An improved cooperative spectrum sensing of femtocells with hybrid TDD access scheme in massive MIMO system

To improve the sensing performance and achieve higher throughput of the femtocells (FCs) while alleviating the influence to the macrocell in the cognitive massive multiple‐input and multiple‐output system (MIMO), we propose in this paper a hybrid time‐division duplex (TDD) access scheme of the FCs with confidence factor–based weighted cooperative spectrum sensing (CSS). A first, we present an efficient hybrid TDD access scheme for better spectrum reuse of the FCs based on the typical TDD and reversed TDD schemes. Furthermore, confidence factor–based weighted CSS has been used for better spectrum sensing and interference alleviation. In the cognitive massive MIMO system, FC base stations will form dynamical clustering based on the channel conditions, sense the spectrum through cooperative scheme, and decide whether to access the spectrum or not. After information exchange within each FC cluster, the FC base stations can obtain and update their confidence factors and weight factors based on the sensing results and reliability. Numerical results and theoretical analysis show that the proposed scheme can get more accurate sensing results, increase the throughput and the spectrum access opportunity of the FCs, and efficiently alleviate the interference to the macrocell tier.     

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.     

Cyclostationarity-Based Decision Reporting Scheme for Cooperative Spectrum Sensing

Cooperative spectrum sensing has emerged as a promising solution to the hidden terminal problem in cognitive radio networks (CRNs). It could significantly promote the sensing capability of CRNs by exploiting space diversity gains in a fading environment. However, owing to the decision reporting overhead, there exists a tradeoff between the system throughput and performance of cooperative spectrum sensing. In this paper, we propose a cyclostationarity-based decision reporting scheme for cooperative spectrum sensing in CRNs with cyclic delay diversity orthogonal frequency division multiplexing (CDD-OFDM). Decision information would be embedded into the CDD-OFDM signals in terms of cyclostationary signatures and shared among cognitive radio (CR) users along with data transmissions. As a result, satisfied system throughput could be achieved without additional spectral or temporal resources consumption when the number of cooperative users increases. Numerical results are presented to show the system throughput enhancement.     

Optimization algorithm of periodical cooperative spectrum sensing in cognitive radio

To decrease the interference to the primary user (PU) and improve the detected performance of cognitive radio (CR), a single‐band sensing scheme wherein the CR periodically senses the PU by cooperative spectrum sensing is proposed in this paper. In this scheme, CR first senses and then transmits during each period, and after the presence of the PU is detected, CR has to vacate to search another idle channel. The joint optimization algorithm based on the double optimization is proposed to optimize the periodical cooperative spectrum sensing scheme. The maximal throughput and minimal search time can be respectively obtained through the joint optimization of the local sensing time and the number of the cooperative CRs. We also extend this scheme to the periodical wideband cooperative spectrum sensing, and the joint optimization algorithm of the numbers of the sensing time slots and cooperative CRs is also proposed to obtain the maximal throughput of CR. The simulation shows that the proposed algorithm has lower computational quantity, and compared with the previous algorithms, when SNR = 5 dB, the throughput and search time of the proposed algorithm can respectively improve 0.3 kB and decrease 0.4 s. The simulation also indicates that the wideband cooperative spectrum sensing can achieve higher throughput than the single‐band cooperative spectrum sensing. Copyright © 2012 John Wiley & Sons, Ltd.     

典型部署策略下认知无线传感网的机会频谱接入方法

在典型规则拓扑模式及覆盖部署方式的传感网中探讨无冲突的认知频谱接入方法（包括频谱和时隙分配、协作频谱感知和感知结果汇报方案）,为数据采集提供高效的传输手段。提出对应网络环境下的次级用户的阻塞率和掉话率、各拓扑模式下的网络有效接收带宽和最大传输时延的分析模型。通过对几种拓扑模式的比较,表明Triangle的协作频谱感知效果最佳,而Square的有效接收带宽最佳;在完全覆盖部署方式下,Square和Triangle的传输时延较小,而多重覆盖部署方式下Square的时延最小。指出单个节点上的虚警概率对传输时延的影响不大,授权用户出现概率则对时延有明显影响,而选择较大的传输时隙/感知时隙比能显著降低时延。     

Probability-based combination for cooperative spectrum sensing

This letter proposes a probability-based scheme for combination of spectrum sensing information collected from cooperative cognitive radio users. The proposed scheme enables combination of both synchronous and asynchronous sensing information by utilizing the statistics of licensed band occupancy and is superior to conventional schemes in terms of detection performance.     

Sensor node-assisted asynchronous cooperative spectrum sensing for cognitive radio network

In order to take advantage of the asynchronous sensing information, alleviate the sensing overhead of secondary users （SUs） and improve the detection performance, a sensor node-assisted asynchronous cooperative spectrum sensing （SN-ACSS） scheme for cognitive radio （CR） network （CRN） was proposed. In SN-ACSS, each SU is surrounded by sensor nodes （SNs）, which asynchronously make hard decisions and soft decisions based on the Bayesian fusion rule instead of the SU. The SU combines these soft decisions and makes the local soft decision. Finally, the fusion center （FC） fuses the local soft decisions transmitted from SUs with different weight coefficients to attain the final soft decision. Besides, the impact of the statistics of licensed band occupancy on detection performance and the fact that different SNs have different sensing contributions are also considered in SN-ACSS scheme. Numerical results show that compared with the conventional synchronous cooperative spectrum sensing （SCSS） and the existing ACSS schemes, SN-ACSS algorithm achieves a better detection performance and lower cost with the same number of SNs.     

A new sensing‐throughput tradeoff scheme in cooperative multiband cognitive radio network

A conventional cognitive radio network (CRN) uses the spectrum of the licensed primary network (PN) on the premise of detecting the absence of the PN by the spectrum sensing of the sensor node (SN). In this paper, a cooperative multiband CRN is considered, wherein the SNs are allowed to use some time of the transmission slot to relay PN data by cooperative communication, while using the remaining time of the transmission slot to forward its own data, over multiple sub‐bands during each frame, if the presence of PN is detected by cooperative spectrum sensing of the SNs in the sensing slot. A new sensing–throughput tradeoff scheme is formulated as a multi‐variable optimization problem, which maximizes the average aggregate throughput of the CRN over all the sub‐bands by jointly optimizing spectrum sensing time and sub‐band transmission power, subject to the constraints on the average aggregate throughput of the PN, the maximal aggregate power of each SN, and the false alarm and detection probabilities of each sub‐band. The bi‐level optimization method is adopted to obtain the optimal solution by dividing the multi‐variable optimization problem into two convex single‐variable sub‐optimization problems. The simulations show that there exists the optimal sensing time and sub‐band transmission power that maximize the average aggregate throughput of the CRN and, compared with the conventional scheme, the throughput obtained by the proposed scheme is outstanding. Copyright © 2014 John Wiley & Sons, Ltd.     

Delay QoS Guaranteed Cooperative Double-Threshold Sensing Scheme in Cognitive Radio Networks

In cognitive radio networks, cooperation can greatly improve the performance of spectrum sensing. This paper proposes a delay (QoS) quality-of-service guaranteed cooperative spectrum sensing frame structure in which secondary users (SUs) conduct spectrum sensing and data transmission concurrently over two different parts of the primary user spectrum band. A double-threshold sensing scheme is employed in the local sensing step, only the SUs with reliable sensing information are allowed to transmit their “one bit” local decisions to the fusion center. The sensing performance and the SU transmission delay are analyzed in detail in this paper. Computer simulations show that the delay QoS guaranteed cooperative double-threshold sensing scheme could not only decrease the SU transmission delay but also save the reporting overhead of the SUs compared with the conventional detection method with one threshold.     

Adaptively Controlled Cooperative Spectrum Sensing Using OR Fusion Rule for Throughput Maximization in Cognitive Radio

Utilization of wireless spectrum resources should be improved with the great increase of using wireless services. Cognitive radio (CR) has been proposed to overcome the problem of inefficient use of spectrum holes. Spectrum sensing is the most important functional block, which is used to estimate the spectrum holes in the CR system. Cooperative spectrum sensing improves the detection performance and minimizes miss-detection of the primary user. The objective of this paper is to achieve the maximum throughput for all values signal-to-noise ratio (SNR). Cooperative spectrum sensing with fixed sensing time does not provide efficient throughput performance for all values of SNR. In this paper, we propose an adaptively controlled cooperative spectrum sensing scheme using OR fusion rule for throughput maximization in CR system. The proposed scheme estimates the required optimal sensing time for each value of the SNR to achieve the maximum throughput. Simulation results of the proposed scheme demonstrate that it maximizes the achieved throughput for all values of SNR and minimizes the probability of false alarm.

     

Reliable relay assisted wireless multicast using network coding

We first consider a topology consisting of one source, two destinations and one relay. For such a topology, it is shown that a network coding based cooperative (NCBC) multicast scheme can achieve a diversity order of two. In this paper, we discuss and analyze NCBC in a systematic way as well as compare its performance with two other multicast protocols. The throughput, delay and queue length for each protocol are evaluated. In addition, we present an optimal scheme to maximize throughput subject to delay and queue length constraints. Numerical results will demonstrate that network coding can bring significant gains in terms of throughput.     

Performance analysis of rate-adaptive cooperative MAC based on wireless local area networks

Bi-dimensional Markov chain model based on cooperative medium access control (MAC) of wireless local area networks (WLAN) is considered to reflect system performance accurately. Two basic factors that affect the analysis results are station retry limits and non-saturated transmit probability. A uniform solution considering both factors is proposed. To prove the theoretical analysis, a cooperative MAC (CoopMAC) topology is established and the simulation model is enhanced by changing the cooperative table to the nodes' memory with more information added. Meanwhile, the three-way handshake scheme is modified and a handshake threshold is set based on the packet size. Simulation results show the performance analytical model is accurate, and the rate-adaptive cooperative MAC protocol significantly improves the network performance in terms of non-saturated system throughput and delay.     

模拟人群信任和决策机制的协作频谱感知方法

通过模拟人群内部的信任和决策机制,针对多用户的频谱协作感知一致性问题,提出了一种分布式算法。该算法首先通过网络的历次协作过程预测出各感知用户的动态可信值,据此产生用户的相对可信值,并结合决策机制使得用户之间进行数据交互,随着数据的可信、迭代交互,所有用户状态将趋于一致,最后通过判定算法得出最终结果。算法充分考虑了实际环境中各用户频带感知能力的不平衡性,而且各次级用户只需要进行少量局部数据交换即可实现协作感知,与传统的OR-rule、1-out-of-N rule以及普通迭代法有较大区别。对3种数据篡改攻击进行了分析,并在预测算法的基础上提出了相应的安全策略。理论分析与仿真结果表明,新算法在准确性和安全性上均优于传统合作频谱感知算法,能显著提高频谱感知准确率,同时兼具较强的防攻击能力。     

Enhancing the spectral efficiency and energy efficiency of underwater channel communication by optimal cooperative spectrum sensing using hybrid optimization

Underwater wireless sensor networks (UWSNs) contain quite a lot of components such as vehicles and sensors that are deployed in a specific acoustic area to perform collaborative monitoring and data collection errands. These networks are adopted interactively between diverse nodes and ground‐based stations. Currently, UWSNs face problems and challenges that pertain to limited bandwidth, media access control, high propagation delay, 3D topology, spectrum sensing, resource utilization, routing, and power constraints. This proposal deals with the intelligent spectrum sensing in underwater cognitive sonar communication networks (CSCN). Here, the improved performance of spectrum sensing in underwater communication is attained by optimizing the cooperative spectrum sensing and data transmission. The parameters of system like subchannel allocation and transmission power is optimized by a new hybrid meta‐heuristic algorithm by integrating the concepts of deer hunting optimization algorithm (DHOA) and lion algorithm (LA) termed as lion‐enabled DHOA (L‐DHOA). The main intention of optimizing these parameters is to maximize the spectrum efficiency (SE) and energy efficiency (EE) of the underwater channel communication system. From the analysis, with respect to convergence rate, minimum detection probability, and local sensing time, it is proved that the novel hybrid optimization algorithm keeps a great role in making the trade‐off between the SE and EE in underwater channel modeling.     

On Detecting Spectrum Opportunities for Cognitive Vehicular Networks in the TV White Space

We overview the challenges related to spectrum awareness in the vehicular environment, with emphasis on awareness in the TV licensed band. In the vehicular environment the cognitive radio can help to: 1) satisfy capacity demand for Intelligent Transportation Systems (ITS) applications; and 2) offload time insensitive applications from the ITS dedicated spectrum. However, using simple propagation models we show that neither sensing, nor geolocation database lookup alone can provide sufficient incumbent protection. Collaboration among the sensors to take advantage of spatial diversity is difficult due to the rapidly changing network topology. Nevertheless, mobility provides the opportunity to use time diversity at each sensor. We also discuss the influence of sensing subsystem design on the vehicular cognitive network medium access (MAC) sublayer. Whenever appropriate, we evaluate applicability of the requirements imposed by the Federal Communications Commission (FCC) and the IEEE 802.22 standard to the cognitive vehicular networks.     

采用最小最大准则的协作频谱感知融合

给出了采用最小最大准则实现认知无线电系统协作频谱感知融合的方法,以在主用户出现在授权频段的先验概率未知的情况下利用概率计算实现认知无线电系统的协作频谱感知融合。该方法可实现同步和异步感知信息的融合。仿真验证了算法的性能,并与采用估计主用户出现在授权频段的先验概率并进行基于概率的感知融合算法性能进行了比较。结果表明:给出的算法可有效实现主用户出现在授权频段的先验概率未知时的协作频谱感知融合。     

优化的最佳中继协作频谱感知

在基于中继的协作频谱感知中,尽管通过引入认知中继可有效提高协作频谱感知性能,然而认知中继的引入也会带来额外的系统开销及复杂度增加问题。为了节约系统开销,本文在前期取得研究成果的基础上,进一步提出了一种基于删余的最佳中继协作频谱感知方案,只有当次用户检测到主用户信号且目标次用户的报告信道衰落严重时,才申请认知中继的协作传输,同时目标次用户将其检测到的感知信息发送到认知中继;最后,分别从检测性能和次系统可获得的容量角度对所提方案下的协作频谱感知性能进行了理论分析。分析和仿真结果表明,所提方案可以有效提高检测性能,当确保主用户受到足够保护的前提下,利用所提方案可以获得更高的次系统容量。      

Mobility impact in IEEE 802.11p infrastructureless vehicular networks

Vehicular ad hoc networks (VANETs) are an extreme case of mobile ad hoc networks (MANETs). High speed and frequent network topology changes are the main characteristics of vehicular networks. These characteristics lead to special issues and challenges in the network design, especially at the medium access control (MAC) layer. In this paper, we provide a comprehensive evaluation of mobility impact on the IEEE 802.11p MAC performance. The study evaluates basic performance metrics such as packet delivery ratio, throughput, and delay. An unfairness problem due to the relative speed is identified for both broadcast and unicast scenarios. We propose two dynamic contention window mechanisms to alleviate network performance degradation due to high mobility. The first scheme provides dynamic level of service priority via adaptation to the number of neighboring nodes, while the second scheme provides service priority based on node relative speed. Extensive simulation results demonstrate a significant impact of mobility on the IEEE 802.11p MAC performance, the unfairness problem in the vehicle-to-vehicle (V2V) communications, and the effectiveness of the proposed MAC schemes.     

基于随机学习的接入网服务功能链部署算法

针对5G云化接入网场景下物理网络拓扑变化引起的高时延问题,读文提出一种基于部分观察马尔可夫决策过程(POMDP)部分感知拓扑的接入网服务功能链(SFC)部署方案。该方案考虑在5G接入网C-RAN架构下,通过心跳包观测机制感知底层物理网络拓扑变化,由于存在观测误差无法获得全部真实的拓扑情况,因此采用基于POMDP的部分感知和随机学习而自适应动态调整接入网切片的SFC的部署,优化SFC在接入网侧的时延。为了解决维度灾问题,采用基于点的混合启发式值迭代算法求解。仿真结果表明,该模型可以优化部署接入网侧的SFC,并提高接入网吞吐量和资源利用率。     

异步区块链支持的安全频谱共享

针对目前频谱稀缺的困境,一个经济有效的解决方案是将未充分利用的授权频谱以机会的方式分配给未授权用户。然而,实现大规模频谱共享面临激励缺失、隐私泄露、安全威胁和时延过大等挑战。利用区块联盟链技术的安全机制,设计了由频谱接入层、区块链网络层、区块链共识层构成的区块链动态频谱接入系统。该系统采用异步实时拜占庭容错(Practical Byzantine Fault Tolerance,PBFT)改善共识延时,设计基于最优匹配算法的匹配方案,提高频谱复用率。经仿真验证,该方案频谱复用率提升近6%。相比于实时拜占庭机制,所提方案减少了系统延时,提升吞吐量近129%。