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A Resilience Perspective on C-V2X Communication Networks under Imperfect CSI

Tingyu Shui, Walid Saad, Mingzhe Chen

TL;DR

Simulation results validate the framework's superiority in capturing the interplay between adaptation and remediation, as well as the effectiveness of the two proposed metrics in guiding the design of the adaptation power scheme to enhance the system's resilience.

Abstract

Cellular vehicle-to-everything (C-V2X) networks provide a promising solution to improve road safety and traffic efficiency. One key challenge in such systems lies in meeting different quality-of-service (QoS) requirements of coexisting vehicular communication links, particularly under imperfect channel state information (CSI) conditions caused by the highly dynamic environment. In this paper, a novel analytical framework for examining the resilience of C-V2X networks in face of imperfect CSI is proposed. In this framework, the adaptation phase of the C-V2X network is studied, in which an adaptation power scheme is employed and the probability distribution function (PDF) of the imperfect CSI is estimated. Then, the resilience of C-V2X networks is studied through two principal dimensions: remediation capability and adaptation performance, both of which are defined, quantified, and analyzed for the first time. Particularly, an upper bound on the estimation's mean square error (MSE) is explicitly derived to capture the C-V2X's remediation capability, and a novel metric named hazard rate (HR) is exploited to evaluate the C-V2X's adaptation performance. Afterwards, the impact of the adaptation power scheme on the C-V2X's resilience is examined, revealing a tradeoff between the C-V2X's remediation capability and adaptation performance. Simulation results validate the framework's superiority in capturing the interplay between adaptation and remediation, as well as the effectiveness of the two proposed metrics in guiding the design of the adaptation power scheme to enhance the system's resilience.

A Resilience Perspective on C-V2X Communication Networks under Imperfect CSI

TL;DR

Simulation results validate the framework's superiority in capturing the interplay between adaptation and remediation, as well as the effectiveness of the two proposed metrics in guiding the design of the adaptation power scheme to enhance the system's resilience.

Abstract

Cellular vehicle-to-everything (C-V2X) networks provide a promising solution to improve road safety and traffic efficiency. One key challenge in such systems lies in meeting different quality-of-service (QoS) requirements of coexisting vehicular communication links, particularly under imperfect channel state information (CSI) conditions caused by the highly dynamic environment. In this paper, a novel analytical framework for examining the resilience of C-V2X networks in face of imperfect CSI is proposed. In this framework, the adaptation phase of the C-V2X network is studied, in which an adaptation power scheme is employed and the probability distribution function (PDF) of the imperfect CSI is estimated. Then, the resilience of C-V2X networks is studied through two principal dimensions: remediation capability and adaptation performance, both of which are defined, quantified, and analyzed for the first time. Particularly, an upper bound on the estimation's mean square error (MSE) is explicitly derived to capture the C-V2X's remediation capability, and a novel metric named hazard rate (HR) is exploited to evaluate the C-V2X's adaptation performance. Afterwards, the impact of the adaptation power scheme on the C-V2X's resilience is examined, revealing a tradeoff between the C-V2X's remediation capability and adaptation performance. Simulation results validate the framework's superiority in capturing the interplay between adaptation and remediation, as well as the effectiveness of the two proposed metrics in guiding the design of the adaptation power scheme to enhance the system's resilience.

Paper Structure

This paper contains 12 sections, 2 theorems, 20 equations, 4 figures, 2 tables.

Table of Contents

  1. Introduction
  2. System Model
  3. C-V2X Network Model
  4. QoS of the V2V and V2I links
  5. Imperfect CSI model
  6. Resilience Analysis
  7. Deconvolution Estimation during Adaptation Phase
  8. Remediation Capability Analysis
  9. Adaptation Performance Analysis
  10. Simulation Results and Analysis
  11. Conclusion
  12. Proof of Theorem 1

Key Result

Theorem 1

The remediation capability of the C-V2X network, i.e., the MSE of the estimator $\hat{f}_E$, is upper bounded as: where $o = K \pi (1-\delta_m^2) \frac{P^{\textrm{a}}_m L^{\textrm{a}}_m }{P^{\textrm{a}}_n L^{\textrm{a}}_n}$.

Figures (4)

  • Figure 1: System model of the considered C-V2X network.
  • Figure 2: Deconvolution-based estimation through the adaptation power scheme: a) Estimator $\hat{f}_E$ in \ref{['hat pdf']}, b) Upper bound on the MSE.
  • Figure 3: QoS of V2V link during adaptation phase: a) ORF, b) CRF.
  • Figure 4: QoS of V2I link during adaptation phase: a) ORF, b) CRF.

Theorems & Definitions (5)

  • Theorem 1
  • proof
  • Lemma 1
  • proof
  • proof