In this letter, we apply the concept of media-based modulation with radio frequency (RF) mirrors to uncoded spacetime labeling diversity (USTLD). Several configurations are investigated. Results demonstrate a significant improvement in the error performance over USTLD and the recently proposed space-time channel modulation for fast frequency-flat Rayleigh fading channels with and without channel estimation error. Improvement is also shown for the quasi-static channel case. The analytical average bit error probability is formulated for the scheme and is shown to agree well with Monte Carlo simulation results at moderate-to-high signal-to-noise ratios. Furthermore, the detection computational complexity of each configuration is analysed in terms of the number of real operations.

Uncoded space-time labeling diversity (USTLD) is a space-time block coded (STBC) system with labeling diversity applied to it to increase wireless link reliability without compromising the spectral efficiency. USTLD achieves higher link reliability relative to the traditional Alamouti STBC system. This work aims to design a bandwidth-efficient and blind wireless channel estimator for the USTLD system. Tra-ditional channel estimation techniques like the least-squares (LS) and the minimum mean squared error (MMSE) methods are generally inefficient in using the channel bandwidth. The LS and MMSE channel es-timation schemes require the prior knowledge of transmitted pilot symbols and/or channel statistics, together with the receiver noise variance, for channel estimation. A neural network machine learning (NN-ML) chan-nel estimator with transmit power-sharing is proposed to facilitate blind channel estimation for the USTLD system and to minimize the required channel estimation bandwidth utilization. We mathematically model the equivalent noise power and derive the optimal transmit power fraction that minimizes the channel estimation bandwidth utilization. The blind NN-ML channel estimator with transmit power-sharing is shown to utilize 20% of the LS and MMSE wireless channel estimators’ bandwidth to achieve the same bit error rate (BER) performance for the USTLD system in the case of 16-QAM and 16-PSK modulation.

Streaming QR codes is an optical wireless communication (OWC) technology that uses screen-camera communication (SCC) with dynamic QR codes for visible light communication (VLC). At a basic level, VLC uses a light-emitting diode (LED) and photodiode (PD) pair to establish the wireless link required for optical communication. SCC leverages the millions of LEDs and PDs in its screen and camera pair to establish millions of wireless links resembling massive multiple-input multiple-output in radio frequency (RF) communication. SCC technology is constrained by limits in current optoelectronic equipment such as screen refresh rate, rolling shutter and LED blink frequency. Overcoming these hurdles would provide access to tera Hertz of unlicensed optical spectrum easing the burden on scarce RF resources. Smartphone-based SCC using streaming QR codes is a promising technology for short-range wireless communication. The various smartphones, screens and cameras in use today can be leveraged for seamless information transfer between physical and virtual realities. The body of knowledge for SCC is substantial yet dispersed therefore this paper presents a survey on streaming QR codes as an SCC variant. The purpose of this survey is to provide a well-structured consolidation of the literature on SCC with emphasis on streaming QR codes to aid future studies. It describes the symbology enhancements for improved throughput in streaming QR codes where reports have shown up to 24-times data storage improvements and 900 kbps achievable throughput. It further demonstrates that eliminating distortion can result in 7.6673 Mbps achievable throughput.