Joint Space Time Coding on RIS for Simultaneous Direct Modulation and Beamforming

TL;DR

This paper introduces a joint space-time coding method for RIS that enables simultaneous direct modulation and beamforming, improving communication efficiency and reducing error rates in RIS-based systems.

Contribution

It proposes a novel XOR-based joint space-time coding technique for RIS, enabling concurrent direct modulation and beamforming functionalities.

Findings

Significant reduction in bit error rate (BER) with joint coding.

55% reduction in rmsEVM of the constellation diagram.

Effective implementation demonstrated through fabricated RIS prototype.

Abstract

Reconfigurable Intelligent Surface (RIS)-based direct modulation communication systems have garnered significant attention due to their low cost, low power consumption, and baseband-less characteristics. However, these systems face challenges such as the random time-varying coding state of the RIS and the difficulty in implementing beamforming in direct modulation. In this paper, we propose a simple and effective joint space-time coding approach for RIS that enables simultaneous realization of both direct modulation communication and beamforming. By modeling the transmitted signals of the RIS using space-time coding, we show that the time coding determines the direct modulation functionality, while the space coding governs the beamforming. Consequently, we introduce a joint time-space coding technique by performing exclusive-or (XOR) operations on the time and space coding sequences, enabling both functionalities to be achieved concurrently. Numerical simulations demonstrate the effectiveness of the proposed method. Furthermore, we design and fabricate a transmissive 1-bit phase reconfigurable RIS operating in the 3.4~3.79 GHz frequency band for the implementation of a direct modulation communication system. Experimental results reveal that the bit error rate (BER) is significantly reduced when joint space-time coding is used, compared to using time coding alone. Additionally, the root-mean-square error vector magnitude (rmsEVM) of the constellation diagram is reduced by 55%. This technique is promising for applications in the Internet of Things (IoT), contributing to the development of intelligent networks for electronic devices.