D2D网络中基于联盟博弈的中继选择方法

随着无线终端的大规模普及,用户设备（User Equipment,UE）对无线网络的内容分发服务提出了更高的要求。提出了利用设备对设备（Device to Device,D2D）通信技术进行协作中继传输,使得任何UE都可作为潜在中继节点,并且令中继节点为其他UE中继数据,可以提升整体网络的内容分发质量。为弥补UE作为中继节点产生的能耗,采用能量采集（Energy Harvesting,EH）的激励机制,将携能信号作为奖励发送至UE,以提高UE为其他用户中继数据的意愿。同时,为解决中继选择问题,提出了基于联盟博弈方法,对UE和中继节点的合作行为进行分析,为UE选取最优的中继节点,以获取最优的内容分发服务。仿真结果表明,所提方法与贪婪搜索算法相比,可以更大程度地提高系统的吞吐量。     

提高蜂窝网络中数据分发效率的D2D协作转发算法

Device-to-Device(D2D)通信是一种移动终端在蜂窝通信系统的控制下使用授权频段进行点到点通信的新型技术。通过允许接收终端间的数据转发,D2D通信可以用来提高蜂窝网络中的数据分发效率。现有的终端间转发算法,没有充分考虑D2D链路的差异,很难实现频谱资源的高效利用。为此,该文提出了一种基于多跳中继的D2D协作转发算法,包括多播和单播两个模式。该算法根据D2D链路质量自适应地选择最优的中继、路由及传输跳数,能够充分利用D2D链路的多信道分集增益。仿真结果表明,该文所提出的算法能够显著地提高D2D转发的资源利用率,进而提升数据分发业务的吞吐量。     

基于自私行为分析的超密集D2D中继选择算法

在超密集D2D通信中,目前的中继选择方案主要假定中继设备具有主动意愿参与数据转发,但部分理性中继设备出于自身考虑,可能会存在时延或拒绝转发的自私行为,进而影响用户体验效果。从中继设备自私行为角度出发,提出了D2D通信中自私中继设备识别方法,进而提出了基于自私行为分析的超密集D2D中继选择算法。首先,定义了联合兴趣度、转发历史比率和中继物理状态3个中继识别属性因子,并通过三角模糊函数计算三者的权重,从而对具有自私行为的中继设备完成识别。其次,基于理想解相似性偏好排序方法实现了中继设备的最终选择方案。仿真结果表明,所提算法能更有效地识别D2D通信中的自私中继设备,与其他中继选择算法相比,在D2D通信转发成功率、系统平均吞吐量和平均时延等方面均取得了显著进步。     

D2D通信中基于社交门限的最优中继选择方案

在基于设备直传(D2D)通信的中继系统中,提出了一种基于社交感知的增强型中继选择策略.该策略首先在D2D中继网络中引入社交门限值,对潜在中继用户进行筛选和过滤,从而有效降低了探测成本;然后利用最优停止理论实现了最优中继节点的选择.仿真结果表明,与已有中继选择策略相比,所提出的策略能够以较少的中继探测次数获得较高的系统性能收益,从而实现能耗与收益之间的折中.     

面向蜂窝网络的D2D多播通信的分簇和中继选择方法

传统蜂窝网络中,信道衰减的随机性和不确定性导致小区边缘用户的接收性能很差,尤其是面向视频传输等速率要求较高时其弊端更加凸显。D2D通信因其配置灵活性可作为传统蜂窝网络架构的有利补充,能有效改善边缘用户的性能。该文针对D2D通信的多播传输,分析了系统最小时延成本下的中继数量和分簇算法,提出一种基于分簇和中继选择的低时延D2D多播方案。该方案可以自适应选择多播重传中的中继的数量和中继节点到基站的距离,同时给出最优的带宽资源分配机制。仿真结果表明,与其他方案相比,所提方法能有效减少系统时延,提高边缘用户体验和系统性能。     

D2D辅助的协作中继NOMA系统中TSRS策略及其中断性能分析

该文研究了D2D辅助的协作中继NOMA（DC-NOMA）网络,在中继用户（RU）转发信息的第二时隙,利用RU到蜂窝中心用户（CCU）的D2D通信链路传输新的信号。为了提高传输可靠性,设计了新的信号检测策略,通过完全利用边缘信息消除了用户间的干扰。基于新的信号检测策略,提出了一种两阶段中继选择策略（TSRS）。在满足蜂窝边缘用户（CEU）可靠接收的中继集合中,选择使CCU成功解码概率最大的中继。为了评估所提出的DC-NOMA方案,推导了每个用户的确切中断概率且通过仿真得到验证。仿真结果表明,在高信噪比区域,该文所提出的基于新的信号检测策略的DC-NOMA在TSRS方案下的中断性能优于部分中继选择方案（PRSS）和传统的DC-NOMA。特别地,增大中继数量可有效提高DC-NOMA系统的中断性能。      

基于D2D中继的异构网络负载均衡策略

提出了一种基于设备间数据直传(D2D)中继的异构网络负载均衡策略,通过设备之间的直接数据传输,将满载大基站的数据分流到其覆盖范围内的空闲小基站中。具体提出了频谱资源和发射功率的联合资源分配算法,深入研究了在异构网络中利用D2D通信进行数据中继的传输速率最大化问题。仿真结果显示,提出的方法在保证原有用户的通信性能的前提下,增加了系统的可接入用户数和总体吞吐率,从而提升了自组织异构网络的整体性能。     

移动中继多播场景下的节能优化

设备间通信(D2D通信)通过复用蜂窝通信的频带资源,可以使近距离的用户直接通信,而无需通过基站进行中继.它的引入可以提升用户的服务质量,降低终端能耗,拓展小区的覆盖范围.特别的,在CDN场景中,可通过移动中继向请求相同业务内容的用户进行D2D广播传输.但是,在上述场景中,需考虑到移动终端(MT)的能耗和与蜂窝用户之间的同频干扰问题.基于此,提出了一种基于粒子群优化(PSO)算法的联合中继节点选择和功率控制机制来最小化移动中继的总能耗并同时保证两类用户的服务质量(QoS)需求得到满足.通过仿真,此方案效果得到了验证.     

基于LTE D2D技术的车联网通信架构与数据分发策略研究

基于5G通信技术的车联网面临高速率、低时延、高可靠性和大量流媒体数据分发等需求,提出了一种基于LTE D2D的车联网通信架构,设计基于运动一致性的车辆分簇算法,有效增加持续D2D通信时间,提高通信可靠性;其次,针对簇内车辆的流媒体数据分发,提出一种带时延约束的D2D协作中继转发策略,设计最优中继选择算法,大幅提高数据传输速率,提升网络吞吐量。     

基于D2D通信系统中的一种跨层中继选择算法

在D2D通信系统与蜂窝网络共存的场景下,引入中继节点可有效提高D2D链路的吞吐量和D2D用户对蜂窝用户的干扰。文中基于译码转发模式,结合跨层协作通信的思想,提出了一种基于物理层和数据链路层的跨层中继选择算法。该算法结合物理层的信道状态信息和数据链路层的队列状态信息,两个参数进行最优中继节点的选择。并最终通过仿真验证表明,基于跨层中继选择算法可提高通信系统的吞吐量,同时降低了通信系统的平均时延和数据包错误率。     

Optimal cooperative strategy based on quantum bat for cognitive radio of energy harvesting

In order to reduce energy consumption and improve spectral efficiency of the cognitive relay wireless communication system in 5G network,an optimal cooperative transmission strategy of information and energy was designed for cognitive relay radio with wireless energy harvesting.For the proposed optimal cooperative strategy,the maximal throughput formula and outage probability of secondary user were deduced.In order to resolve the derived maximum throughput equation,a quantum bat algorithm which was based on the optimization mechanism of quantum computing and bat algorithm was designed to solve the deduced equation,and the optimal cooperative transmission scheme for information and energy could be obtained.Simulation results show that the proposed optimal cooperative strategy not only can meet the information transfer demand of primary user,but also can realize the energy self-supply of the secondary user system and improve the communication quality of the secondary user.The proposed optimal cooperative strategy has a better performance than the cooperative strategy of existing cognitive relay radio for different simulation scenarios.     

一种基于源端网络编码和交替传输的中继协作方案

针对源节点通过两个中继向目的节点发送数据的无线通信系统,为了减小传统中继协作方案的复用损失,提出了一种将源端网络编码和交替传输有效结合起来的新方案,称为交替源端网络编码(SSNC)。该方案在源端每三个时隙对发送数据进行一次网络编码,并且两个中继在相邻的时隙中交替的发送和接收数据,每个时隙中,一个中继接收源端数据的同时另一个中继转发上一个时隙其接收到的数据给目的端。通过对该方案的中断概率和分集复用折中性能的推导和分析,发现该方案相对于传统的重复编码和分布式空时码方案在获得相同分集阶数的情况下有更高的传输效率,在实际的通信系统中可以兼顾性能和效率。仿真结果证实了我们的结论。      

An efficient resource optimization scheme for D2D communication

With the rapid development of wireless technologies, wireless access networks have entered their Fifth-Generation (5G) system phase. The heterogeneous and complex nature of a 5G system, with its numerous technological scenarios, poses significant challenges to wireless resource management, making radio resource optimization an important aspect of Device-to-Device (D2D) communication in such systems. Cellular D2D communication can improve spectrum efficiency, increase system capacity, and reduce base station communication burdens by sharing authorized cell resources; however, can also cause serious interference. Therefore, research focusing on reducing this interference by optimizing the configuration of shared cellular resources has also grown in importance. This paper proposes a novel algorithm to address the problems of co-channel interference and energy efficiency optimization in a long-term evolution network. The proposed algorithm uses the fuzzy clustering method, which employs minimum outage probability to divide D2D users into several groups in order to improve system throughput and reduce interference between users. An efficient power control algorithm based on game theory is also proposed to optimize user transmission power within each group and thereby improve user energy efficiency. Simulation results show that these proposed algorithms can effectively improve system throughput, reduce co-channel interference, and enhance energy efficiency.     

能量收集多跳D2D无线传感网络中的中继选择算法

针对无线功率传输技术的能量收集效率有限造成信噪比下降进而引发通信中断率增加的问题,在能量收集多跳D2D(Device to Device)无线传感网络中,提出一种基于改进K-means聚类的中继选择方法。首先,推导得到能量收集下的信噪比因子,使其作为K-means聚类特征。然后,利用最小欧氏距离原则得到距离聚类中心最近的实际节点的位置。最后,根据距离重排序得到中继节点,形成从源节点到目的节点的通信链路。仿真实验结果表明,相比最短路径算法和随机中继协作方案,所提出的改进算法链路信噪比更大,能够减小通信中断率,具有更好的中继性能。     

Hybrid time slot allocation algorithm based on LoRa Internet of things

To improve the efficiency and stability of data transmission in the long-range (LoRa) Internet of things (IoT),a hybrid time slot allocation algorithm is proposed, which implements a priority mechanism with high-priority nodes sending data in fixed time slots and low-priority nodes using the carrier sense multiple access (CSMA) algorithm to compete for shared time slots to transmit data. To improve network efficiency, a gateway is used to adjust the time slot allocation policy according to network status and balance the number of fixed and shared time slots. And more, a retransmission time slot is added to the time slot allocation algorithm, which redesigns the time frame structure, and adopts a retransmission mechanism to improve communication reliability. Simulation and measurement results show that the packet loss rate and transmission delay of the proposed hybrid algorithm are smaller than those of the fixed slot allocation algorithm, making the proposed algorithm more suitable for LoRa IoT.     

基于连续时隙预测的帧时隙Aloha防碰撞算法

在射频识别（Radio Frequency Identification,RFID）系统中,针对EPC C1G2协议的Q算法中Q值调整的不灵活性及对空闲时隙和碰撞时隙处理上的缺点,提出了一种基于连续时隙预测的帧时隙Aloha防碰撞算法.通过马尔可夫时隙状态模型,分析不同连续时隙状态下帧长与标签数的关系,提出连续时隙预测机制和自适应散列方案.有效地减少了无效时隙的出现,实现了读取阶段的时隙多数为成功时隙.仿真结果表明,本文提出的算法能够灵活地调整帧长,有效提高吞吐率,降低传输延时和开销,为物联网（Internet of Things,IoT）的海量数据信息完整性问题提供了合理的解决方案.     

A demand-based slot assignment algorithm for energy-aware reliable data transmission in wireless sensor networks

This paper proposes a new demand-based slot assignment (DSA) algorithm that allocates time slots based on the bandwidth demand of each node in a tree topology. DSA is basically different from SDA, DAS, or WIRES that assigns one large slot for each sensor node, but is similar to the frame-slot pair assignment (FSA) algorithm used in TreeMAC in that it assigns multiple small size slots for sensor nodes per each data collection round. DSA tackles the shortcomings of FSA in terms of the capability of packet aggregation and filtering, the balance of energy consumption, and bandwidth utilization. In general, nodes at lower tree depths process more packets and consume more energy than ones at higher tree depths, and thus the imbalanced energy consumption shortens network lifetime. The proposed algorithm allocates a sequence of receiving slots and then a sequence of sending slots to each node. This approach not only reduces the power consumption of nodes at lower depths significantly by allowing efficient data aggregation and filtering, but also it improves bandwidth utilization by removing wasted slots. In addition, the RTS and CTS messages are used within a slot for ensuring the reliability of data transmission and updating sync time between a child and its parent. Simulation results show that DSA far outperforms FSA in energy consumption and bandwidth utilization.