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In recent years, the tremendous increase in data traffic carried by wireless communication networks has generated the urgent need for establishing more energy-efficient wireless communication systems. Recent advances in semiconductor and light devices have triggered remarkable research interest to the development of these optical wireless communication (OWC) links. Among them, free-space optical (FSO) links and, more recently, ultraviolet links which operate within the (UV-C) spectral band, have been considered as prime candidates to create both high speed and power effective line-of-sight (LOS) and non-light-of-sight (NLOS) free-air communication links, respectively. Moreover, transdermal optical wireless (TOW) links for telemetry with medical implants minimize the expense of power for the implant. In the current review, a background on the energy efficiency challenges in wireless communication is presented. Each of these OWC technologies is mainly discussed in terms of key energy consumption requirements and major limiting factors that affect their power performance. Energy-efficient modulation formats as well as other powerful techniques for performance enhancement such as diversity and relaying are assessed. The survey is concluded with a discussion regarding their future energy consumption requirements and trends. [ABSTRACT FROM AUTHOR]

In this paper, we study an energy-efficient computation offloading for vehicular edge computing systems, where multiple roadside units assist vehicular users to offload computation tasks to edge servers. Our goal is to minimize the users’ energy consumption by optimizing user association, data partition, transmit power, and computation resources, subject to the constraints of partial tasks offloading, user latency, maximum transmit power, outage performance, and computation capacity of edge servers. We utilize deep learning for user association to avoid combinatorial complexity, and develop an efficient optimization algorithm to optimize other variables. The resulting algorithm has scalable complexity with convergence guarantee, as confirmed by our theoretical analysis. Simulation results demonstrate that the introduced resource allocation algorithm can significantly reduce the total energy consumption of users. [ABSTRACT FROM AUTHOR]

We propose a predictive energy-efficient scheduling scheme that optimizes the user equipment (UE)'s bits/joule metric subject to quality-of-service (QoS) constraints in downlink orthogonal frequency-division multiple access (OFDMA) systems. This is achieved by minimizing the number of wake-up transmission time intervals (TTIs), where the UE receiver circuit is on, in a longer time horizon than studied before. The proposed predictive scheduler is supported by a ray-tracing (RT) engine that increases the scheduler's knowledge by long-term information about the users' propagation characteristics. A convex multiobjective binary-integer-programming formulation for the problem is presented to optimize both the UE's energy efficiency (EE) and QoS. The multiobjective formulation is then used for benchmarking of a low-complexity and computationally efficient heuristic scheduler. The results show that the proposed schedulers have significantly improved the UE's EE and the overall capacity of the system, compared with a recently published EE scheduling scheme while maintaining target QoS. [ABSTRACT FROM PUBLISHER]

With the advance of multimedia and pattern recognition based medical technologies, smart medical applications in smart hospital and smart medical for individual, such as disease diagnosis and health monitoring, play an important role in our life. However, the communication infrastructure of supporting these applications is a challenge. This paper studies the energy-efficient multicast routing problem in multi-hop wireless networks for these medical applications. Energy consumption has become the main problem of sustainable development of communication networks, particularly for these applications. How to carry out high energy-efficient communication is an important research topic for wired and wireless networks to implement green communications. This paper proposes an energy-efficient multicast routing approach to multi-hop wireless networks for smart medical applications. Different from previous methods, we aim at maximizing energy efficiency of networks. To this end, we make use of topology control and sleeping mechanism to obtain the optimal routing strategy with maximum network energy efficiency to construct the network multicast route. Simulation results show that the proposed approach is effective and feasible. [ABSTRACT FROM AUTHOR]