Adaptive received signal strength-based localization and channel state information estimation model for indoor multiple-input multiple-output visible light communication using the distance vector

Abstract

We propose an adaptive localization and channel state information (CSI) estimation model using the distance vector for indoor multiple-input multiple-output (MIMO) visible light communication (VLC). Under normal conditions, receivers (Rxs) require the CSI of all channels [formed by multiple transmitters (Txs) and multiple Rxs] to recover the original data, and the received signal strength (RSS) obtained from Txs, i.e., light-emitting diodes (LEDs) to predict the Rx’s location. A beacon [or pilot signal (PS)] with CSI is periodically broadcasted from each LED to MIMO Rxs for constructing the CSI matrix and measuring the RSS. However, in an abnormal condition, PSs from one or multiple Txs might not reach Rxs due to shadowing, thus resulting in a failure in positioning and data recovery. To combat this, the proposed model enables the Rx to predict its location without the need for all PSs based on the construction of the distance vectors at Rx. Simulations conducted for two scenarios of user’s mobility, i.e., lattice and random direction mobility, show a low positioning error of ∼0.1 and 0.2 m, respectively. Based on predicted positions, MIMO VLC is capable of fulfilling the CSI matrix and assists the Rx in recovering transmitted data with a very low bit error rate.