error probability and throughput.