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Mini-Slot-Assisted Short Packet URLLC:Differential or Coherent Detection?

Canjian Zheng, Fu-Chun Zheng, Jingjing Luo, Pengcheng Zhu, Xiaohu You, Daquan Feng

TL;DR

The paper tackles mini-slot assisted URLLC by addressing the conflict between channel estimation overhead and strict latency/reliability. It introduces an adaptive framework that switches between differential OFDM (frequency or time domain) and pilot-based coherent detection to minimize training overhead while preserving performance. Using non-asymptotic information-theoretic bounds, it derives BLER and rate expressions for both differential and pilot-assisted schemes, and validates the theory with simulations showing scenario-dependent benefits. The results highlight the practicality of adaptive differential/coherent detection for short-packet URLLC and point to future work on multi-BS diversity and extended deployment scenarios.

Abstract

One of the primary challenges in short packet ultra-reliable and low-latency communications (URLLC) is to achieve reliable channel estimation and data detection while minimizing the impact on latency performance. Given the small packet size in mini-slot-assisted URLLC, relying solely on pilot-based coherent detection is almost impossible to meet the seemingly contradictory requirements of high channel estimation accuracy, high reliability, low training overhead, and low latency. In this paper, we explore differential modulation both in the frequency domain and in the time domain, and propose adopting an adaptive approach that integrates both differential and coherent detection to achieve mini-slot-assisted short packet URLLC, striking a balance among training overhead, system performance, and computational complexity. Specifically, differential (especially in the frequency domain) and coherent detection schemes can be dynamically activated based on application scenarios, channel statistics, information payloads, mini-slot deployment options, and service requirements. Furthermore, we derive the block error rate (BLER) for pilot-based, frequency domain, and time domain differential OFDM using non-asymptotic information-theoretic bounds. Simulation results validate the feasibility and effectiveness of adaptive differential and coherent detection.

Mini-Slot-Assisted Short Packet URLLC:Differential or Coherent Detection?

TL;DR

The paper tackles mini-slot assisted URLLC by addressing the conflict between channel estimation overhead and strict latency/reliability. It introduces an adaptive framework that switches between differential OFDM (frequency or time domain) and pilot-based coherent detection to minimize training overhead while preserving performance. Using non-asymptotic information-theoretic bounds, it derives BLER and rate expressions for both differential and pilot-assisted schemes, and validates the theory with simulations showing scenario-dependent benefits. The results highlight the practicality of adaptive differential/coherent detection for short-packet URLLC and point to future work on multi-BS diversity and extended deployment scenarios.

Abstract

One of the primary challenges in short packet ultra-reliable and low-latency communications (URLLC) is to achieve reliable channel estimation and data detection while minimizing the impact on latency performance. Given the small packet size in mini-slot-assisted URLLC, relying solely on pilot-based coherent detection is almost impossible to meet the seemingly contradictory requirements of high channel estimation accuracy, high reliability, low training overhead, and low latency. In this paper, we explore differential modulation both in the frequency domain and in the time domain, and propose adopting an adaptive approach that integrates both differential and coherent detection to achieve mini-slot-assisted short packet URLLC, striking a balance among training overhead, system performance, and computational complexity. Specifically, differential (especially in the frequency domain) and coherent detection schemes can be dynamically activated based on application scenarios, channel statistics, information payloads, mini-slot deployment options, and service requirements. Furthermore, we derive the block error rate (BLER) for pilot-based, frequency domain, and time domain differential OFDM using non-asymptotic information-theoretic bounds. Simulation results validate the feasibility and effectiveness of adaptive differential and coherent detection.
Paper Structure (13 sections, 4 theorems, 44 equations, 8 figures)

This paper contains 13 sections, 4 theorems, 44 equations, 8 figures.

Table of Contents

  1. Introduction
  2. Background
  3. Motivations
  4. Related Works and Our Contributions
  5. System Model and Assumptions
  6. Differentially modulated OFDM
  7. PA-OFDM
  8. Performance analysis of mini-slot-assisted short packet OFDM
  9. Preliminaries on Non-Asymptotic Information Theory
  10. Differentially Modulated Short Packet OFDM
  11. Pilot Symbol-assisted Short Packet OFDM
  12. Simulation Results
  13. Conclusions

Key Result

Theorem 1

(IS lower bound Polyanskiy2010Channel ): For a general P2P channel consists of an input alphabet $\mathcal{X}$, an output alphabet $\mathcal{Y}$ and a conditional channel transition probability ${{\mathbb{P}}_{Y^{\overline N}\left| X^{\overline N} \right.}}\left( {y^{\overline N}\left| x^{\overline where $\beta>0$ is an arbitrary positive constant and is termed the information density.

Figures (8)

  • Figure 1: Reference signal patterns of 2, 4 and 7 OFDM symbol units with coherent detection (a-d), frequency domain differential modulation (e-g), and time domain differential modulation (h-j). According to 3GPP211, the patterns (a) and (b) are used in both low and high mobility scenarios, (c) is used in low mobility scenarios, and (d) is used in high mobility scenarios.
  • Figure 2: Block diagram of FDDi-OFDM.
  • Figure 3: Transceiver components of (a) TDDi-OFDM and (b) PA-OFDM.
  • Figure 4: The BLER performance of PA-OFDM, FDDi-OFDM and TDDi-OFDM for different $K$ under a 2 OFDM symbol unit with modulation order $M = 4$, $f_dT_s =0.01$, $L=5$ and SNR $\gamma=2$dB.
  • Figure 5: BLER performance comparisons of PA-OFDM, FDDi-OFDM and TDDi-OFDM under a 2 OFDM symbol unit: (a) $f_d T_s=0.01$, and (b) $f_d T_s=0.1$.
  • ...and 3 more figures

Theorems & Definitions (4)

  • Theorem 1
  • Theorem 2
  • Theorem 3
  • Corollary 1