主用户干扰约束下的机会频谱接入感知−传输时隙优化调度

提出一种基于主用户干扰约束的机会频谱接入感知-传输时隙调度优化方案。首先,推导切换机制下认知系统的吞吐量和主用户干扰率,建立感知时间和感知周期联合优化模型;然后,在主用户干扰率和次用户感知质量双重约束下,推导了可最大化认知系统吞吐量的最优感知时间和感知周期的闭合表达式;最后,阐述了时隙优化调度方案并计算了认知系统可获得的最大吞吐量。仿真结果表明,所提出的时隙调度方案可以为认知系统提供更高的吞吐量,并更好地适应主用户干扰率和感知质量约束的变化。     

碰撞约束和非理想感知下认知多址接入信道的有效吞吐量

在碰撞约束和非理想信道信息下,研究认知多址接入信道中多个次用户接入主用户频谱的有效吞吐量问题。在机会频谱接入方式（OSA）下,定义有效吞吐量并作为次用户的性能指标。考虑信道质量信息,在信道质量分布参数未知的情况下采用有限的信道样本对参数进行估计,并对非理想感知下次用户的性能进行分析。通过仿真实验,分别讨论了信道质量门限与碰撞概率及次用户性能之间的关系,对比了理想感知和非理想感知下次用户的性能,并与其他算法进行对比,验证了本文接入策略的有效性。     

基于时间估计的动态频谱接入算法

基于先验知识模型,设计了基于信道剩余空闲时间估计的动态频谱接入算法：每个次用户根据感知历史维护信道剩余空闲时间的估计向量并周期进行更新,每个时隙开始时次用户选择剩余空闲时间估计最大的信道接入。对动态频谱接入算法的适应性问题进行了分析,并求得了次用户的最优传输时间长度。仿真结果表明,在给定的参数下,新算法的信道利用率比其他算法提高约5%-10%,同时对主用户的干扰保持最低。     

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。      

CVANET中基于POMDP模型的频谱接入算法

针对认知车载Ad Hoc网络(CVANET)信道的动态特性,以部分可观测马尔科夫决策过程(POMDP)为模型对认知车辆用户的频谱感知和频谱接入过程进行研究,提出基于POMDP模型的分布式机会频谱接入算法,并通过贪心算法降低POMDP算法计算量,最后通过仿真研究影响认知车辆用户吞吐量的主要因素,并验证算法的可行性。仿真分析结果表明,认知车辆用户通过本算法接入吞吐量得到有效提高,降低了交通中广播风暴的可能,并且降低了计算量。     

基于跨层优化的机会频谱接入算

针对周期性信道感知机会频谱接入系统,首先采用马尔可夫过程对次用户的感知活动进行建模分析,然后结合物理层和MAC层参数提出一个跨层性能指标--有效传输容量,并在最大化有效传输容量准则下提出一种跨层优化机会频谱接入算法,进而分析了机会频谱共享系统可获得的平均有效传输容量.理论分析和仿真结果表明,所提出的跨层优化接入算法性能优于单层优化接入算法,它可以使次用户获得更高的有效传输容量.     

基于最优停止的认知无线网络下行频谱接入算法

为有效平衡认知无线网络中次用户系统中接入信道的感知时间和信道总的吞吐量之间的矛盾,提出了一种只对部分信道进行感知的频谱接入策略,联合总的感知信道数和各条信道的感知时间进行优化,并通过最优停止算法求解,在最大化节省感知时间的同时,取得较大的平均吞吐量。与HC-MAC(Hardware Constrained- Media Access Control)算法的仿真分析对比表明,该算法在相同给定条件下感知时间更短,吞吐量更大,具有明显的优势。     

主用户活跃性对新的认知无线电系统容量的影响

在机会频谱接入认知无线电系统中,认知用户只有在通过感知确定信道空闲时才可以接入授权信道,因此频谱感知对于系统性能影响非常重要。本文提出了基于新帧结构的四元频谱感知模型,考虑主用户活跃性对认知网络吞吐量的影响,采用可同时最大化感知和数据传输时间的新帧结构模型,不需要考虑感知和吞吐量的均衡。理论分析新模型下感知时间,主用户活跃性,目标检测概率,主用户接收信噪比对系统吞吐量的影响,并与传统模型进行对比。     

基于认知无线电的双向中继网络的资源分配

针对认知无线电中的双向中继网络,研究了基于非完美感知的频谱机会式接入和频谱共享接入下的资源分配问题.与传统基于认知的双向中继的资源分配方法不同,提出的算法联合考虑了感知时间和次级系统的发射功率.在感知时间和发射功率满足条件的情况下,使次级系统的吞吐量最大.为了有效地保护主用户不受干扰,在每一跳都考虑了平均干扰功率约束,同时考虑次级系统总的功率约束.在非完美感知的频谱机会式接入和频谱共享接入机制下,新算法能够获得最优的感知时间和功率分配.最后,仿真比较了两种方案的性能,验证了新算法的有效性.     

基于POMDP的次用户多时隙信道选择算法

为了最大化次用户系统吞吐量,同时减少信道选择过程中的计算量,在多条主用户信道的次用户多时隙系统中,用半马尔科夫链(Partially Observable Markov Decision Process,POMDP)理论刻画次用户信道选择过程,并提出了对应的信道选择算法。在每一个时隙开始时,次用户选择部分信道进行感知,之后根据感知结果选择不同的传输功率接入信道,对于没有被感知的信道,次用户可以直接接入。对POMDP问题求解采用了最优策略、次优策略以及任意策略,并通过在不同仿真环境下的数值分析比较,论证了所提算法的实用有效。     

无人机短包通信中基于NOMA传输的安全性能分析

针对物联网（IoT）通信的低延时需求,为了保证数据传输的灵活性,本文构建一种基于短包传输的无人机（UAV）通信网络。由于非正交多址接入（NOMA）技术能够增加可服务的地面用户数量,故将该技术应用到无人机短包通信（UAV-SPC）系统中可以解决多用户的安全传输问题。与正交多址（OMA）技术相比,NOMA可有效提高用户接入公平性和频谱利用率,因此被广泛用于下行链路的通信传输。为解决复杂的安全传输问题,首先证明在功率和译码错误率约束的条件下,分别存在最优的功率分配,数据传输包长和系统传输比特数使目标用户的平均安全吞吐量最大。在此基础上,通过本文所提算法得到安全传输问题的优化解。实验结果验证了该算法的稳定性和可行性。此外,与基准方案相比,本文所提方案可有效降低短包传输的通信时延,提高系统中目标用户的平均安全吞吐量。     

Optimization of Time-Domain Combining Cooperative Spectrum Sensing in Cognitive Radio Networks

In cognitive radio networks, the secondary users take chances to access the spectrum without causing interference to the primary users so that the spectrum access is dynamic and somewhat opportunistic. Therefore, spectrum sensing is of significant importance. In this paper, we propose a novel time-domain combining cooperative spectrum sensing framework, in which the time consumed by reporting for one secondary user is also utilized for other secondary users’ sensing. We focus on the optimal sensing settings of the proposed sensing scheme to maximize the secondary users’ throughput and minimize the average sensing error probability under the constraint that the primary users are sufficiently protected. Some simple algorithms are also derived to calculate the optimal solutions. Simulation results show that fundamental improvement of the achievable throughput and sensing performance can be obtained by optimal sensing settings. In addition, our proposed scheme outperforms the general frame structure on either achievable throughput or the performance of average sensing error probability.     

An optimal OSA approach based on channel-usage estimate under collision probability constraint in cognitive radio systems

Opportunistic spectrum access system allows the secondary user to access spectrum holes not being utilized by the primary user. Traditional opportunistic spectrum access approaches only sense and utilize current spectrum holes. This can result in uncontrollable collision probability, which exceed the maximum collision probability allowed by the primary user network. In this paper, we consider a cognitive radio system with one primary channel and one secondary user, and then, we introduce a channel-usage pattern model and a fundamental access scheme in this system. Based on the fundamental access scheme, we adopt fixed detection duration and transmission duration ratio approach to analyze what and how to determine spectrum holes utilization and collision probability in this model. On the basis of this model and fundamental access scheme, we study optimal opportunistic spectrum access problem and formulate it as an optimization problem that the secondary user maximizes spectrum holes utilization under the constraint of collision tolerable level, and then we solve this optimization problem in two cases: one is that the idle period is exponential distribution, the other is that the idle period is Pareto distribution. According to the solution of the optimization problem, we respectively propose an optimal opportunistic spectrum access algorithm in each case. Theoretical analysis and simulation results both show that the optimal opportunistic spectrum access algorithms can maximize spectrum holes utilization under the constraint that the collision probability is bounded below collision tolerable level.     

Cross-Layer Based Opportunistic MAC Protocols for QoS Provisionings Over Cognitive Radio Wireless Networks

We propose the cross-layer based opportunistic multi-channel medium access control (MAC) protocols, which integrate the spectrum sensing at physical (PHY) layer with the packet scheduling at MAC layer, for the wireless ad hoc networks. Specifically, the MAC protocols enable the secondary users to identify and utilize the leftover frequency spectrum in a way that constrains the level of interference to the primary users. In our proposed protocols, each secondary user is equipped with two transceivers. One transceiver is tuned to the dedicated control channel, while the other is designed specifically as a cognitive radio that can periodically sense and dynamically use the identified un-used channels. To obtain the channel state accurately, we propose two collaborative channel spectrum-sensing policies, namely, the random sensing policy and the negotiation-based sensing policy, to help the MAC protocols detect the availability of leftover channels. Under the random sensing policy, each secondary user just randomly selects one of the channels for sensing. On the other hand, under the negotiation-based sensing policy, different secondary users attempt to select the distinct channels to sense by overhearing the control packets over the control channel. We develop the Markov chain model and the M/G^Y/1-based queueing model to characterize the performance of our proposed multi-channel MAC protocols under the two types of channel-sensing policies for the saturation network and the non-saturation network scenarios, respectively. In the non-saturation network case, we quantitatively identify the tradeoff between the aggregate traffic throughput and the packet transmission delay, which can provide the insightful guidelines to improve the delay-QoS provisionings over cognitive radio wireless networks.     

支持紧急通信的无线认知网络频谱接入方法

提出了支持应急通信的无线认知网络机会频谱接入模型。首先按照离散时间完全和限定(k=1)服务两级轮询策略实现主用户和次用户对频谱的共享。其次,通过在数据确认中捎带轮询列表信息方式实现数据传输和用户调度的并行处理,减少用户切换造成的时延浪费。通过建模分析得出网络吞吐量及用户平均等待时延的精确解析,结果表明本方案能有效抑制次用户对主用户通信质量的影响,又能增加网络吞吐量并为通信业务提供时延保障。     

Q学习算法在机会频谱接入信道选择中的应用

针对“先听后传”的机会频谱接入中认知用户的信道选择问题,本文提出了一种基于Q学习的信道选择算法。在非理想感知的条件下,通过建立认知用户的信道选择模型并设计恰当的奖励函数,使智能体能够与未知环境不断交互和学习,进而选择长期累积回报最大的信道接入。在学习过程中,本文引入了Boltzmann实验策略,运用模拟退火思想实现了资源探索与资源利用之间的折衷。仿真结果表明,所提算法能够在未知环境先验知识条件下可以快速选择性能较好的信道接入,有效提高认知用户的接入吞吐量和系统的平均容量。      

Throughput Maximization in Cognitive Radio System with Transmission Probability Scheduling and Traffic Pattern Prediction

In this paper, we propose a novel transmission probability scheduling (TPS) scheme for the opportunistic spectrum access based cognitive radio system (OSA-based CRS), in which the secondary user (SU) optimally schedules its transmission probabilities in the idle period of the primary user (PU), to maximize the throughput of the SU over a single channel when the collision probability perceived by the PU is constrained under a required threshold. Particularly, we first study the maximum achievable throughput of the SU when the proposed TPS scheme is employed under the assumption that the distribution of the PU idle period is known and the spectrum sensing is perfect. When the spectrum sensing at the SU is imperfect, we thoroughly quantify the impact of sensing errors on the SU performance with the proposed TPS scheme. Furthermore, in the situation that the traffic pattern of the PU and its parameters are unknown and the spectrum sensing is imperfect, we propose a predictor based on hidden Markov model (HMM) for the proposed TPS scheme to predict the future PU state. Extensive simulations are conducted and show that the proposed TPS scheme with the HMM-based predictor can achieve a reasonably high SU throughput under the PU collision probability constraint even when the sensing errors are severe.     

Modified 802.11‐Based Opportunistic Spectrum Access in Cognitive Radio Networks

In this letter, a modified 802.11‐based opportunistic spectrum access is proposed for single‐channel cognitive radio networks where primary users operate on a slot‐by‐slot basis. In our opportunistic spectrum access, control frames are used to reduce the slot‐boundary impact and achieve channel reservation to improve throughput of secondary users. An absorbing Markov chain model is used to analyze the throughput of secondary users. Simulation results show that the analysis accurately predicts the saturation throughput.     

Auction-Based Throughput Maximization in Cognitive Radio Networks Under Interference Constraint

Cognitive radio is an emerging technique to improve the utilization of radio frequency spectrum in wireless communication networks. That is, spectrum efficiency can be increased significantly by giving opportunistic access of the frequency bands to a group of cognitive users to whom the band has not been licensed. In this paper, as a cross layer application (MAC and physical layers) of graph theory, we consider the problem of throughput maximization of spectrum allocation in cognitive radio networks under interference constraint. We propose a novel auction-based channel allocation mechanism which tries to maximize both total and primary users’ utilities while satisfying signal to interference ratio constraint on primary receivers so that transmitted packets will be successfully received, without controlling secondary user powers. For comparison we discuss a greedy algorithm as well, however, one that does not handle interference issue. In order to compare results of proposed and greedy algorithms, we propose net throughput by taking into account outage probability of primary receiver. Simulation results show that exposing higher SINR (outage) threshold not only decreases total gain and primary users’ utilities but also worsens channel distribution performance. On the other hand adding auction mechanism significantly increases total gain throughput and primary user’ s utility. Particularly, up to SINR threshold values of 20 dBs, auction provides outstanding performance and proposed algorithm has total throughput results close to those of the greedy one even though no interference constraint is applied in the greedy algorithm. Another noticeable point of simulation results is crossover of net throughputs of proposed and greedy algorithms at a SINR threshold level after which results of ABSA-UNIC and NASA-UNIC are much better. This clearly shows superiority of proposed mechanism.