Low-Power Wake-Up Radio for Wireless Sensor Networks

Power consumption is a critical issue in many wireless sensor network scenarios where network life expectancy is measured in months or years. Communication protocols typically rely on synchronous operation and duty-cycle mechanisms to reduce the power usage at the cost of decreased network responsiveness and increased communication latency. A low-power radio-triggered device can be used to continuously monitor the channel and activate the node for incoming communications, allowing purely asynchronous operations. To be effective, the power consumption of this wake-up device must be on the order of tens of microwatts since this device is always active. This paper presents our first attempt at designing such a low-power receiver. Very few realizations of wake-up devices are reported in the literature and none presents power dissipation below 40 μW. Our design implements a complete wake-up device and initial results indicate an average power consumption below 20 μW, which is more than 2 times lower than other reported devices.     

On the Trade-Off between Energy and Multicast Efficiency in 802.16e-Like Mobile Networks

In this paper, we define a new problem that has not been addressed in the past: the trade-off between energy efficiency and throughput for multicast services in 802.16e or similar mobile networks. In such networks, the mobile host can reduce its energy consumption by entering the sleep mode when it is not supposed to receive or transmit information. For unicast applications, the tradeoff between delay and energy efficiency has been extensively researched. However, for mobile hosts running multicast (usually push- based) applications, it is much more difficult to determine when data should be transmitted by the base station and when each host should enter the sleep mode. In order to maximize the channel throughput while limiting the energy consumption, a group of hosts needing similar data items should be active during the same time intervals. We define this as an optimization problem and present several algorithms for it. We show that the most efficient solution is the one that employs cross-layer optimization by dividing the hosts into groups according to the quality of their downlink physical (PHY) channels.     

异构云无线接入网下基于功率域NOMA的能效优化算法

针对异构云无线接入网络的频谱效率和能效问题,该文提出一种基于功率域-非正交多址接入(PD-NOMA)的能效优化算法。首先,该算法以队列稳定和前传链路容量为约束,联合优化用户关联、功率分配和资源块分配,并建立网络能效和用户公平的联合优化模型;其次,由于系统的状态空间和动作空间都是高维且具有连续性,研究问题为连续域的NP-hard问题,进而引入置信域策略优化(TRPO)算法,高效地解决连续域问题;最后,针对TRPO算法的标准解法产生的计算量较为庞大,采用近端策略优化(PPO)算法进行优化求解,PPO算法既保证了TRPO算法的可靠性,又有效地降低TRPO的计算复杂度。仿真结果表明,该文所提算法在保证用户公平性约束下,进一步提高了网络能效性能。     

异构云无线接入网下基于功率域NOMA的能效优化算法

针对异构云无线接入网络的频谱效率和能效问题,该文提出一种基于功率域-非正交多址接入(PD-NOMA)的能效优化算法.首先,该算法以队列稳定和前传链路容量为约束,联合优化用户关联、功率分配和资源块分配,并建立网络能效和用户公平的联合优化模型;其次,由于系统的状态空间和动作空间都是高维且具有连续性,研究问题为连续域的NP-hard问题,进而引入置信域策略优化(TRPO)算法,高效地解决连续域问题;最后,针对TRPO算法的标准解法产生的计算量较为庞大,采用近端策略优化(PPO)算法进行优化求解,PPO算法既保证了TRPO算法的可靠性,又有效地降低TRPO的计算复杂度.仿真结果表明,该文所提算法在保证用户公平性约束下,进一步提高了网络能效性能.     

Maximum Lifetime Routing Problem in Duty-Cycling Sensor Networks

In order to extend the lifetime of a wireless sensor network, the energy consumption of individual sensor nodes need to be minimized. This can be achieved by minimizing the idle listening time with duty cycling mechanism and/or minimizing the number of communications per node. The nodes will have different relay loads for different routing strategies: therefore, the routing problem is important factor in minimization of the number of communications per node. In this paper, we investigate achievable network lifetime with a routing mechanism on top of an existing duty-cycling scheme. To this end, we formulated the routing problem for duty-cycling sensor network as a linear programming problem with the objective of maximizing the network lifetime. Using the developed linear programming formulation, we investigate the relationship between network lifetime and duty-cycling parameter for different data generation rates and determine the minimum duty-cycling parameter that meets the application requirements. To the best of our knowledge, this is the first mathematical programming formulation which addresses the maximum lifetime routing problem in duty-cycling sensor network. In order to illustrate the application of the analytical model, we solved the problem for different parameter settings.     

Robust Energy Efficiency Power Allocation for Uplink OFDM–Based Cognitive Radio Networks

This paper studies the energy efficiency power allocation for cognitive radio networks based on uplink orthogonal frequency‐division multiplexing. The power allocation problem is intended to minimize the maximum energy efficiency measured by “Joule per bit” metric, under total power constraint and robust aggregate mutual interference power constraint. However, the above problem is non‐convex. To make it solvable, an equivalent convex optimization problem is derived that can be solved by general fractional programming. Then, a robust energy efficiency power allocation scheme is presented. Simulation results corroborate the effectiveness of the proposed methods.     

Estimating Clock Uncertainty for Efficient Duty-Cycling in Sensor Networks

Radio duty cycling has received significant attention in sensor networking literature, particularly in the form of protocols for medium access control and topology management. While many protocols have claimed to achieve significant duty-cycling benefits in theory and simulation, these benefits have often not translated into practice. The dominant factor that prevents the optimal usage of the radio in real deployment settings is time uncertainty between sensor nodes which results in overhead in the form of long packet preambles, guard bands, and excessive control packets for synchronization. This paper proposes an uncertainty-driven approach to duty-cycling, where a model of long-term clock drift is used to minimize the duty-cycling overhead. First, we use long-term empirical measurements to evaluate and analyze in-depth the interplay between three key parameters that influence long-term synchronization: synchronization rate, history of past synchronization beacons, and the estimation scheme. Second, we use this measurement-based study to design a rate-adaptive, energy-efficient long-term time synchronization algorithm that can adapt to changing clock drift and environmental conditions, while achieving application-specific precision with very high probability. Finally, we integrate our uncertainty-driven time synchronization scheme with the BMAC medium access control protocol, and demonstrate one to two orders of magnitude reduction in transmission energy consumption with negligible impact on packet loss rate.     

Trade-Off Analysis of Energy Consumption and Image Quality for Multihop Wireless Sensor Networks

It has become necessary in recent years to observe and monitor some physical phenomena. This was made possible by the emergence of wireless sensor networks. The main characteristic of such networks is nodes with scarce resources. Given the stringent resource constraints, nodes are limited in energy, memory and computational power. These resource constraints pose serious difficulties for image processing and transmission to the destination. Therefore, image transfer in wireless sensor networks presents major challenge which raises issues related to its representation, its storage and its transmission. Based on wavelet transform an Adaptive Energy Efficient Wavelet Image Compression Algorithm is proposed in order to be suitable for wireless sensor network. In addition, an identification of the wavelet image compression parameters is investigated to analyze the trade-offs between the energy saving, and the image quality. Performance studies indicate that the proposed scheme enabling significant reductions in computation as well as communication energy needed, with minimal degradation in image quality.     

Energy Harvesting for Cooperative Cognitive Radio Networks

Wireless Personal Communications - In this paper, we analyze the performance of cooperative cognitive radio networks where the secondary nodes harvest energy from radio frequency signals. Our...     

认知无线电频谱感知技术综述

针对频谱资源匮乏这一问题,认知无线电技术在提高频谱利用率方面应用前景广泛,而频谱感知作为认知无线电技术实现的前提条件,是目前无线电领域的一个研究热点。近年来人们提出了很多种频谱感知的方法,综述了频谱感知技术的研究进展,对几种典型的传统频谱感知模型进行对比介绍,讨论了几种新型的感知技术,并对各种技术的性能进行深入分析,最后指出了频谱感知研究的挑战及发展趋势。     

Energy and Latency-Aware Scheduling Under Channel Uncertainties in LTE Networks for Massive IoT

The machine-to-machine (M2M) communication is an enabler technology for internet of things (IoT) that provides communication between machines and devices without human intervention. One of the main challenges in IoT is managing a large number of machine-type communications co-existing with the human to human (H2H) or human type communications. Long term evolution (LTE) and LTE-advanced (LTE-A) technologies due to their inherent characteristics like high capacity and flexibility in data access management are appropriate choices for M2M/IoT systems. In this paper, a two-phase intelligent scheduling mechanism based on interval type-2 fuzzy logic to (1) satisfy QoS requirements, (2) ensure fair resource allocation and (3) control energy level of devices for coexistence of M2M/H2H traffics in LTE-A networks, is presented. The proposed interval type-2 fuzzy Logic mechanism enhances data traffic efficiency by predicting and handling the network uncertainties. The performance of the proposed algorithm is evaluated in terms of various metrics such as delay, throughput, and bandwidth utilization.     

Energy Efficiency of Heterogeneous Networks in LTE-Advanced

Traditionally mobile operators have met the surge in mobile data traffic and the growing number of rural subscribers by deploying more macro base stations. This increases overall energy consumption, operational costs and carbon footprint of cellular networks. In this paper we investigate solutions for reducing the number and size of active macrocells following traffic load conditions in both homogeneous and heterogeneous networks. Results are presented as overall energy reduction gains for homogeneous macro-only and micro-only networks and heterogeneous joint macro-relay and micro-relay networks, using long-term-evolution-advanced technology. Results show that reducing the number of active cells using sleep mode at base stations, in low to medium traffic load conditions, combined with the deployment of small cells offer energy gains in both homogeneous and heterogeneous networks. However, the most significant gains are observed in heterogeneous networks.     

合作认知无线网络中能效最优资源分配

针对能量受限的合作认知网络,该文研究在保证主用户服务质量要求下,认知用户能量效率最大化问题。认知用户利用信能同传技术接收主用户信号,并采用解码转发协议协助主用户通信。基于分式规划和引入辅助变量将原始非凸问题转换为凸优化问题进行求解,并提出一种迭代的资源分配算法。仿真结果表明,所提算法能够快速收敛于最优解。与能量合作方案相比,该文所采用方案能量效率显著提高,同时能更好地保证主用户服务质量要求。     

Energy Efficiency Optimization of NOMA IoT Communication for 5G

Mobile Networks and Applications - With the rapid increase in the number of mobile users and the continuous emergence of new wireless multimedia services, 5G mobile communication technology that...     

超高频RFID系统与其他无线网络的电磁兼容性研究

无线射频识别（RFID）技术与互联网、移动通信网络等技术结合应用,可以实现全球范围内物品跟踪与信息共享。然而,RFID作为无线通信系统,其发射的射频信号可能对其它无线网络造成干扰,降低系统性能,影响系统正常工作。中国已经发布了840～845MHz和920～925MHz频段RFID的试用标准,其中920～925MHz的RFID应用和点对点立体声广播处在一个同一个频段,与无中心对讲机和GSM网络处在相邻频段,RFID系统与这些系统之间的电磁兼容性就成为系统能否稳定实现的最主要因素。     

面向大规模物联网的无人机通信感知一体化能效优化算法

针对大规模物联网场景下无人机通信感知一体化系统存在的重复感知和能量受限等问题,提出了一种基于聚类算法的能效优化方案。该方案在满足无人机的移动性和感知能力约束下,通过联合设计无人机的三维轨迹和发射功率来最大化系统能效。由于该问题是非凸的,首先将其解耦为两个子问题,然后利用模拟退火算法和标准凸优化技术来求解无人机的悬停位置和飞行速度以获取最优轨迹,最后根据最优轨迹推导发射功率的闭合表达式,求得每个悬停位置的最优发射功率。与传统的二维和三维方案相比,所提基于聚类的能效优化方案在收敛速度提高4倍的基础上能提升20%~30%系统能效。     

认知无线电中频谱感知技术的研究进展

认知无线电技术作为解决当前频谱利用率低下这一问题的有效手段,已成为无线电发展的一个新的里程碑。频谱感知作为实现认知无线电的首要任务,主要涉及物理层的信号检测与处理以及链路层的控制与优化。文中对频谱感知技术的最新研究进展情况进行了综述,重点总结和分析了检测算法的性能、协作融合算法以及感知机制的参数优化,并在此基础上讨论了下一步的研究方向。     

无线网络能效的优化与评估

文章从能效测度入手,对已有的无线网络能效测度评价体系进行了讨论,并提出以碳排放量为标准和与网络负载相结合的能效测度模型。在能效测度模型的基础上,文章提出减少设备使用、无线资源调度、节点协作等一系列无线网络能效优化方法,并建议在无线网络协议架构中加入能效监控和能效评估模块。文章还对无线网络能效优化和评估方法中存在的技术挑战进行了展望。     

译码转发中继网络的能量效率分析

随着人们资源节约与环保意识增加,如何获得较高的能量效率成为了绿色通信中一个重要而又棘手的问题。因此,本文研究了译码转发协议下的直接传输、单向中继、双向中继三种传输方式的能量效率。首先在瑞利信道环境下推导了能量效率的闭合表达式,然后通过凸优化算法使得能量效率达到最大。最后,还分析了信道衰落情况、发射的比特数、中继位置和系统电路功率对系统能量效率的影响。仿真结果表明,电路功率对系统的能量效率影响较大;双向中继在发送比特数对等、源节点至中继的距离相同时,其能量效率才达到最优;而当源节点至中继的距离差异较大时,单向中继的能量效率比双向中继性能更好;信道衰落较大时,双向中继比单向中继和直传更有优势。