An Effective Spatial Modulation Based Scheme for Indoor VLC Systems

TL;DR

This paper introduces an advanced spatial modulation scheme for indoor visible light communication that improves throughput and spectral efficiency by transmitting decomposed complex symbols with optimized power allocation, outperforming conventional methods.

Contribution

It presents a novel SM-based scheme transmitting decomposed complex symbols with superposition coding and optimized power allocation, enhancing indoor VLC system performance.

Findings

Outperforms conventional SM schemes in spectral efficiency and error rate.

Optimized power allocation significantly improves system performance.

Proposed algorithm converges quickly with superior results.

Abstract

We propose an enhanced spatial modulation (SM)-based scheme for indoor visible light communication systems. This scheme enhances the achievable throughput of conventional SM schemes by transmitting higher order complex modulation symbol, which is decomposed into three different parts. These parts carry the amplitude, phase, and quadrant components of the complex symbol, which are then represented by unipolar pulse amplitude modulation (PAM) symbols. Superposition coding is exploited to allocate a fraction of the total power to each part before they are all multiplexed and transmitted simultaneously, exploiting the entire available bandwidth. At the receiver, a two-step decoding process is proposed to decode the active light emitting diode index before the complex symbol is retrieved. It is shown that at higher spectral efficiency values, the proposed modulation scheme outperforms conventional SM schemes with PAM symbols in terms of average symbol error rate (ASER), and hence, enhancing the system throughput. Furthermore, since the performance of the proposed modulation scheme is sensitive to the power allocation factors, we formulated an ASER optimization problem and propose a sub-optimal solution using successive convex programming (SCP). Notably, the proposed algorithm converges after only few iterations, whilst the performance with the optimized power allocation coefficients outperforms both random and fixed power allocation.