Maritime cognitive radio spectrum sensing based on multi-antenna cyclostationary feature detection

ABSTRACT

With the development of the maritime transportation industry, the number of ships is increasing and the ships are becoming more intelligent. Due to the rapid development of maritime communication, the demand for communication spectrum is increasing. Therefore, the maritime cognitive radio (CR) system is an effective solution. Because of the multipath fading caused by sea surface and atmosphere has a more serious influence on communication signals, which increases the instability of the signal reception, the spectrum sensing technology in maritime cognitive radio is more challenging than the spectrum sensing on land. In order to solve this problem, a cyclostationary detection algorithm for multiple antennas in fading model is proposed. A maximum ratio combining algorithm based on optimal weight correlation value (OWCV-MRC) is proposed for the diversity gain and system performance degradation caused by diversity technology on multipath fading channels. The algorithm uses the correlation values of the attenuation gains on the two different branches as the weighting coefficients of each branch, thus improving the coefficient matrix in the maximum ratio combining (MRC) algorithm. The simulation results show that the proposed algorithm can effectively detect the target signal in the fading channel with ultra-low signal to noise ratio (SNR).     

Asymptotically maximum likelihood detection for subcarrier mapping‐induced cyclostationary signatures in cognitive radio networks

In cognitive radio networks based on orthogonal frequency division multiplexing, the subcarrier mapping‐induced cyclostationary signatures are utilized for robust network coordination. However, the effect of network coordination depends on the reliable detection of such cyclostationary signatures. Moreover, doubly selective fading increases the difficulty of reliable detection. In this paper, we first derive an exact covariance matrix to characterize the statistics of the cyclostationary signatures induced by subcarrier mapping. Using the exact covariance matrix rather than its estimation adopted in conventional algorithms, we propose an asymptotically maximum likelihood detection algorithm. The detection performance of the proposed asymptotically maximum likelihood detection algorithm is analyzed and evaluated both in flat fading and doubly selective fading channels. Simulation results show that the proposed algorithm outperforms the conventional low‐complexity single‐cycle signature detection algorithm in terms of less observation period or smaller mapping set size. Copyright © 2011 John Wiley & Sons, Ltd.     

Distributed joint spectrum detection and power allocation in multi-band cognitive radio networks

This article proposes a novel dynamic spectrum sharing scheme in distributed multi-band cognitive radio networks. A non-cooperative game has been utilized to model the spectrum sharing among secondary base stations (SBSs). A distributed joint spectrum detection and power allocation algorithm is designed for maximizing the downlink throughput of secondary networks. Simulation results demonstrate that the proposed algorithm converges fast and achieves a better throughput performance than uniform threshold case. Meanwhile, the convergence of algorithm is proved by Nikaido-Isoda (N-I) function method.     

Cyclostationary signature design for common control channel of cognitive radio

Embedding specific signatures in transmitted signals for identifying common control channels of cognitive radio are addressed in research laboratories because availability of the spectrum occupied by the common control channel might change in time. A novel solution to embed a unique cyclostationary signature for the common control channel of cognitive radio is proposed in this article. Based on linear periodically time-variant transformation (LPTV) model, the cyclic autocorrelation expression of the proposed signature is derived, which characterizes its cyclostationarity. Analysis of the cyclostationary signature is presented considering effects of additive white Gaussian noise(AWGN)and multiplath channels. Simulation results illustrating the reliability of signatures are given.     

Cooperative automatic modulation recognition in cognitive radio

In this article, a new effective method of cooperative modulation recognition (CMR) is proposed to recognize different modulation types of primary user for cognitive radio receivers. In the cognitive radio (CR) system, two CR users respectively send their feature parameters to the cooperative recognition center, which is composed of back propagation neural network (BPNN). With two users' cooperation and the application of an error back propagation learning algorithm with momentum, the center improves the performance of modulation recognition, especially when one of the CR users' signal-to-noise ratio (SNR) is low. To measure the performance of the proposed method, simulations are carried out to classify different types of modulated signals corrupted by additive white Gaussian noise (AWGN). The simulation results show that this cooperation algorithm has a better recognition performance than those without cooperation.     

Jointly optimizing sensing time and resource allocation in multichannel cognitive radio networks

Spectrum sensing is a key technique for determining the spectrum available in cognitive radio (CR) networks. In this paper, we study how to jointly optimize sensing time and resource allocation to maximize the sum transmission rate of all CR users of a multichannel CR network. We take into consideration the transmission power and interference constraints to protect primary users from harmful interference, as well as constraints of detection probability and false alarm probability. Under these constraints, we propose an asymptotically optimal resource allocation algorithm. The optimal sensing time can be obtained using the traditional one‐dimensional exhaustive search. However, owing to the high complexity of searching for the sensing time, we propose a simplified method to get the optimal sensing time under the assumption that false alarm probability is small. Simulation results show that the simplified method can obtain the optimal sensing time efficiently under strict constraint of false alarm probability. Copyright © 2012 John Wiley & Sons, Ltd.     

基于循环谱能量的自适应频谱检测算法

根据信号循环平稳谱的特征,研究在低信噪比环境下的频谱检测问题,提出一种基于循环谱能量的自适应判决门限频谱检测算法。该算法融合能量检测与循环平稳特征检测的机理,以信号的循环谱能量为检测统计量,加权合并虚警率与检测率,准确估计循环谱特征值,构建了具有噪声自适应能力的频谱检测判决门限。仿真结果表明,该算法可以在低信噪比环境下有效地完成频谱检测,克服了噪声波动对频谱检测性能的影响,对不同调制主信号的感知具有稳健性。与最大—最小特征值算法和盲检测算法相比,该算法分别改善了信噪比4dB和8dB。     

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.     

Performance optimisation of RF energy harvesting relay-based interweave/underlay cognitive radio network

This paper investigates the performance of energy harvesting (EH) relay-based interweave/underlay cognitive radio network. The relay employs amplify and forward (AF) technique along with time-switching relaying protocol (TSR) for EH. Based on sensing accuracy, we derive an expression for optimisation of charging duration TSR parameter and sensing duration for maximising throughput of interweave cognitive radio (CR). Based on sensing efficiency, throughput and outage probability for underlay CR is analysed considering the interference temperature constraints and optimal power distribution parameter at secondary user (SU) terminals. Variations in the sum-rate and detection probability are considered in terms of cumulative distribution functions (CDF) of the terminal Signal to Noise Ratios (SNRs). We prove that erogodic sum-rate is maximised in underlay CR case, when interference power distribution parameter is half across the SU terminals. The optimised values of switching-time ratios have been derived analytically for both interweave and underlay CR. The results thus obtained are compared by taking symmetrical and asymmetric channels between SU terminals. Analytical results are validated through Monte-Carlo simulations to confirm the accuracy of the derived expressions.     

最优线性认知无线电协作频谱感知技术研究

频谱感知是检测频谱空穴,实现动态频谱接入的前提和关键。单认知用户检测存在阴影效应和多径衰落等影响,检测效果较差。多用户协作频谱感知是目前频谱感知的主要手段。文中针对常用的协作频谱感知方法的不足,提出一种基于最优线性加权的协作频谱感知方法,对其检测模型与检测算法进行分析,并进行仿真。仿真结果表明,最优线性加权协作频谱感知在相同的条件下相比常用协作频谱感知具有更大的检测概率,更优良的检测性能。     

认知无线电中基于感知信息量化的合作频谱感知

针对认知无线电频谱感知性能的提高与传输开销的矛盾,本文提出了一种基于感知信息量化的合作频谱感知方案。该方法对各认知用户的本地检测结果采用3个判决门限进行2比特位的量化,在融合中心处对量化信息加权处理后,得到最终主用户是否存在的判决。本文详细研究了采用该方案的检测概率,虚警概率和吞吐量,理论分析和仿真结果表明,该方法在每个认知用户只增加1bit传输开销的前提下能够极大的改善检测性能,实现了检测性能与传输开销的较好权衡。     

基于认知无线电的频谱检测技术研究

信息时代无线通信飞速发展,许多需要较宽频谱和较高下载速率的业务,如多媒体通信业务,已经成为无线服务的重点对象。认知无线电是一种智能的无线通信技术,可以通过感知周围环境来自动调整其发射机参数,其核心思想是利用已分配但未获得充分利用的频谱,从而提高频谱利用率避免对主用户造成干扰是认知无线电最需要解决的问题,频谱感知则是实现这一目标的前提。     

Sensing OFDM systems with timing and frequency offset for cognitive radio networks

In this paper, we consider the detection of orthogonal frequency division multiplexing with timing and frequency offset for cognitive radio over fast time‐varying multipath channels. By making different assumptions on the availability of the timing and frequency offset at the secondary user, we derive two algorithms based on likelihood ratio test and generalized likelihood ratio test, respectively and theoretically obtain the detection performances of them. The proposed algorithms jointly utilize energy of observations and correlation of the cyclic prefix (CP) data. The extensive simulations show that the two algorithms outperform the other CP‐based methods, perform well at very low signal to noise ratio (SNR) and are robust to the CP ratio. Copyright © 2012 John Wiley & Sons, Ltd.     

Wireless distributed computing for cyclostationary feature detection

Recently, wireless distributed computing (WDC) concept has emerged promising manifolds improvements to current wireless technologies. Despite the various expected benefits of this concept, significant drawbacks were addressed in the open literature. One of WDC key challenges is the impact of wireless channel quality on the load of distributed computations. Therefore, this research investigates the wireless channel impact on WDC performance when the latter is applied to spectrum sensing in cognitive radio (CR) technology. However, a trade-off is found between accuracy and computational complexity in spectrum sensing approaches. Increasing these approaches accuracy is accompanied by an increase in computational complexity. This results in greater power consumption and processing time. A novel WDC scheme for cyclostationary feature detection spectrum sensing approach is proposed in this paper and thoroughly investigated. The benefits of the proposed scheme are firstly presented. Then, the impact of the wireless channel of the proposed scheme is addressed considering two scenarios. In the first scenario, workload matrices are distributed over the wireless channel. Then, a fusion center combines these matrices in order to make a decision. Meanwhile, in the second scenario, local decisions are made by CRs, then, only a binary flag is sent to the fusion center.     

Variable length signal detection framework for cognitive radio systems

The cognitive radio (CR) system opportunistically utilizes the frequency bands temporally unoccupied by the primary user. In the CR system, the energy or cyclostationary detector is used to detect the primary user signal. For protecting the primary user tightly, the signal detection time can be very long, which leads to inefficiency in the CR system. Thus, we propose a novel signal detector that greatly reduces the average detection time. The proposed detector periodically decides whether it terminates the detection process or receives more input signal for more information. Therefore, the proposed detector has variable detection time. We will call the proposed detector the variable length signal detector (VLSD). The VLSD is designed by using a partially observable Markov decision process framework for optimal performance. We present the numerical results showing that the VLSD requires much smaller average detection time compared with the traditional fixed length signal detector to achieve a given detection error probability. Copyright © 2012 John Wiley & Sons, Ltd.     

Detection efficiency of cooperative spectrum sensing in cognitive radio network

Sensing the spectrum in a reliable and efficient manner is crucial to cognitive radio. To combat the channel fading suffered by the single radio, cooperative spectrum sensing is employed, to associate the detection of multiple radios. In this article, the optimization problem of detection efficiency under the constraint of detection probability is investigated, and an algorithm to evaluate the required radio number and sensing time for maximal detection efficiency is presented. To show the effect of cooperation on the detection efficiency, the proposed algorithm is applied to cooperative sensing using the spectral correlation detector under the Rayleigh flat fading channel.     

Adaptive dual‐radio spectrum‐sensing scheme in cognitive radio networks

In this paper, a novel spectrum‐sensing scheme, called adaptive dual‐radio spectrum‐sensing scheme (ADRSS), is proposed for cognitive radio networks. In ADRSS, each secondary user (SU) is equipped with a dual radio. During the data transmission, with the received signal‐to‐noise ratio of primary user (PU) signal, the SU transmitter (SUT) and the SU receiver (SUR) are selected adaptively to sense one channel by one radio while communicating with each other by the other one. The sensing results of the SUR are sent to the SUT through feedback channels (e.g., ACK). After that, with the sensing results from the SUT or the SUR, the SUT can decide whether the channel switching should be carried out. The theoretical analysis and simulation results indicate that the normalized channel efficiency, defined as the expected ratio of time duration without interference to PUs in data transmission to the whole frame length, can be improved while satisfying the interference constraint to PUs. After that, an enhanced ADRSS is designed by integrating ADRSS with cooperative spectrum sensing, and the performance of ADRSS under imperfect feedback channel is also discussed. Copyright © 2011 John Wiley & Sons, Ltd.     

基于循环平稳特征的频谱感知算法概述

传统的静态频谱资源分配分配政策导致频谱利用率低下,为解决这一问题,人们提出利用认知无线电技术实现动态频谱接入.频谱感知是认知无线电的关键技术,循环平稳特征检测算法是3种常见频谱检测算法之一,但是该算法存在各种不足.首先简要介绍认知无线电的背景和概念,然后详细介绍了循环平稳特征检测算法,以及目前提出的各种基于循环平稳特征检测的增强算法,分析了各自的原理及其优缺点.     

认知无线电的频谱感知技术研究

认知无线电是一种用于提高无线电通信频谱利用率的新的智能技术。论文首先简述了认知无线电的背景和概念;然后针对认知无线电感知频谱环境的功能,详细地对比分析了三种频谱检测的方法:匹配滤波器法、能量检测法和循环平稳特性检测法;最后介绍了“协同机制”用于改善极弱信号的接收问题。     

多输入多输出系统基于特征函数频谱盲检测

提出多输入多输出（Multiple-Input Multiple-Output,MIMO）认知无线电系统中基于多元特征函数的频谱盲检测方法.所提方法不需要知道授权用户传输信号的先验知识,也不需要知道信道噪声的方差.通过计算次用户多天线系统接收到的信号样本向量的经验特征函数,MIMO系统中的频谱检测就转换为多元特征函数检验问题.通过度量经验特征函数与已知特征函数的距离, 实现频谱检测.在MIMO系统中,基于特征函数的频谱检测算法比现存的频谱检测方法,具有更好的性能,特别是在低信噪比、小样本条件下.