Constrained Partial Group Decoding with Max-Min Fairness for Multi-color Multi-user Visible Light Communication

TL;DR

This paper introduces a novel multi-layer coding and constrained partial group decoding approach for multi-color VLC systems, improving throughput by managing interference and optimizing decoding order.

Contribution

It proposes a new decoding method with a greedy algorithm for max-min fairness, a rate allocation scheme, and a classification-based reduction of decoding complexity in multi-color VLC systems.

Findings

Throughput increases with slight receiver misalignment due to interference reduction.

A greedy algorithm effectively achieves max-min fairness in rate allocation.

The proposed methods improve system performance and decoding efficiency.

Abstract

A visible light communication (VLC) system can adopt multi-color light emitting diode (LED) arrays to support multiple users. In this paper, a multi-layer coding and constrained partial group decoding (CPGD) method is proposed to tackle strong color interference and increase the system throughput. After channel model formulation, user information rates are allocated and decoding order for all the received data layers is obtained by solving a max-min fairness problem using a greedy algorithm. An achievable rate is derived under the truncated Gaussian input distribution. To reduce the decoding complexity, a map on the decoding order and rate allocation is constructed for all positions of interest on the receiver plane and its size is reduced by a classification-based algorithm. Meanwhile, the symmetrical geometry of LED arrays is exploited. Finally, the transmitter-user association problem is formulated and solved by a genetic algorithm. It is observed that the system throughput increases as the receivers are slightly misaligned with corresponding LED arrays due to the reduced interference level, but decreases afterwards due to the weakened link gain.