基于学习的能量采集认知M2M通信资源分配算法

本文针对能量采集认知机器到机器（Machine-to-Machine,M2M）通信的能量效率问题，在保证服务质量（Quality of Service,QoS）的条件下，提出了一种能效优化算法.以最大化网络中用户能效为目标，综合考虑传输功率控制、时隙分配、传输模式选择、中继选择以及每个设备的能量状态为约束，将优化问题建模为一个混合整数非线性规划问题.将该能效优化问题转化为离散时间有限状态马尔科夫决策过程（Discrete-time and Finite-state Markov Decision Process,DFMDP）进行求解.提出一种基于深度强化学习的算法寻找最优策略.仿真结果表明，所提算法在平均能效方面优于其他方案，且收敛速度在可接受范围内.     

无线EH认知物联网网络资源分配研究

由于5G技术的快速发展,基于能量采集的认知物联网(Internet of things,IOT)具有很大的应用前景。针对无线物联网网络中存在的"doubly-near-far"问题,考虑在认知物联网网络中将能量采集与信息接收站分开管理,提出了一个基于能量采集的异构认知物联网网络模型,实现用户能效的最大化。此外,该模型不仅考虑能量采集,还考虑了频谱利用率低、频谱资源稀缺的问题,针对该网络优化问题,提出了一个混合整数非线性规划问题,通过信道分配、功率控制以及时间分配的联合优化的方法,考虑用户数据速率、干扰约束的同时,最大化能效。仿真实验结果证明了所提出模型以及算法的有效性。     

非线性能量收集认知无线电网络的次用户吞吐量最大化方案

针对一对主用户和M对次用户构成的认知无线电网络（cognitive radio network,CRN），研究了非线性能量收集的认知无线电网络的次用户吞吐量最大化问题。具体来说，对于考虑次用户发射器（secondary transmitter,ST）电路功率的情况，首先将主用户吞吐量需求下的次用户吞吐量最大化（secondarythroughput maximization,STM）问题建模为一个非线性优化问题，然后将它转化成凸优化问题，最后提出一种联合使用黄金分割和二分法的低复杂度算法，获得主用户发射器（primarytransmitter,PT）能量传输和次用户信息传输的最优时间分配以及主用户发射器的最优发射功率。对于忽略次用户发射器电路功率的情况，首先证明次用户吞吐量最大化问题的凸特性，然后设计了一个更高效的算法来求解。仿真结果表明，相比等时间分配方案和链路增益优先级方案，提出的设计算法能显著提升次用户吞吐量。     

基于能量采集的译码转发中继系统功率分配算法

本文针对基于能量采集的译码转发（DF）中继蜂窝异构网络,提出了一种系统容量最大化的功率分配算法。中继和用户节点均采集由基站发送的射频信号的能量;利用采集到的能量,通过时分多址方式,用户节点经中继将信息发送给基站。在满足中继和用户节点采集能量的因果性限制及总功率受限条件下,构建了系统容量的优化模型。利用拉格朗日乘子法和KKT (Karush-Kuhn-Tucker)最优条件,为使系统容量最大化,对中继和用户功率进行分配;通过等效信道增益,将中继功率和用户功率联合优化问题简化为用户功率优化问题,然后通过次梯度算法获得功率最优解。仿真结果表明,与受限于中继和用户采集能量因果性的用户平均功率算法相比较,本文算法可以提高系统平均容量。      

云无线接入网络高能效功率分配和波束成形联合优化算法

针对云无线接入网络(C-RAN)的资源分配问题,该文采用max-min公平准则作为优化准则,以C-RAN用户的能量效率作为优化目标函数,在满足最大发射功率和最小传输速率约束条件下,通过最大化最差链路的能量效率来实现用户发射功率和无线远端射频单元(RRHs)波束成形向量的联合优化。上述优化问题属于非线性、分式规划问题,为了方便求解,首先将原优化问题转化为差分形式的优化问题,然后通过引入变量将差分形式的、非平滑优化问题转化为平滑优化问题。最终,提出一种双层迭代功率分配和波束成形算法。在仿真实验中,将该文算法与传统的非能效资源分配算法和能量效率最大化算法进行了比较,实验结果证明该文算法在改进C-RAN能量效率和提高资源分配公平性方面的有效性。     

认知Ad Hoc网络能量有效频谱接入策略

针对认知无线Ad Hoc网络中次用户能量受限问题,提出一种基于能量有效性的机会频谱接入策略。联合考虑信道状态的时变性和次用户的频谱感知准确性,基于部分可观测马尔科夫决策过程（POMDP）建立了一种最大化能量有效性的分析架构,指导次用户选择能效最佳信道,并根据信念状态、信道增益和检测概率,自适应控制传输功率。仿真结果表明,该策略能够有效提高次用户传输的能量有效性,通过对传输功率的有效控制,实现了传输性能和能量开销的有效折中。      

多信道认知用户能量高效的最优功率分配

针对多信道认知用户能量效率问题,提出认知用户能量效率优化模型,进而优化传输功率和感知帧长。首先,多信道认知用户基于多带宽联合能量检测方案,在一定传输功率和干扰功率限制下,建立了以单位数据能耗为目标的最优化问题;其次,通过非线性分式规划的对偶优化将目标函数转换为内点法求解形式;然后,结合内点法和二分法给出算法流程,进而配置最优功率和感知时间。仿真结果表明,对应不同通信环境采用该优化方法都能通过配置最优功率和感知时间达到能量效率最优。     

认知无线电网络中基于跨层设计的能效优化算法

为提高认知无线电网络中次用户节点的能量有效性,该文基于连续时间马尔科夫理论对次用户的频谱感知和接入过程进行联合建模,对影响次用户传输能效的主要因素进行了分析,提出了一种基于跨层设计的能量有效优化算法。该算法可有效减小主用户非时隙返回信道对次用户能量有效性的影响,并通过联合优化感知时间和接入概率,使次用户在感知性能和传输能效间实现了有效折衷。仿真结果表明,本文算法相对于仅考虑频谱感知或接入策略的单层优化算法,可使次用户的能量有效性得到较大提高。      

基于OFDM的认知无线电系统功率分配研究

分析了基于OFDM的认知无线电系统中认知用户和授权用户之间的相互干扰,以及下行链路对认知用户进行功率分配的优化目标,并给出了速率最大化优化目标下的最优功率分配方案。授权用户能够承受的干扰功率成为认知无线电系统功率分配问题的主要限制因素,其限制了认知用户的发射功率和传输速率,认知用户传输产生的干扰必须满足授权用户能够承受的干扰功率限制。     

基于能效的NOMA蜂窝车联网动态资源分配算法

在支持车与车直接通信(V2V)的非正交多址接入(NOMA)蜂窝网络场景下,针对V2V用户与蜂窝用户的干扰以及NOMA准则下的功率分配问题,该文提出一种基于能效的动态资源分配算法。该算法首先为了保证V2V用户的时延及可靠性同时满足蜂窝用户的速率需求,联合考虑子信道调度、功率分配和拥塞控制,建立了最大化系统能效的随机优化模型。其次,利用李雅普诺夫随机优化方法,通过控制可接入数据量保证队列稳定性以避免网络拥塞,并根据实时网络负载状态动态地进行资源调度,设计一种次优化子信道匹配算法获得用户调度方案,进一步,利用凸优化理论和拉格朗日对偶分解方法得到功率分配策略。最后,仿真结果表明,该文算法可以满足不同用户的服务质量(QoS)需求,并在保证网络稳定性前提下提高系统能效。     

Combined spatial-temporal energy harvesting and relay selection for cognitive wireless powered networks

In order to improve the Energy Efficiency (EE) and spectrum utilization of Cognitive Wireless Powered Networks (CWPNs), a combined spatial-temporal Energy Harvesting (EH) and relay selection scheme is proposed. In the proposed scheme, for protecting the Primary User (PU), a two-layer guard zone is set outside the PU based on the outage probability threshold of the PU. Moreover, to increase the energy of the CWPNs, the EH zone in the two-layer guard zone allows the Secondary Users (SUs) to spatially harvest energy from the Radio Frequency (RF) signals of temporally active PUs. To improve the utilization of the PU spectrum, the guard zone outside the EH zone allows for the constrained power transmission of SUs. Moreover, the relay selection transmission is designed in the transmission zone of the SU to improve the EE of the CWPNs. In addition to the EE of the CWPNs, the outage probabilities of the SU and PU are derived. The results reveal that the setting of a two-layer guard zone can effectively reduce the outage probability of the PU and improve the EE of CWPNs. Furthermore, the relay selection transmission decreases the outage probabilities of the SUs.     

Optimal Energy Harvesting-based Weighed Cooperative Spectrum Sensing in Cognitive Radio Network

In cognitive radio (CR) network, to improve spectrum sensing performance to primary user (PU) and decrease energy wastage of secondary user (SU) in cooperative spectrum sensing, an energy harvesting-based weighed cooperative spectrum sensing is proposed in this paper. The SU harvests the radio frequency (RF) energy of the PU signal and then converts the RF energy into the electric energy to supply the power used for energy detection and cooperation. The time switching model and power splitting model are developed to realize the notion. In the time switching model, the SU performs either spectrum sensing or energy harvesting at any time, while in the power splitting model, the received PU signal is split into two signal streams, one for spectrum sensing and the other one for energy harvesting. A joint optimization problem is formulated to maximize the spectrum access probability of the SU by jointly optimizing sensing time, number of cooperative SUs and splitting factor. The simulation results have shown that compared to the traditional cooperative spectrum sensing, the proposed energy harvesting-based weighed cooperative spectrum sensing can decrease the energy wastage obviously while guaranteeing the maximum spectrum access probability.     

可见光无线信能同传网络中能量有效的波束赋形设计

物联网是6G的核心应用场景,然而由于射频频谱资源稀缺,为数以百亿计的物联网设备提供高质量无线覆盖服务面临挑战。可见光通信(Visible Light Communication, VLC)作为射频通信的补充,提供了丰富的高频频谱资源。该文研究多用户VLC无线信能同传网络的可达能量效率(Energy Efficiency, EE)性能界,即在用户信息和能量需求、避免LED谐波失真以及VLC发射机总功率约束下最大化EE。为求解所考虑的问题,结合Dinkelbach方法和连续凸近似方法构建迭代算法优化波束赋形向量和直流偏置。从理论上证明了所提算法的收敛性,并讨论了避免LED谐波失真的工作条件对EE的影响。仿真结果验证了所提方法的有效性,分析了信息需求、能量需求和VLC发射机总功率对EE的影响规律,并讨论了LED视野对EE和VLC信号传播的影响。     

Recent advances and future challenges of four key resources cooperation in cognitive radio network

Cognitive radio (CR) can improve spectrum utilization by spectrum sharing or cooperation between the primary user and secondary users.It is well known that energy,interference and relay are also three key resources in cognitive radio network (CRN).Energy cooperation or sharing between the primary user and secondary user will further promote energy efficiency.Energy harvesting from RF interference signal can turn bane (interference) into a boon (green energy).Secondary user relay data of the primary user can enhance QoS of the primary user,also get some opportunities for their own transmission.Thus,four resources cooperation (spectrum,energy,interference,relay) in CRN will improve simultaneously both spectrum efficiency and energy efficiency,and also increase throughput and QoS.The overviews for collaborative utilization problems of four key resources in CRN was given.Firstly,collaboration models of four key resources were analyzed.Then,recent research advances were summarized,including three kinds of resources collaborative utilization (both energy harvesting and relay transmission,both energy cooperation and energy harvesting) and four resources collaborative utilization (simultaneous relay transmission,energy harvesting and energy cooperation) in CRN.Further,some potential challenges of four key resources cooperation in CRN were discussed.Finally,some key future research directions was concluded.     

认知无人机网络中次级链路吞吐量优化研究

无人机(UAV)的便携性和高机动性使其与认知无线电(CR)结合的应用场景更加实用。在构建的无人机认知无线网络(CRN)模型中,该文提出UAV单弧度吞吐量优化方案,在确保检测概率的前提下优化感知弧度最大化UAV平均吞吐量。考虑在信道条件不理想情况下进一步改善感知性能,提出基于协作频谱感知(CSS)的多弧度吞吐量优化方案,利用交替迭代优化(AIO)算法对感知弧度和弧度数量进行联合优化以最大化吞吐量。仿真结果表明,该文提出的多弧度协作频谱感知方案在信道衰落严重时,对于主用户(PU)服务质量(QoS)和UAV吞吐量有明显提升。     

Throughput analysis in censoring-based cooperative cognitive radio network with energy harvesting

An energy harvesting (EH) and cooperative cognitive radio (CR) network (CRN) is studied in this paper where CR users transmit data through a primary user (PU) channel if the channel remains idle, else an optimal number CRs helps in transmission of PU. To achieve the optimum number of CRs (ONCR) involved in cooperation, a novel scheme based on a combination of channel censoring and total error is proposed. The performance of the proposed scheme is investigated under RF harvesting scenario. The EH is dependent on sensing decision and a CR source harvests energy from PU's RF signal. The harvested energy (HE) is split into two parts: One part is used by the CR network (CRN) for its own transmission, and the other part is used for supporting PU. The effect of the energy allocation factor on total throughput is also investigated. New expressions for optimal number of CRs and throughput are developed. The effect of network parameters such as sensing time, censoring threshold, and energy allocation parameter (EAP) on throughput is investigated. Impact of distance between nodes is also studied.     

Robust energy efficiency power allocation for relay-assisted uplink cognitive radio networks

In this paper, we investigate a worst-case robust power allocation scheme to improve energy efficiency (EE) for an amply-and-forward relaying uplink underlay OFDM cognitive radio system with imperfect channel situation information about the channel between primary user (PU) and secondary user (SU) and the channel between SU and corresponding relay. Specifically, a max–min problem is formulated to transform the original optimization problem into maximum EE on minimum throughout channel, and an epigraph problem is introduced to obtain analytical expressions of objective power allocation. Simulation results show that the proposed EE power allocation scheme is valid and effective in EE and robustness.     

认知无线电网络的物理层安全研究及其鲁棒性设计

该文从用户服务质量(QoS)的角度研究了多输入单输出(MISO)认知无线电网络的物理层安全问题。通过在次用户的发送信号中加入适当功率的人为噪声,能够有效地提高网络的物理层安全性能。经过适当的变换,将次用户的安全优化问题转化为一个半定规划,从而可以有效地求得次用户的最优发射方案。另外,针对信道状态信息不确定性的问题,在假设已知信道状态信息误差范围的前提下,采用最差性能最优的方法对系统进行鲁棒性设计,以保证即使在信道状态信息误差最大的情况下,依然可以满足系统的约束条件。最后,通过仿真验证了算法的有效性。     

Throughput optimization using simultaneous sensing and transmission in energy harvesting cognitive radio networks

A three‐dimensional continuous‐time Markov model is proposed for an energy harvesting cognitive radio system, where each secondary user (SU) harvests energy from the ambient environment and attempts to transmit data packets on spectrum holes in an infinite queuing buffer. Unlike most previous works, the SU can perform spectrum sensing, data transmission, and energy harvesting simultaneously. We determine active probability of the SU transmitter, where the average energy consumption for both spectrum sensing and data transmission should not exceed the amount of harvested energy. Then, we formulate achievable throughput of secondary network as a convex optimization problem under average transmit and interference energy constraints. The optimal pair of controlled energy harvesting rate and data packet rate is derived for proposed model. Results indicate that no trade‐off is available among harvesting, sensing/receiving, and transmitting. The SU capability for self‐interference cancelation affects the maximum throughput. We develop this work under hybrid channels including overlay and underlay cases and propose a hybrid solution to achieve the maximum throughput. Simulation results verify that our proposed strategy outperforms the efficiency of the secondary network compared to the previous works.     

Joint optimisation of transmission and waiting times in cognitive radio

Transmission time optimisation is one of the key considerations of cognitive network design. There are many studies in cognitive radio networks (CRNs) focusing on finding the best transmission time for secondary users (SUs) to maximise transmission or energy efficiency. While longer sensing duration leads to a higher sensing accuracy and causes less interference, the SU spends less time for transmission and more energy on sensing spectrum. On the other hand, when the transmission duration becomes longer, although the SU has more opportunities to access the channel, it may encounter higher interference due to primary user (PU) returns and the probability of collision becomes higher. In this article, in a decentralised slotted protocol for CRN, the SU spectrum access is proved as a renewal process, then the interference due to PU return during SU transmission, the missed opportunities due to waiting for the channel to become idle and the energy consumed by the SU in the whole spectrum access process including idling energy, transmission energy and sensing energy consumption are formulated and integrated into newly defined efficiency to obtain the optimum transmission time and waiting time.