We consider the satellite Internet of Things (IoT) system, in which the IoT device observes physical processes and transmits status updates to the monitor node over an error-prone channel with non-trivial propagation delay. The freshness of status updates is characterized by age of information (AoI), a novel metric which is defined as the time that elapsed since the freshest received status update was generated. Channel coding is used to combat the burst channel errors and feedback is available through hybrid automatic repeat request (HARQ) protocols. By adopting both the simple-HARQ and incremental redundancy hybrid ARQ (IR-HARQ) transmission schemes, we study the age-optimal redundancy allocation problems under the constraint of reliability. As we put special interests on the satellite-IoT scenarios in which the propagation delays are nonnegligible, there exists a threshold of the propagation delay only below which using retransmissions is beneficial to AoI. However, characterization of such a threshold has received little attention in the literature. By formulating and solving the age-optimal redundancy allocation problems for the adopted HARQ schemes, explicit expressions of the optimal codeword length for each transmission round are derived, and then the threshold of the propagation delay for beneficial retransmissions is obtained. Extensive numerical analyses are conducted to show the effects of propagation delay and channel state on the redundancy allocation results and the optimal AoI. The threshold is also demonstrated by numerical analysis. The results shed important light on the age-optimal HARQ design for freshness-critical satellite IoT systems in the presence of non-trivial propagation delay.

In this paper, we study the age-oriented hybrid automatic repeat request (HARQ) protocol design in space-air-ground integrated networks (SAGINs) scenarios. A real-time communication system, where the updates are delivered from the remote nodes to terrestrial devices, is formulated. As the end-to-end latency $D$ is nontrivial, the traditional HARQ with frequent feedbacks is not always beneficial to timely transmission. Intuitively, there is a threshold $D^{*}$ of $D$ , only within which retransmission is advantageous to age. Inspired by this, we formulate an age-optimal redundancy allocation problem and derive the explicit expression of $D^{*}$ for advantageous retransmissions. Besides, to further increase the timeliness of the system, we propose a fast incremental redundancy hybrid ARQ protocol (fast IR-HARQ), where successive decoding and feedback operations are omitted based on channel estimation. Considering the shadowed Rician fading channel and finite blocklength regime, we derive expressions of the average age for the standard IR-HARQ and fast IR-HARQ setups. As expected, the proposed fast IR-HARQ scheme reduces the average age significantly compared with the IR-HARQ strategy. Further, we evaluate the influence of different parameters on the age performance of the fast IR-HARQ scheme. The results demonstrate the superiority of the proposed fast IR-HARQ protocol without loss of reliability.

The objective of this paper is to investigate an update scheduling issue in the satellite-based network for time-sensitive marine Internet-of-Things (marine IoT) applications. In this particular scenario, multiple gateways capture updates from surrounding marine IoT sensors and make online decisions regarding task scheduling for orbital processing by a specific satellite. A hybrid low earth orbit and geosynchronous earth orbit (hybrid GEO-LEO) satellite architecture shows promise in achieving timely update delivery. However, the limited communication and orbital processing resources create significant challenges for ensuring timely task scheduling in the hybrid network. To address this challenge, we model the age-optimal scheduling issue as a collaborative gateway association and resource management problem. We first transform it into two corresponding sub-problems: resource management and scheduling decision-making. Subsequently, we employ the Lagrange multiplier algorithm to achieve optimal resource allocation results while utilizing deep reinforcement learning techniques to determine the scheduling decisions intelligently. Extensive simulation results demonstrate that our designed intelligent task scheduling scheme with optimal resource management outperforms state-of-the-art schemes in terms of peak-age, thereby highlighting the effectiveness of hybrid GEO-LEO networks for time-sensitive marine IoT applications.

To support the emergent freshness-critical applications in the satellite-integrated IoT, information must be transmitted timely and reliably. A significant limitation of the upcoming satellite-integrated IoT era is the non-trivial propagation latency because of long-distance communication. To realize timely information delivery, the hybrid automatic repeat request (HARQ) strategy with frequent feedback is not fit anymore, since the reliability of the HARQ strategy needs multiple retransmission of the obsolete packets, which inevitably result in information staleness in the satellite-integrated IoT. In this paper, we design a two-layer coding strategy that uses error-correction codes within each packet in the physical-layer (PHY) and erasure-correction codes across the packets in the packet-layer. Then, we formulate an AoI-optimal redundancy-allocation problem to find the redundancy compromise between error-correction codes and erasure-correction codes. By solving the redundancy-allocation problem for the designed two-layer coding strategy, we derive explicit expressions of the AoI-optimal two-layer coding rates. Inspired by this, we explore the optimal reliability of the physical channel. Numerical results and analysis prove that making the physical channel suitably unreliable is beneficial to the timeliness of the system. And the simulation results indicate that the combination of erasure-correction codes and relative lossy error-correction codes achieves AoI-improvement over the ultra-reliable PHY-only coding scheme. The simulation results also show that the choice of AoI-optimal coding rates depends heavily on the channel characteristics, such as the signal-to-noise ratio, fade duration and channel fading parameters.

As an important branch of the Internet of Things, the Internet of Multimedia Things (IoMT) has complex application scenarios, thus putting forward new challenges to data communication. With the application of compressed sensing (CS)-based image compression and transmission in the field of IoMT, the traditional CS image reconstruction algorithms have been extended to model-based algorithms, which exploit more prior information of multimedia objects other than sparsity/compressibility in the reconstruction process. However, these algorithms mainly exploit just one type of prior information, still leaving room for further improvement. In this paper, we propose a novel CS image reconstruction algorithm by jointly leveraging multi-scale (local and global) heterogeneous (statistical and structural) priors of natural images, named jointly leveraging statistical and structural priors for CS image reconstruction (JLSSP-CS), to enable high-quality CS image recovery for IoMT. Specifically, the proposed JLSSP-CS algorithm is realized under the iterative hard thresholding framework, and the reconstruction process is composed of two phases. In the first phase, the local statistical correction and the global statistical correction are considered sequentially. Then, the global statistical and structural priors are exploited in nested iterations to further refine the recovery result in the second phase. The extensive simulations have been conducted, and the results indicate that the proposed JLSSP-CS algorithm outperforms the current state of the art by realizing high-quality image reconstruction with a small number of measurements for IoMT end devices.

Ultrasonic wire bonding is one of the most important techniques for die interconnection in microelectronic packaging. It is widely used for power devices, microwave devices and photoelectron devices packaging. At room temperature, ultrasonic energy and plastic deformation energy, generated by metal wire plastic deformation under the wedge tool pressure, make the wire and metallization join together. The ultrasonic bonds, after bonding and aging, of Al+1%Si wire with 25/spl mu/m diameter bonded on the Au/Ni/Cu pad, are analyzed by scanning electronic microscopy (SEM) with energy dispersive x-ray spectrometer (EDX). The joints begin at the bond periphery where it is the location of the greatest plastic flow. It is found that the mechanism of ultrasonic bonding is, both the plastic flow of metal wire generated by wedge tool pressure which results in the diffusion of Ni into Al wire; and the effect of ultrasound is that, on the one hand, ultrasonic vibration enhances the metal wire ability of plastic flow and, on the other hand, it generates many defects inside the metal wire which are the fast diffusion channels. The diffusion type is likely the short-circuit diffusion, which is more prominent than the crystal diffusion when the temperature is low. After high temperature storage at 170 /spl deg/C for 10 days, there is evident diffusion of Ni into Al wire, but the microstructure is the same with the bonds after bonding, there is no evident change. Aged for 30 days, the bond interface forms a cloud-like structure, and the major composition is Al and Ni with weight percent of 78.82% and 15.55% respectively. However, the diffusion is not even and some parts of the bond interface are absence of Ni diffusion. When the aging time is 40 days, the cloud-like structure transforms into rectangular island-like structure and there are many cavities inside the bond wire, which are different from the Kirkendall voids because of the shape and dimension.