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On the Bit Error Probability of DMA-Based Systems

Nemanja Stefan Perović

Abstract

Dynamic metasurface antennas (DMAs) are an alternative application of metasurfaces as active reconfigurable antennas with advanced analog signal processing and beamforming capabilities, which have been proposed to replace conventional antenna arrays for next generation transceivers. Motivated by this, we investigate the bit error probability (BEP) optimization in a DMA-based system, propose an iterative optimization algorithm, which adjusts the transmit precoder and the weights of the DMA elements, prove its convergence and derive complexity.

On the Bit Error Probability of DMA-Based Systems

Abstract

Dynamic metasurface antennas (DMAs) are an alternative application of metasurfaces as active reconfigurable antennas with advanced analog signal processing and beamforming capabilities, which have been proposed to replace conventional antenna arrays for next generation transceivers. Motivated by this, we investigate the bit error probability (BEP) optimization in a DMA-based system, propose an iterative optimization algorithm, which adjusts the transmit precoder and the weights of the DMA elements, prove its convergence and derive complexity.
Paper Structure (11 sections, 1 theorem, 26 equations, 1 figure)

This paper contains 11 sections, 1 theorem, 26 equations, 1 figure.

Table of Contents

  1. Introduction
  2. System Model and Problem Formulation
  3. DMA Model
  4. System Model
  5. Problem Formulation
  6. Proposed Optimization Method
  7. Convergence and Complexity Analysis
  8. Convergence Analysis
  9. Complexity Analysis
  10. Simulation Results
  11. Conclusion

Key Result

Lemma 1

The gradient of $f(\mathbf{Q},\mathbf{p})$ w.r.t. $\mathbf{Q}^{*}$ and $\mathbf{p}^{*}$ are given by where $\mathop{\mathrm{vec}}\nolimits_{d}(\mathbf{X})$ denotes a column-vector whose elements are the diagonal elements of $\mathbf{X}$.

Figures (1)

  • Figure 1: BEP for different size of symbol alphabet ($M$) and number of microstrips ($N_{d}$).

Theorems & Definitions (1)

  • Lemma 1