Environment monitoring is important for the safety of underground coal mine production, and it is also an important application of Wireless Sensor Networks (WSNs). We put forward an integrated environment monitoring system for underground coal mine, which uses the existing Cable Monitoring System (CMS) as the main body and the WSN with multi-parameter monitoring as the supplementary technique. As CMS techniques are mature, this paper mainly focuses on the WSN and the interconnection between the WSN and the CMS. In order to implement the WSN for underground coal mines, two work modes are designed: periodic inspection and interrupt service; the relevant supporting technologies, such as routing mechanism, collision avoidance, data aggregation, interconnection with the CMS, etc., are proposed and analyzed. As WSN nodes are limited in energy supply, calculation and processing power, an integrated network management scheme is designed in four aspects, i.e., topology management, location management, energy management and fault management. Experiments were carried out both in a laboratory and in a real underground coal mine. The test results indicate that the proposed integrated environment monitoring system for underground coal mines is feasible and all designs performed well as expected.

Unmanned aerial vehicle (UAV)-assisted relay mobile edge computing (MEC) network is a prominent concept, where network deployment is flexible and network coverage is wide. In scenarios such as emergency communications and low-cost coverage, optimization of offloading methods and resource utilization are important ways to improve system effectiveness due to limited terminal and UAV energy and hardware equipment. A multilevel edge computing network resource optimization model on the basis of UAV fusion that provides relay forwarding and offload services is established by considering the initial energy state of the UAV, the green energy charging function, and the reliability of computing offload. With normalized system utility function maximization as the goal, a Markov decision process algorithm meets the needs of the practical application scene and provides a flexible and effective unloading mode. This algorithm is adopted to solve the optimal offloading mode and the optimal resource utilization scheme. Simulations verify the effectiveness and reliability of the proposed multilevel offloading model. The proposed model can optimize system resource allocation and effectively improve the utility function and user experience of computing offloading systems.

Heterogeneous network, which is a key technology of fifth generation(5G) mobile communication system, can effectively solve the spectrum resource shortage in the communication system. However, with densified deployment of base stations (BSs) and growth of user quantity and communication data size, the system energy consumption of BSs has imposed enormous economic pressure on network operators. As a result, energy consumption decreases and cost of communication system becomes a problem that requires urgent solutions. Renewable energy power generation devices of BSs have provided an opportunity for solving this problem with the development of smart power grids. However, the production rate of renewable energy sources presents intense volatility because of the influence of weather factors. This condition brings new challenges to the energy allocation of communication system. Therefore, an energy sharing link between BSs was established in a heterogeneous wireless network, and the distance between macro-BS and micro-BS was taken as an index. The energy consumption-based energy and user joint allocation method and energy cost-based energy and user joint allocation method were proposed. The two multi-objective optimization problems were converted into two convex optimization problems, and the optimal allocation strategies were solved using convex optimization toolbox. Simulation results indicate that the energy consumption-based allocation method takes energy consumption as the optimization objective and makes the shared link transmit energy sources as few as possible. This way reduces energy consumptions of the link and the system. Starting from the economic angle, the energy cost-based allocation method considers the influence of energy price, coordinates energy allocation between BSs based on energy cost using the shared link, and optimizes energy allocation among BSs at each time slot. Therefore, the method can reduce the energy cost of the system by a large margin. INDEX TERMS 5G, energy sharing, green communication, energy allocation, user allocation, convex optimization. I. INTRODUCTION In recent years, the energy consumption of information and communication technology (ICT) has become an economic issue for operators and a major challenge for sustainable development. The energy consumption of the ICT industry accounts for approximately 3% of global annual energy consumption, and this figure is growing at an annular rate of 15%-20% [1]. With the rapid development of wireless communication technology and Internet of Things (IoT) technology [2], the quantity of equipment connected to wireless communication base stations (BSs) will present exponential The associate editor coordinating the review of this manuscript and approving it for publication was Jun Wu. growth in the future. By 2020, the demand for high-speed data traffic, such as high-quality wireless video streaming, social networking services, and IoT communication, will grow by 1,000 times [3]. If effective measures are not taken, then mobile communication ...

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Wireless and power line communications (PLC) are important components of distribution network communication, and have a broad application prospect in the fields of intelligent power consumption and home Internet of Things (IoT). This study mainly analyzes the performance of a dual-hop wireless/power line hybrid fading system employing an amplify-and-forward (AF) relay in terms of outage probability and average bit error rate (BER). The Nakagami-m distribution captures the wireless channel fading; whereas the PLC channel gain is characterized by the Log-normal (LogN) distribution. Moreover, the Bernoulli-Gaussian noise model is used on the noise attached to the PLC channel. Owing to the similarity between LogN and Gamma distributions, the key parameters of probability density function (PDF) with approximate distribution are determined by using moment generating function (MGF) equations, joint optimization of s vectors, and approximation of LogN variable sum. The MGF of the harmonic mean of the dual Gamma distribution variables is derived to evaluate the system performance suitable for any fading parameter m value. Finally, Monte Carlo simulation is used to verify the versatility and accuracy of the proposed method, and the influence of the hybrid fading channel and multidimensional impulse noise parameters on system performance is analyzed.

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