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Towards Green Communication: Soft Decoding Scheme for OOK Signals in Zero-Energy Devices

Ticao Zhang, Dennis Hui, Mehrnaz Afshang, Mohammad Mozaffari

TL;DR

This work addresses reliable communication for zero-energy IoT devices by proposing Manchester-coded OOK with non-coherent envelope detection and a soft-decision receiver. It derives an exact closed-form LLR expression and practical low-complexity approximations, enabling near-optimal soft decoding without full channel state information. Simulations in AWGN and block Rayleigh fading show substantial gains over hard decisions, with interleaving delivering large improvements in fading environments. The approach offers a viable path to extend coverage for energy-harvesting IoT while keeping receiver power consumption ultra-low.

Abstract

The booming of Internet-of-Things (IoT) is expected to provide more intelligent and reliable communication services for higher network coverage, massive connectivity, and low-cost solutions for 6G services. However, frequent charging and battery replacement of these massive IoT devices brings a series of challenges. Zero energy devices, which rely on energy-harvesting technologies and can operate without battery replacement or charging, play a pivotal role in facilitating the massive use of IoT devices. In order to enable reliable communications of such low-power devices, Manchester-coded on-off keying (OOK) modulation and non-coherent detections are attractive techniques due to their energy efficiency, robustness in noisy environments, and simplicity in receiver design. Moreover, to extend their communication range, employing channel coding along with enhanced detection schemes is crucial. In this paper, a novel soft-decision decoder is designed for OOK-based low-power receivers to enhance their detection performance. In addition, exact closed-form expressions and two simplified approximations are derived for the log-likelihood ratio (LLR), an essential metric for soft decoding. Numerical results demonstrate the significant coverage gain achieved through soft decoding for convolutional code.

Towards Green Communication: Soft Decoding Scheme for OOK Signals in Zero-Energy Devices

TL;DR

This work addresses reliable communication for zero-energy IoT devices by proposing Manchester-coded OOK with non-coherent envelope detection and a soft-decision receiver. It derives an exact closed-form LLR expression and practical low-complexity approximations, enabling near-optimal soft decoding without full channel state information. Simulations in AWGN and block Rayleigh fading show substantial gains over hard decisions, with interleaving delivering large improvements in fading environments. The approach offers a viable path to extend coverage for energy-harvesting IoT while keeping receiver power consumption ultra-low.

Abstract

The booming of Internet-of-Things (IoT) is expected to provide more intelligent and reliable communication services for higher network coverage, massive connectivity, and low-cost solutions for 6G services. However, frequent charging and battery replacement of these massive IoT devices brings a series of challenges. Zero energy devices, which rely on energy-harvesting technologies and can operate without battery replacement or charging, play a pivotal role in facilitating the massive use of IoT devices. In order to enable reliable communications of such low-power devices, Manchester-coded on-off keying (OOK) modulation and non-coherent detections are attractive techniques due to their energy efficiency, robustness in noisy environments, and simplicity in receiver design. Moreover, to extend their communication range, employing channel coding along with enhanced detection schemes is crucial. In this paper, a novel soft-decision decoder is designed for OOK-based low-power receivers to enhance their detection performance. In addition, exact closed-form expressions and two simplified approximations are derived for the log-likelihood ratio (LLR), an essential metric for soft decoding. Numerical results demonstrate the significant coverage gain achieved through soft decoding for convolutional code.
Paper Structure (12 sections, 3 theorems, 16 equations, 8 figures)

This paper contains 12 sections, 3 theorems, 16 equations, 8 figures.

Table of Contents

  1. Introduction
  2. Related Work
  3. Our Contributions
  4. System Model and LLR computation
  5. System Model
  6. LLR Computation
  7. Low-complexity approximations to the LLR
  8. Simulation Results and Discussions
  9. Performance in AWGN Channel
  10. Performance in Block Rayleigh Fading Channel
  11. Impact of the Randomly Modulated Phase Sequences
  12. Conclusions

Key Result

Theorem 1

[LLR-exact] The exact closed-form expression of LLR for Manchester encoded OOK signal for the non-coherent receiver can be expressed as: where $I_0(x)=\frac{1}{\pi}\int_0^{\pi}e^{x\cos(z)}{\rm d}z$ is the modified zero-order Bessel function.

Figures (8)

  • Figure 1: Illustration of the proposed soft OOK signal transmission system including BS and low-power receiver.
  • Figure 2: Illustration of function $f(x)=\log(I_0(x))$ and its low-complexity approximations.
  • Figure 3: BER performance of hard- and soft-decision decoding with convolutional codes in AWGN channels.
  • Figure 4: BLER performance of hard- and soft-decision decoding with convolutional codes in AWGN channels.
  • Figure 5: The impact of time domain modulation in AWGN channels.
  • ...and 3 more figures

Theorems & Definitions (3)

  • Theorem 1
  • Proposition 1
  • Proposition 2