Device-to-Device (D2D) communication has emerged as a promising technology for optimizing spectral efficiency in future cellular networks. D2D takes advantage of the proximity of communicating ...devices for efficient utilization of available resources, improving data rates, reducing latency, and increasing system capacity. The research community is actively investigating the D2D paradigm to realize its full potential and enable its smooth integration into the future cellular system architecture. Existing surveys on this paradigm largely focus on interference and resource management. We review recently proposed solutions in over explored and under explored areas in D2D. These solutions include protocols, algorithms, and architectures in D2D. Furthermore, we provide new insights on open issues in these areas. Finally, we discuss potential future research directions.
Immediate placement of an intrauterine device after vaginal delivery is safe and convenient, but longitudinal data describing clinical outcomes have been limited.
We sought to determine the ...proportion of TCu380A (copper) intrauterine devices expelled, partially expelled, malpositioned, and retained, as well as contraceptive use by 6 months postpartum, and determine risk factors for expulsion and partial expulsion.
In this prospective, observational study, women who received a postplacental TCu380A intrauterine device at vaginal delivery were enrolled postpartum. Participants returned for clinical follow-up at 6 weeks, and for a research visit with a pelvic exam and ultrasound at 6 months. We recorded intrauterine device outcomes and 6-month contraceptive use. Partial expulsion was defined as an intrauterine device protruding from the external cervical os, or a transvaginal ultrasound showing the distal end of the intrauterine device below the internal os of the cervix. Multinomial logistic regression models identified risk factors associated with expulsion and partial expulsion by 6 months. The area under the receiver operating characteristics curve was used to assess the ability of a string check to predict the correct placement of a postplacental intrauterine device. The primary outcome was the proportion of intrauterine devices expelled at 6 months.
We enrolled 200 women. Of 162 participants with follow-up data at 6 months, 13 (8.0%; 95% confidence interval, 4.7–13.4%) experienced complete expulsion and 26 (16.0%; 95% confidence interval, 11.1–22.6%) partial expulsion. Of 25 malpositioned intrauterine devices (15.4%; 95% confidence interval, 10.2–21.9%), 14 were not at the fundus (8.6%; 95% confidence interval, 5.2–14.1%) and 11 were rotated within the uterus (6.8%; 95% confidence interval, 3.8–11.9%). Multinomial logistic regression modeling indicated that higher parity (odds ratio, 2.05; 95% confidence interval, 1.21–3.50; P = .008) was associated with expulsion. Provider specialty (obstetrics vs family medicine; odds ratio, 5.31; 95% confidence interval, 1.20–23.59; P = .03) and gestational weight gain (normal vs excess; odds ratio, 9.12; 95% confidence interval, 1.90–43.82; P = .004) were associated with partial expulsion. Long-acting reversible contraceptive method use at 6 months was 80.9% (95% confidence interval, 74.0–86.6%). At 6 weeks postpartum, 35 of 149 (23.5%; 95% confidence interval, 16.9–31.1%) participants had no intrauterine device strings visible. Sensitivity of a string check to detect an incorrectly positioned intrauterine device was 36.2%, and specificity of the string check to predict a correctly positioned intrauterine device was 84.5%. This corresponds to an area under the receiver operating characteristics curve of 0.5.
This prospective assessment of postplacental TCu380A intrauterine device placement, with ultrasound to confirm device position, finds a complete intrauterine device expulsion proportion of 8.0% at 6 months. The association of increasing parity with expulsion is consistent with prior research. The clinical significance of covariates associated with partial expulsion (provider specialty and gestational weight gain) is unclear. Due to the observational study design, any associations cannot imply causality. The proportion of partially expelled and malpositioned intrauterine devices was high, and the area under the receiver operating characteristics curve of 0.5 indicates that a string check is a poor test for assessing device position. Women considering a postplacental intrauterine device should be counseled about the risk of position abnormalities, as well as the possibility of nonvisible strings, which may complicate clinical follow-up. The clinical significance of intrauterine device position abnormalities is unknown; future research should evaluate the influence of malposition and partial expulsion on contraceptive effectiveness and side effects.
Mobile edge computing (MEC) and device-to-device (D2D) offloading are two promising paradigms in the industrial Internet of Things (IIoT). In this article, we investigate task co-offloading, where ...computing-intensive industrial tasks can be offloaded to MEC servers via cellular links or nearby IIoT devices via D2D links. This co-offloading delivers small computation delay while avoiding network congestion. However, erratic movements, the selfish nature of devices and incomplete offloading information bring inherent challenges. Motivated by these, we propose a co-offloading framework, integrating migration cost and offloading willingness, in D2D-assisted MEC networks. Then, we investigate a learning-based task co-offloading algorithm, with the goal of minimal system cost (i.e., task delay and migration cost). The proposed algorithm enables IIoT devices to observe and learn the system cost from candidate edge nodes, thereby selecting the optimal edge node without requiring complete offloading information. Furthermore, we conduct simulations to verify the proposed co-offloading algorithm.
Cardiovascular disease is the leading cause of death and has dramatically increased in recent years. Continuous cardiac monitoring is particularly important for early diagnosis and prevention, and ...flexible and stretchable electronic devices have emerged as effective tools for this purpose. Their thin, soft, and deformable features allow intimate and long‐term integration with biotissues, which enables continuous, high‐fidelity, and sometimes large‐area cardiac monitoring on the skin and/or heart surface. In addition to monitoring, intimate contact is also crucial for high‐precision therapies. Combined with tissue engineering, soft bioelectronics have also demonstrated the capability to repair damaged cardiac tissues. This review highlights the recent advances in wearable and implantable devices based on flexible and stretchable electronics for cardiovascular monitoring and therapy. First, wearable/implantable soft bioelectronics for cardiovascular monitoring (e.g., the electrocardiogram, blood pressure, and oxygen saturation level) are reviewed. Then, advances in cardiovascular therapy based on soft bioelectronics (e.g., mesh pacing, ablation, robotic sleeves, and electronic stents) are discussed. Finally, device‐assisted tissue engineering therapy (e.g., functional electronic scaffolds and in vitro cardiac platforms) is discussed.
Over the past few decades, soft bioelectronics have been widely adopted in biomedical research fields to address limitations in each field. Here, wearable and implantable devices based on flexible and stretchable electronics for cardiovascular monitoring and therapy that overcome the problems with conventional treatments are reviewed. In addition, the emerging field of device‐assisted tissue engineering is highlighted.
Mobile edge computing (MEC) has emerged as a new paradigm to assist low latency services by enabling computation offloading at the network edge. Nevertheless, human mobility can significantly impact ...the offloading decision and performance in MEC networks. In this context, we propose device-to-device (D2D) cooperation based MEC to expedite the task execution of mobile user by leveraging proximity-aware task offloading. However, user mobility in such distributed architecture results in dynamic offloading decision that instigates mobility-aware task scheduling in our proposed framework. We jointly formulate task assignment and power allocation to minimize the total task execution latency by taking account of user mobility, distributed resources, tasks properties, and energy constraint of the user device. We first propose Genetic Algorithm (GA)-based evolutionary scheme to solve our formulated mixed-integer non-linear programming (MINLP) problem. Then we propose a heuristic named mobility-aware task scheduling (MATS) to obtain effective task assignment with low complexity. The extensive evaluation under realistic human mobility trajectories provides useful insights into the performance of our schemes and demonstrates that, both GA and MATS achieve better latency than other baseline schemes while satisfying the energy constraint of mobile device.
The explosive growth of content requests from mobile users is stretching the capability of current mobile networking technologies to satisfy users' demands with acceptable quality of service. An ...effective approach to address this challenge, which has not yet been thoroughly studied, is to offload network traffic by caching popular content at the edges (e.g., mobile devices and base stations) of mobile networks, thus reducing the massive duplication of content downloads. In this paper, we address the system modeling, large-scale optimization, and framework design of hierarchical edge caching in device-to-device aided mobile networks. In particular, taking into account the analysis of social behavior and preference of mobile users, heterogeneous cache sizes, and the derived system topology, we investigate the maximum capacity of the network infrastructure in terms of offloading network traffic, reducing system costs, and supporting content requests from mobile users locally. Our proposed framework has a low complexity and can be applied in practical engineering implementation. Trace-based simulation results demonstrate the effectiveness of the proposed framework.
Device-to-device (D2D) technology, which allows direct communications between proximal devices, is widely acknowledged as a promising candidate to alleviate the mobile traffic explosion problem. In ...this paper, we consider an overlay D2D network, in which multiple D2D pairs coexist on several orthogonal spectrum bands, i.e., channels. Due to spectrum scarcity, the number of D2D pairs is typically more than that of available channels, and thus multiple D2D pairs may use a single channel simultaneously. This may lead to severe co-channel interference and degrade network performance. To deal with this issue, we formulate a joint channel selection and power control optimization problem, with the aim to maximize the weighted-sum-rate (WSR) of the D2D network. Unfortunately, this problem is non-convex and NP-hard. To solve this problem, we first adopt the state-of-art fractional programming (FP) technique and develop an FP-based algorithm to obtain a near-optimal solution. However, the FP-based algorithm requires instantaneous global channel state information (CSI) for centralized processing, resulting in poor scalability and prohibitively high signalling overheads. Therefore, we further propose a distributed deep reinforcement learning (DRL)-based scheme, with which D2D pairs can autonomously optimize channel selection and transmit power by only exploiting local information and outdated nonlocal information. Compared with the FP-based algorithm, the DRL-based scheme can achieve better scalability and reduce signalling overheads significantly. Simulation results demonstrate that even without instantaneous global CSI, the performance of the DRL-based scheme can approach closely to that of the FP-based algorithm.
This paper investigates the resource allocation problem in device-to-device-based vehicular communications, based on slow fading statistics of channel state information (CSI), to alleviate signaling ...overhead for reporting rapidly varying accurate CSI of mobile links. We consider the case when each vehicle-to-infrastructure (V2I) link shares spectrum with multiple vehicle-to-vehicle (V2V) links. Leveraging the slow fading statistical CSI of mobile links, we maximize the sum V2I capacity while guaranteeing the reliability of all V2V links. We use graph partitioning tools to divide highly interfering V2V links into different clusters before formulating the spectrum sharing problem as a weighted 3-D matching problem. We propose a suite of algorithms, including a baseline graph-based resource allocation algorithm, a greedy resource allocation algorithm, and a randomized resource allocation algorithm, to address the performance-complexity tradeoffs. We further investigate resource allocation adaption in response to slow fading CSI of all vehicular links and develop a low-complexity randomized algorithm.
Device-to-device (D2D) communication, which enables direct communication between nearby mobile devices, is an attractive add-on component to improve spectrum efficiency and user experience by reusing ...licensed cellular spectrum in 5G system. In this paper, we propose to enable D2D communication in unlicensed spectrum (D2D-U) as an underlay of the uplink LTE network for further booming the network capacity. A sensing-based protocol is designed to support the unlicensed channel access for both LTE and D2D users. We further investigate the subchannel allocation problem to maximize the sum rate of LTE and D2D users while considering their interference to the existing Wi-Fi systems. Specifically, we formulate the subchannel allocation as a many-to-many matching problem with externalities, and develop an iterative user-subchannel swap algorithm. Analytical and simulation results show that the proposed D2D-U scheme can significantly improve the system sum rate.
Massive multimedia services have been considered as one the most prominent characteristics for smart cities. In this paper, we propose an energy-efficient content delivery system via the ...device-to-device communications, which realizes the large-scale content delivery among mobile devices with constrained energy, unpredictable demand, limited storage, random mobility, and opportunistic transmission. The highlights of this paper lie in two parts. On the theoretical end, through exploring the relationship among the coding, storage, and transmission, a systematic energy-saving content delivery fashion is investigated. On the technical end, a totally distributed content delivery system is designed in a simple and efficient manner, in which each device only utilizes local information to make decisions and implements its own scheme individually. Importantly, the proposed scheme is realized in a practical smart city system, and numerical results demonstrate that it is flexible to various users' needs and communication environments.
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