Optimal Discrete Constellation Inputs for Aggregated LiFi-WiFi Networks

TL;DR

This paper analyzes and optimizes the performance of an aggregated LiFi-WiFi system with discrete constellation inputs, introducing novel rate expressions and optimization schemes that significantly improve achievable data rates.

Contribution

It derives the first achievable rate expressions for practical aggregated LiFi-WiFi systems with discrete inputs and proposes new optimization algorithms for rate maximization.

Findings

Optimized strategies outperform state-of-the-art schemes in achievable rate.

Proposed power allocation scheme enhances system performance.

Efficient algorithms balance computational complexity and transmission quality.

Abstract

In this paper, we investigate the performance of a practical aggregated LiFi-WiFi system with the discrete constellation inputs from a practical view. We derive the achievable rate expressions of the aggregated LiFi-WiFi system for the first time. Then, we study the rate maximization problem via optimizing the constellation distribution and power allocation jointly. Specifically, a multilevel mercy-filling power allocation scheme is proposed by exploiting the relationship between the mutual information and minimum mean-squared error (MMSE) of discrete inputs. Meanwhile, an inexact gradient descent method is proposed for obtaining the optimal probability distributions. To strike a balance between the computational complexity and the transmission performance, we further develop a framework that maximizes the lower bound of the achievable rate where the optimal power allocation can be obtained in closed forms and the constellation distributions problem can be solved efficiently by Frank-Wolfe method. Extensive numerical results show that the optimized strategies are able to provide significant gains over the state-of-the-art schemes in terms of the achievable rate.