认知无线电中基于状态转移概率的感知时隙优化算法

为了在感知性能与系统传输效率之间对感知时隙长度进行有效折衷,在对授权信道当前分别为"占用"和"空闲"状态时的感知时隙长度与状态转移概率之间的关系进行分析的基础上,提出了一种基于授权信道状态转移概率预测的感知时隙长度优化算法。该算法能够保证在感知过程中始终用最小的感知时隙长度来满足系统对感知性能的最低要求,以最大化认知系统的能量效率与传输效率。     

感知不确定下卫星认知无线网络多频谱接入优化策略

针对卫星认知无线网络频谱感知不确定性较大导致传统频谱接入机制效率降低的问题,该文提出一种基于动态多频谱感知的信道接入优化策略。认知LEO卫星根据频谱检测概率与授权用户干扰门限之间的关系,实时调整不同频谱感知结果下的信道接入概率。在此基础上以系统吞吐量最大化为目标,设计了一种基于频谱检测概率和虚警概率联合优化的判决门限选取策略,并推导了最佳感知频谱数量。仿真结果表明,认知用户能够在不大于授权用户最大干扰门限的前提下,根据授权信道空闲状态动态选择最佳频谱感知策略,且在检测信号信噪比较低时以更加积极的方式接入授权频谱,降低了频谱感知不确定性对信道接入效率的影响,提高了认知系统吞吐量。     

VANET中利用空闲TDMA时隙协助发送数据的方法

车载自组网中的分布式TDMA方法没有利用节点的空闲TDMA时隙,未能充分利用无线信道资源,基于此,提出了一种利用空闲TDMA时隙的MAC层数据重发方法,当节点发送数据失败时,附近节点利用空闲的TDMA时隙重新发送传输失败的数据。理论分析和仿真结果表明,所提方法显著提高了分布式TDMA方法的数据发送成功概率和网络吞吐量。此外,通过仿真比较所提方法与IEEE802.11p的性能,结果表明,由于以确定的方式访问信道,所提方法能够及时稳定地传输车载自组网中的实时安全信息。     

动态时隙控制的双概率随机多址接入ad hoc网络MAC协议分析

提出了一种动态时隙控制的双概率随机多址接入MAC(DSTPMA)协议,用户终端以P1概率侦测空闲信道,以P2概率检测忙信道,并在发送状态调整时隙定位后接入信道发送信息分组.通过对多通道的DSTPMA协议的建模分析,得到了控制协议的系统吞吐量.仿真实验结果表明,理论分析与仿真结果相一致.     

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。     

基于能量收集驱动和信道感知的CRN

针对能量采集器供电的认知无线电网络进行了研究。首先,在采用离散时间马尔可夫链的建模基础上,通过分析认知用户在收集到的能量包和电池容量的限制下有效地利用能量,以最大化当前时隙的吞吐量。然后,找到多个信道的最优感知顺序和对应于该感知顺序下信道的最优传输能量集,得到使认知无线电网络在多个时隙的预期吞吐量最大化的递归表达式。最后提出了一种基于该递归表达式实现最大化预期吞吐量的算法。仿真实验结果表明,所提出的方案相比于其他方案,不仅提高了认知无线电网络的吞吐量,而且降低了主信道上的平均碰撞比。     

多信道合作感知中基于信道可用概率的感知信道集合选择算法

首先分析了在给定感知信道集合和相应的可用概率集合条件下认知无线网络最大吞吐量的求解算法,接着给出了授权信道可用概率的估计方法,并在此基础上提出了一种基于授权信道可用概率估计的感知信道集合的次优选择算法。从分析结果与仿真结果可知,该次优选择算法与最优选择算法的性能差别不大,但是复杂度却大大降低了,另外该算法与已有算法相比可以得到更高的系统吞吐量。     

802.11无线网状网中基于时频信道的准动态信道分配算法

该文首次在多天线多信道802.11无线网状网中提出了时频信道的概念。时频信道是通过在时间和频率两个维度划分无线资源取得的。这种划分方法增加了信道数量,使信道划分更加精细,为提高系统的信道利用率做了准备。在时频信道的基础上,提出了准动态信道分配算法。该算法可以和现有的固定信道分配算法结合,实现准动态信道分配,根据链路上负载变化,取得最大的吞吐量。该算法先根据固定信道分配算法为各链路分配相同数量的时频信道,剩余部分当作公共信道。在通信过程中,各链路首先使用分配给自己的信道和空闲的公共信道。如果分配给一个链路的信道不够,且别的链路上的信道有空闲,该链路还可以暂时使用这些空闲信道。理论分析和仿真结果证明该算法可以有效提高系统的吞吐量。     

认知无线电网络中次用户平均吞吐量的优化

协作频谱感知的认知无线电网络中,已有研究表明增加参与协作频谱感知的次用户数量能够提高感知性能,进而提高信道吞吐量。然而,由于信道容量的限制,不断增加参与协作感知的次用户数量并不会使信道吞吐量无限提高,反而会使次用户平均可获得的吞吐量不断降低。针对上述问题,该文以次用户平均吞吐量为优化目标,证明多信道条件下,对于任意给定的融合参数,次用户的平均吞吐量是感知时间的凸函数,并提出交叉迭代算法进行2维优化。仿真结果表明,当信噪比为-10 dB时,次用户使用交叉迭代算法获得的平均吞吐量较已有算法可提高20%以上。     

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。     

Optimization of sensing time in multichannel sequential sensing for cognitive radio

This paper studies the design of sensing time in multichannel sequential sensing for cognitive radio under the multichannel sensing slots and one transmission slot scheme. Firstly, we consider the case where the channel idle probability is known. In this case, when the channels’ signal‐to‐noise ratios (SNRs) are equal, we prove that there exist optimal sensing times that maximize the achievable throughput for secondary user, while primary user is sufficiently protected. When the channels’ SNRs are different, brute‐force search is used to find the optimal sensing order that maximizes the achievable throughput of secondary user, and the corresponding optimal sensing times will be obtained. Then, a suboptimal and low‐complexity approach of one‐slot sensing time without knowing the channel idle probability is proposed. The proposed approach solves the problem of sensing order by selecting the channel with the minimum sensing time in the next sensing slot when the channels’ SNRs are different. Numerical results show that the proposed approach achieves a performance close to that of the optimal sensing time under different conditions and has significant performance improvement over the approach of fixed sensing time. Copyright © 2011 John Wiley & Sons, Ltd.     

An Assigned-Slot Listen-Before-Transmission Protocol for a Multiaccess Data Channel

In the multiaccess protocol described in this paper, users are each assigned specific slots of time in which to listen to the channel and determine if the channel is busy or idle. If the channel is idle, a ready user may transmit a fixed length message, or packet; otherwise he must wait a random time and try again. When two or more users transmit simultaneously, none are successful and each must retry after a random time. Though we have considered random slot assignment in general, in this paper we treat only fixed assignment. An interesting special case is when only one user is assigned to each sensing slot. Then there can be no collision and none of the channel capacity is wasted on retransmissions; that is, the channel is conflictfree. Delay-throughput performance curves are presented and compared with some other current multiaccess schemes of interest. Stability considerations are also discussed.     

A joint sensing and transmission power control policy for RF energy harvesting cognitive radio networks

We consider a radio frequency energy harvesting cognitive radio network in which a secondary user (SU) can opportunistically access channel to transmit packets or harvest radio frequency energy when the channel is idle or occupied by a primary user. The channel occupancy state and the channel fading state are both modeled as finite state Markov chains. At the beginning of each time slot, the SU should determine whether to harvest energy for future use or sense the primary channel to acquire the current channel occupancy state. It then needs to select an appropriate transmission power to execute the packet transmission or harvest energy if the channel is detected to be idle or busy, respectively. This sequential decision‐making, done to maximize the SU's expected throughput, requires to design a joint spectrum sensing and transmission power control policy based on the amount of stored energy, the retransmission index, and the belief on the channel state. We formulate this as a partially observable Markov decision process and use a computationally tractable point‐based value iteration algorithm. Section 5 illustrate the significant outperformance of the proposed optimal policy compared with the optimal fixed‐power policy and the greedy fixed‐power policy.     

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。     

Determination of the multi‐slot transmission in Bluetooth systems with the estimation of the channel error probability

Bluetooth is an open specification for a technology to enable short‐range wireless communications that operate in an ad hoc fashion. Bluetooth uses frequency hopping with a slot length of 625 μs. Each slot corresponds to a packet and multi‐slot packets of three or five slots can be transmitted to enhance the transmission efficiency. However, the use of multi‐slot packet may degrade the transmission performance under high channel error probability. Thus, the length of multi‐slot should be adjusted according to the current channel condition. Segmentation and reassembly (SAR) operation of Bluetooth enables the adjustment of the length of multi‐slot. In this paper, we propose an efficient multi‐slot transmission scheme that adaptively determines the optimal length of slots of a packet according to the channel error probability. We first discuss the throughput of a Bluetooth connection as a function of the length of a multi‐slot and the channel error probability. A decision criteria which gives the optimal length of the multi‐slot is presented under the assumption that the channel error probability is known. For the implementation in the real Bluetooth system, the channel error probability is estimated with the maximum likelihood estimator (MLE). A simple decision rule for the optimal multi‐slot length is developed to maximize the throughput. Simulation experiment shows that the proposed decision rule for the multi‐slot transmission effectively provides the maximum throughput under any type of channel error correlation. Copyright © 2005 John Wiley & Sons, Ltd.     

最优认知用户配对与协作感知算法研究

针对协作算法频谱感知和时隙消耗方面的不足,提出一种最优用户配对与协作感知算法。采用接收信噪比最优的认知用户为感知用户且以接收信噪比次优的认知用户为其中继的配对准则,获得最佳频谱感知性能。通过优化设置协作门限,选择性地采用非协作或协作模式,获得更低的时隙消耗。同时,推导了在瑞利平坦衰落环境下该算法的频谱检测概率下界与时隙消耗。数值计算结果表明,与原有算法相比,该算法不仅检测概率更高且时隙消耗更低。     

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.     

Enhancing the Spectrum Sensing Performance of Cluster-Based Cooperative Cognitive Radio Networks via Sequential Multiple Reporting Channels

In cluster-based cooperative cognitive radio networks (CCRNs), spectrum sensing and decision making processes to determine whether the primary user (PU) signal is present or absent in the network are very important and vital issues to the utilisation of the idle spectrum. The reporting time delay is a very important matter to make quick and effective global decisions for the fusion center (FC) in a cluster-based CCRNs. In this paper, we propose the concept of multiple reporting channels (MRC) for cluster-based CCRNs to better utilize the reporting time slot by extending the sensing time of secondary users (SUs). A multiple reporting channels concept is proposed based on frequency division multiple access to enhance the spectrum sensing performance and reduce the reporting time delay of all cluster heads (CHs). In this approach, we assign an individual reporting channel to each cluster for reporting purposes. All the SUs in each cluster sequentially pass their sensing results to the corresponding cluster head (CH) via the assigned single reporting channel, which extends the sensing time duration of SUs. Each CH uses the dedicated reporting channel to forward the cluster decision to the FC that makes a final decision by using the “K-out-of-N” rule to identify the presence of the PU signal. This approach significantly enhances the sensing time for all SUs than the non-sequential as well as minimize the reporting time delay of all CHs than sequential single channel reporting approach. These two features of our proposed approach increase the decision accuracy of the FC more than the conventional approach. Simulation results prove that our proposed approach significantly enhances the sensing accuracy and mitigate the reporting time delay of CH compared to the conventional approach.