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RIS-Assisted OTFS Communications: Phase Configuration via Received Energy Maximization

Mohamad H. Dinan, Arman Farhang

TL;DR

The paper tackles the challenge of enhancing high-speed wireless downlink performance by integrating RIS with OTFS modulation and proposes a DD-domain phase-shift design to maximize received energy. A gradient-based algorithm, leveraging Wirtinger calculus and a convex relaxation, computes RIS phase configurations that collect energy from all cascaded DD taps across the OTFS block, with complexity reduced by exploiting sparsity and the BC structure. Numerical results demonstrate substantial BER/Gain improvements over benchmark SCP and random phase configurations, with gains exceeding 4 dB and increasing with more RIS elements, including across standard channels like 3GPP TDL-C at high speeds. The approach highlights the potential of RIS to bolster OTFS in dynamic, high-speed scenarios, supporting future 6G deployments.

Abstract

In this paper, we explore the integration of two revolutionary technologies, reconfigurable intelligent surfaces (RISs) and orthogonal time frequency space (OTFS) modulation, to enhance high-speed wireless communications. We introduce a novel phase shift design algorithm for RIS-assisted OTFS, optimizing energy reception and channel gain in dynamic environments. The study evaluates the proposed approach in a downlink scenario, demonstrating significant performance improvements compared to benchmark schemes in the literature, particularly in terms of bit error rate (BER). Our results showcase the potential of RIS to enhance the system's performance. Specifically, our proposed phase shift design technique outperforms the benchmark solutions by over 4 dB. Furthermore, even greater gains can be obtained as the number of RIS elements increases.

RIS-Assisted OTFS Communications: Phase Configuration via Received Energy Maximization

TL;DR

The paper tackles the challenge of enhancing high-speed wireless downlink performance by integrating RIS with OTFS modulation and proposes a DD-domain phase-shift design to maximize received energy. A gradient-based algorithm, leveraging Wirtinger calculus and a convex relaxation, computes RIS phase configurations that collect energy from all cascaded DD taps across the OTFS block, with complexity reduced by exploiting sparsity and the BC structure. Numerical results demonstrate substantial BER/Gain improvements over benchmark SCP and random phase configurations, with gains exceeding 4 dB and increasing with more RIS elements, including across standard channels like 3GPP TDL-C at high speeds. The approach highlights the potential of RIS to bolster OTFS in dynamic, high-speed scenarios, supporting future 6G deployments.

Abstract

In this paper, we explore the integration of two revolutionary technologies, reconfigurable intelligent surfaces (RISs) and orthogonal time frequency space (OTFS) modulation, to enhance high-speed wireless communications. We introduce a novel phase shift design algorithm for RIS-assisted OTFS, optimizing energy reception and channel gain in dynamic environments. The study evaluates the proposed approach in a downlink scenario, demonstrating significant performance improvements compared to benchmark schemes in the literature, particularly in terms of bit error rate (BER). Our results showcase the potential of RIS to enhance the system's performance. Specifically, our proposed phase shift design technique outperforms the benchmark solutions by over 4 dB. Furthermore, even greater gains can be obtained as the number of RIS elements increases.
Paper Structure (5 sections, 18 equations, 5 figures, 2 algorithms)

This paper contains 5 sections, 18 equations, 5 figures, 2 algorithms.

Table of Contents

  1. Introduction
  2. System Model
  3. Proposed Phase Shifts Design
  4. Numerical Results
  5. Conclusion

Figures (5)

  • Figure 1: An RIS-assisted OTFS setup.
  • Figure 2: Effect of increasing number of RIS elements on the average channel gain in RIS-assisted OTFS systems; here, $N=16$ and $M=32$.
  • Figure 3: Convergence rate of the optimization algorithm; here, $L=32$, $N=16$ and $M=32$.
  • Figure 4: BER performance for $N=16$, and $M=32$, (a) channel with equal average tap gains, and (b) channel with unequal average tap gains.
  • Figure 5: BER performance of RIS-assisted OTFS systems in the TDL-C channel; here, $N=16$, $M=128$, and 4-QAM modulation is used.