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Coded Water-Filling for Multi-User Interference Cancellation

Yuan Li, Zicheng Ye, Huazi Zhang, Jun Wang, Jianglei Ma, Wen Tong

TL;DR

The analysis reveals the capacity gains achievable through early termination and power allocation techniques in multi-user settings and shows that coded water-filling is instrumental for further improving spectral efficiency in crowded spectrums.

Abstract

In this paper, we study the system-level advantages provided by rateless coding, early termination and power allocation strategy for multiple users distributed across multiple cells. In a multi-cell scenario, the early termination of coded transmission not only reduces finite-length loss akin to the single-user scenario but also yields capacity enhancements due to the cancellation of interference across cells. We term this technique \emph{coded water-filling}, a concept that diverges from traditional water-filling by incorporating variable-length rateless coding and interference cancellation. We formulate a series of analytical models to quantify the gains associated with coded water-filling in multi-user scenarios. First, we analyze the capacity gains from interference cancellation in Additive White Gaussian Noise (AWGN) channels, which arises from the disparity in the number of bits transmitted by distinct users. Building upon this, we broaden our analysis to encompass fading channels to show the robustness of the interference cancellation algorithms. Finally, we address the power allocation problem analogous to the water-filling problem under a multi-user framework, proving that an elevation in the water-filling threshold facilitates overall system capacity enhancement. Our analysis reveals the capacity gains achievable through early termination and power allocation techniques in multi-user settings. These results show that coded water-filling is instrumental for further improving spectral efficiency in crowded spectrums.

Coded Water-Filling for Multi-User Interference Cancellation

TL;DR

The analysis reveals the capacity gains achievable through early termination and power allocation techniques in multi-user settings and shows that coded water-filling is instrumental for further improving spectral efficiency in crowded spectrums.

Abstract

In this paper, we study the system-level advantages provided by rateless coding, early termination and power allocation strategy for multiple users distributed across multiple cells. In a multi-cell scenario, the early termination of coded transmission not only reduces finite-length loss akin to the single-user scenario but also yields capacity enhancements due to the cancellation of interference across cells. We term this technique \emph{coded water-filling}, a concept that diverges from traditional water-filling by incorporating variable-length rateless coding and interference cancellation. We formulate a series of analytical models to quantify the gains associated with coded water-filling in multi-user scenarios. First, we analyze the capacity gains from interference cancellation in Additive White Gaussian Noise (AWGN) channels, which arises from the disparity in the number of bits transmitted by distinct users. Building upon this, we broaden our analysis to encompass fading channels to show the robustness of the interference cancellation algorithms. Finally, we address the power allocation problem analogous to the water-filling problem under a multi-user framework, proving that an elevation in the water-filling threshold facilitates overall system capacity enhancement. Our analysis reveals the capacity gains achievable through early termination and power allocation techniques in multi-user settings. These results show that coded water-filling is instrumental for further improving spectral efficiency in crowded spectrums.

Paper Structure

This paper contains 12 sections, 3 theorems, 52 equations, 8 figures.

Key Result

Theorem 1

There exists a series of $(\ell_s, M_s=2^{K_s}, P, \varepsilon)$ VLSF codes satisfying

Figures (8)

  • Figure 1: Comparison of fixed-length codes and variable-length codes in multi-user interference cancellation scenarios.
  • Figure 2: Comparison of code lengths between fixed-length codes and variable-length codes.
  • Figure 3: A illustration of the queuing model.
  • Figure 4: Two extreme scenarios: constant congestion and no congestion.
  • Figure 5: The ratio of code length savings under different packet intervals with two cells.
  • ...and 3 more figures

Theorems & Definitions (9)

  • Definition 1
  • Theorem 1
  • proof
  • Remark 1
  • Theorem 2
  • proof
  • Theorem 3
  • proof
  • Example 1