Prediction and Communication Co-design for Ultra-Reliable and Low-Latency Communications

TL;DR

An optimization problem is formulated that maximizes the number of URLLC services supported by the system by optimizing time and frequency resources and the prediction horizon, and shows that the tradeoff between user experienced delay and reliability can be improved significantly via prediction and communication co-design.

Abstract

Ultra-reliable and low-latency communications (URLLC) are considered as one of three new application scenarios in the fifth generation cellular networks. In this work, we aim to reduce the user experienced delay through prediction and communication co-design, where each mobile device predicts its future states and sends them to a data center in advance. Since predictions are not error-free, we consider prediction errors and packet losses in communications when evaluating the reliability of the system. Then, we formulate an optimization problem that maximizes the number of URLLC services supported by the system by optimizing time and frequency resources and the prediction horizon. Simulation results verify the effectiveness of the proposed method, and show that the tradeoff between user experienced delay and reliability can be improved significantly via prediction and communication co-design. Furthermore, we carried out an experiment on the remote control in a virtual factory, and validated our concept on prediction and communication co-design with the practical mobility data generated by a real tactile device.

Figures (7)

• Figure 1: Illustration of network structure.
• Figure 2: Illustration of prediction and communication co-design.
• Figure 3: Joint optimization of predictions and communications: the packet loss probability $\varepsilon_c$ in communications, the prediction error probability $\varepsilon_p$, and the over error probability $\varepsilon_o$ are drawn as functions of prediction horizon $T_{\rm p}T_{\rm s}$.
• Figure 4: Comparison of reliability-delay tradeoff curves between co-design and no predictions with different bandwidth $B$ and numbers of received antennas $N_{\rm r}$.
• Figure 5: $\Pr\{\sum_{n=1}^N{ B_n} > B_{\max}\}$ v.s. the number of devices when the distribution of large-scale fading of devices is known.

Theorems & Definitions (16)

• Remark 1
• Remark 2
• Lemma 1
• proof
• Lemma 2
• proof
• Lemma 3
• proof
• Proposition 1
• proof