卫星S频段下行链路频谱占用建模与预测

目前提出的频谱占用模型能够在时域上描述和重现基本的统计特征，如传统的地面移动通信的频谱占用/空闲周期长度可以用经典的广义帕累托(GP)分布、指数分布等分布来拟合。然而在某些复杂的如卫星链路频谱占用场景中，传统的参数估计分布无法给出良好的拟合。为此提出了用核密度估计(KDE)的方法来进行概率密度分布的拟合，在此基础上，分别采用差分整合移动平均自回归模型(ARIMA)和模糊神经网络对频谱占用模型的时间序列进行预测并进行对比。结论表明，核密度估计的使用可以更加准确地描述并再现卫星下行链路所使用S频段的占用时间序列的统计特征，而模糊神经网络的预测比ARIMA模型预测更加精确。     

Spectrum Sensing Framework for Cognitive Radio Networks

Spectrum sensing feature of cognitive radio devices represents a cornerstone characteristic facilitating real-time and accurate spectrum occupancy measurements in cognitive radio networks. It practically enables the cognitive radio devices to detect vacant spectrum holes and use them for their communication purposes. There are numerous spectrum sensing methods proposed in the literature ranging from local based ones to cooperative strategies among several devices increasing the confidence level of the detected spectrum. This paper gives a general spectrum sensing framework for cognitive radio networks, classifies and explores different spectrum sensing techniques and approaches and shows practical examples, from authors’ own experience, of realized spectrum sensing engines and strategies along with some obtained results.     

南海环境下基于白频谱的WLAN超远距离覆盖

通过对南海电磁频谱占用度进行分析,提出了空白电视频段下南海海岛无线宽带网络超远距离覆盖的解决方案,在该方案下设计了一种基于空频谱的海面信道模型。该信道模型以Irregular Terrain Methodology(ITM)模型为基础,通过模型参数修订,加入双径传播效应,使其符合南海海域无线电波传输特征。通过仿真实验,证明了该海面信道模型能够准确反映出空白电视频段无线电波海面传输损耗,为空白电视频段下南海海岛无线宽带网络超远距离覆盖方案提供理论依据。     

Building accurate radio environment maps from multi-fidelity spectrum sensing data

In cognitive wireless networks, active monitoring of the wireless environment is often performed through advanced spectrum sensing and network sniffing. This leads to a set of spatially distributed measurements which are collected from different sensing devices. Nowadays, several interpolation methods (e.g., Kriging) are available and can be used to combine these measurements into a single globally accurate radio environment map that covers a certain geographical area. However, the calibration of multi-fidelity measurements from heterogeneous sensing devices, and the integration into a map is a challenging problem. In this paper, the auto-regressive co-Kriging model is proposed as a novel solution. The algorithm is applied to model measurements which are collected in a heterogeneous wireless testbed environment, and the effectiveness of the new methodology is validated.     

Statistical analysis of mobile radio reception: an extension of clarke?s model

Statistical analysis and modeling of wireless channels is essential to wireless communication systems. Clarke?s model [1] and the corresponding statistical analysis of mobile radio reception has been widely accepted in numerous wireless applications. Since the component phases in Clarke?s model are assumed to be constant in time, the well-known results of statistical analysis based on this model, such as the autocorrelation and Doppler power spectrum, are not appropriate to describe real wireless channels for which the random environments (radio propagation paths) are time-varying and accordingly for which the channel is non-constant in the absence of Doppler frequency shift. In this paper, we extend the traditional Clarke?s model incorporating the effect of fluctuations in the component phases, and perform the statistical analysis which results in a closed-form expression of the autocorrelation of the fading. The theoretical power spectral density function, which is the Fourier transform of the resultant autocorrelation of the fading, is shown to fit the practical measured spectra, which is in contrast to the traditional theoretical flat fading channel spectra (Jakes? spectrum in [2]). The proposed model and statistical results should have important implications for detailed spectral analysis and channel simulations for real wireless communications systems in random fluctuating electromagnetic propagation environments.     

Analysis of Wideband Microstrip Antenna based Spectrum Occupancy Measurement Campaign for Cognitive Radio Application

Frequency scarcity due to demand of bandwidth in wireless communication can be resolved by knowledge of spectrum occupancy. Therefore different measurement campaigns were conducted for spectrum occupancy worldwide. It has been observed that large numbers of bands is underutilized. These bands can be utilized by a secondary user without interference. In this paper, Spectrum utilization has determined by conducting a campaign for measurement of spectrum occupancy in the Solapur city, India for 0.7 to 2.4 GHz frequency region. As per the analysis, Telecom cellular service band has highest spectrum occupancy while aeronautical radio, fixed satellite doesn’t have any utilization. Total average spectrum occupancy is 15.77%. These results are obtained by using circularly polarized wideband microstrip antenna in place of commercially available antennas for measurement campaign, which shows good agreement with occupancy results but with lower system complexity. The results propose that Solapur city would be a better choice for deployment of cognitive radio as emerging technology to share the unoccupied spectrum.     

Interference coordination for LTE-Advanced and FM broadcasting interoperability

The surest way to guarantee that multiple wireless systems can concurrently exist harmlessly, when operating in the same or adjacent channel, is by analyzing spectrum overlapping. This paper proposes a more accurate model to evaluate the interference power from co-channel and adjacent channel of orthogonal frequency division multiplexing-based long term evolution-advanced (LTE-Advanced) towards broadcasting frequency modulation systems at 800?MHz. Power spectral density overlapping factor is employed, and closed form of the interference power loss is derived. Numerical results demonstrate that the proposed method evaluates more exact interference power than the advanced minimum coupling loss (A-MCL) method, where the co-channel and adjacent channel interference powers are reduced by 1.3 and 3?dB, correspondingly, compared to that obtained using the A-MCL method. This decreases the minimum separation distance between the two systems, which can eventually lead to efficient radio spectrum resources utilization.     

一种深度残差网络构建的5G无线智能传播模型

为建立更为准确的全覆盖、全应用、全频谱的5G无线信道模型,提出通过认知无线电与深度神经网络相结合的方法研究无线电波传播特性。根据传统无线传播模型并考虑到不同传播环境,根据信道大尺度衰落特性（包括路径损耗、阴影衰落和小尺度衰落特性）的统计结果,通过BP算法提取特征,并应用FeatureTools进行深度特征综合建立特征方程,计算特征变量与传播损耗的相关系数,进行相关系数的置信区间及变量独立性检验,最终筛选出22个特征并排序。基于深度残差网络建立传播路径损耗的回归模型,结合批正则化过拟合测算平均接收功率,为建立更精确的无线信道模型提供了量化依据,并最终在测试数据集上取得均方根误差8.36（本地）和10.03（云端）的成绩,对工程实践具有较强的参考价值。     

On a Distributed Cognitive MAC Protocol for IEEE 802.11s Wireless Mesh Networks

A distributed frequency agile medium access control (MAC) extension to the IEEE 802.11s for the next generation wireless mesh networks is proposed. The introduced protocol enhancements are capable of concurrent deployment of existing frequency opportunities in order to coordinate simultaneous data transmissions. The root concept is mainly based on the deployment of well-known ISM frequency bands, where the legacy 802.11-based wireless equipments operate, as the common control channel in order to establish contemporaneous transmissions. We apply the aforementioned key concept to the IEEE 802.11s common channel framework to attain two important goals: To improve the channel utilization using the concept of cognitive radio, and to lower the access delay. Through extensive event-driven simulations, taking into account primary user appearance in non-ISM frequency bands, performance of the proposed MAC enhancement is evaluated showing its higher efficiency compared to the existing solutions, in addition to its better wireless medium management.     

Investigation of radio channel uncertainty in distance estimation in wireless sensor networks

The distance estimation between nodes is a crucial requirement for localization and object tracking. Received signal strength (RSS) measurement is one of the used methods for the distance estimation in wireless networks. Its main advantage is that there are no additional hardware requirements. This paper describes a lateration approach for localization and distance estimation using RSS. For the purpose of investigation of RSS uncertainty, several scenarios were designed for both indoor and outdoor measurements. The first set of RSS measurement scenarios was proposed with the intention of hardware independent investigation of radio channel. For the second set of measurements, we employed IRIS sensor nodes to evaluate the distance estimation with certain devices. The experiments considered also obstacles in the radio channel. The results obtained in the proposed scenarios present usability of the method under different conditions. There is also a signal propagation model constructed from measured data at a node, which subsequently serves for distance determination.     

A decision theoretic approach for channel ranking in crowded unlicensed bands

Interference is disruptive to the operation of wireless sensor networks (WSNs) in unlicensed bands as wireless systems proliferate on the spectrum. The design of a spectrum sharing scheme for WSNs to enable coexistence with geographically collocated heterogeneous wireless systems having multiple parallel interfering channels is a persistent challenge. In this context, interference identification and channel ranking in terms of spectrum access opportunities are addressed in this paper. The goal is to develop a low complexity channel ranking algorithm from channel energy measurements at sensors when a packet-reception-ratio to signal-to-interference-and-noise-ratio (PRR-SINR) interference model is unavailable at network initialization phase. The interference characterizing estimators, temporal occupancy and strength level of a channel, are proposed for interference identification. The effectiveness of the estimators is tested on a sensor platform at 2.4 GHz ISM band under interference from WLAN. Subsequently, the impact of the interference estimators on a channel quality from a receiver perspective is determined with a decision theoretic approach. The estimators are weighted according to their influence on the fitness of a channel and channel ranking is established. The proposed channel ranking achieves a significant gain over heuristic channel ranking (HCR) and gives an accurate interference profile of the channels.     

Review of Robust Cooperative Spectrum Sensing Techniques for Cognitive Radio Networks

Cognitive radio networks sense spectrum occupancy and manage themselves to operate in unused bands without disturbing licensed users. The detection capability of a radio system can be enhanced if the sensing process is performed jointly by a group of nodes so that the effects of wireless fading and shadowing can be minimized. However, taking a collaborative approach poses new security threats to the system as nodes can report false sensing data to reach a wrong decision. This paper makes a review of secure cooperative spectrum sensing in cognitive radio networks. The main objective of these protocols is to provide an accurate resolution about the availability of some spectrum channels, ensuring the contribution from incapable users as well as malicious ones is discarded. Issues, advantages and disadvantages of such protocols are investigated and summarized.     

Elastic bandwidth allocation scheme with softened peak interference power constraint for the dynamic cognitive radio systems

The popularity of diverse wireless communication systems has led to increased strains on the unlicensed spectrum. However, investigations have shown that vast portions of the licensed spectrum remain underutilized across frequency, space and time. To improve the utilization of the existing radio spectrum, cognitive radio (CR) allows a secondary system to access the licensed spectrum as long as the primary system’s operation is not compromised. Two main CR transmission modes, spectrum overlay and underlay have been proposed. In the spectrum overlay mode, challenges in quality-of-service (QoS) provisioning arise due to the necessity for secondary users to vacate the channels when a primary user appears. In the underlay model, interference caused to the primary system has to be carefully managed resulting in a constraint of the secondary system’s transmit power, which causes difficulty in QoS provisioning. In this paper, we propose an elastic bandwidth allocation scheme to make concurrent use of both spectrum overlay and underlay transmission modes. Different from existing hybrid transmission strategy, our scheme employ a novel softened peak interference power constraint to improve the performance of the secondary system while still granting the superior protection to the primary system transmissions. This allows the proposed scheme to achieve a superior transmission capacity in the CR network while avoiding the weaknesses of the both spectrum overlay and spectrum underlay transmission modes.     

Spectrum inpainting: a new framework for spectrum status determination in large cognitive radio networks

In this paper, the problem of spectrum status determination is considered for large cognitive radio (CR) ad hoc networks. Spectrum sensing and spectrum decision are critical for cognitive radio network throughput and hence obtaining accurate knowledge of the spectrum status is vitally important to better spectrum usage decisions. The major challenge of this type of problem lies in the fact that for a network covering a large geographical area, only very limited measurements of spectrum occupancy during spectrum sensing may be obtained by the CR users for a certain location in any given time slot. This is due to both the hardware limitations as well as the tradeoff between spectrum sensing time and data throughput of the CR users. By representing the spectrum sensing results across the network as an image, spectrum status determination is formulated as an image recovery problem. The method of total variation inpainting is applied to solve the problem with low determination error. The proposed method takes advantage of the correlations in multiple dimensions and the numerical results demonstrate the effectiveness of the proposed scheme.     

A Framework for Cognitive WiMAX With Frequency Agility

Cognitive radios have the ability to sense the radio spectrum environment and to switch dynamically to available frequency ranges. Mobile WiMax is an emerging wireless networking standard that could potentially benefit from cognitive radio technology. We develop a framework for applying cognitive radio technology to mobile WiMax networks to increase capacity and simplify network operations. In the proposed cognitive WiMax architecture, base stations are equipped with sensitive detectors and assign channels to subscriber stations dynamically based on spectrum availability. Power control is employed to increase frequency reuse in conjunction with spectrum sensing. Using computer simulation, we evaluate the performance of ldquocognitive channel assignmentrdquo relative to conventional dynamic channel assignment. Our numerical results show that cognitive radios can substantially increase the capacity of emerging WiMax networks by exploiting inherent spectrum hole opportunities. The key performance parameters determining the achievable capacity of cognitive WiMax networks are the detection and interference range, which depend in turn on characteristics of the radio propagation environment.     

COGNITIVE RADIOS FOR DYNAMIC SPECTRUM ACCESS - Dynamic Spectrum Access in the Time Domain: Modeling and Exploiting White Space

Dynamic spectrum access is a promising approach to alleviate the spectrum scarcity that wireless communications face today. In short, it aims at reusing sparsely occupied frequency bands while causing no (or insignificant) interference to the actual licensees. This article focuses on applying this concept in the time domain by exploiting idle periods between bursty transmissions of multi-access communication channels and addresses WLAN as an example of practical importance. A statistical model based on empirical data is presented, and it is shown how to use this model for deriving access strategies. The coexistence of Bluetooth and WLAN is considered as a concrete example     

Radio access technology recognition by classification of low temporal resolution power spectrum measurements

In this paper, a machine learning approach is proposed for automatic recognition of the radio access technology (RAT) based on supervised classification of spectrum power measurements in a cognitive radio context. Recognition of the active local RATs allows the cognitive terminal to make informed decisions on which wireless technology to camp, and to adapt its transmission to the wireless environment. To this end, supervised classification of signals obtained from wide band spectrum power measurements with low temporal resolution is carried out. As a first step, generic features are extracted from the power spectrum measurements. Then several supervised classification algorithms, namely the support vector machines (SVMs), k‐nearest neighbors (kNN) and C4.5 are tested. The effects of reducing the number of features on classification accuracy is also tested through feature selection methods. Finally, the impact of the signal duration on classification accuracy is investigated. The obtained results demonstrate that the tested supervised classification algorithms, combined with simple feature extraction and selection methods, are good candidates for RAT recognition from low temporal resolution spectrum power measurements. Copyright © 2009 John Wiley & Sons, Ltd.     

NS-2 based simulation framework for cognitive radio sensor networks

In this paper, we propose a simulation model for cognitive radio sensor networks (CRSNs) which is an attempt to combine the useful properties of wireless sensor networks and cognitive radio networks. The existing simulation models for cognitive radios cannot be extended for this purpose as they do not consider the strict energy constraint in wireless sensor networks. Our proposed model considers the limited energy available for wireless sensor nodes that constrain the spectrum sensing process—an unavoidable operation in cognitive radios. Our model has been thoroughly tested by performing experiments in different scenarios of CRSNs. The results generated by the model have been found accurate which can be considered for realization of CRSNs.     

Macrocell electric field strength prediction model based upon artificial neural networks

A new macrocell prediction model for mobile radio environment is presented. The use of feedforward artificial neural networks makes it possible to overcome some important disadvantages of previous prediction models, including both deterministic and statistical types. Our sample implementation is based upon extensive electric field strength measurements (in the 900-MHz frequency band) that were carried out in the city of Belgrade using six different test transmitter locations. Comparison between the data obtained by the proposed electric field strength prediction model and independent measurement sets show that the proposed model is sufficiently accurate for use in planning mobile radio systems.     

通信无线资源调度系统设计

为了达到对空间无线电资源的有效管理,提高频谱资源的利用率,在认知用户可以准确获取空间频谱利用情况和无线资源特征的前提下,提出了短时和长期学习的无线资源体统调度模型。根据认知用户对空间某点的无线信号进行特征提取,得到频谱的利用情况和各个信道的特征参数,如调制方式、带宽、中心频率和功率,根据用户的发射机特性,利用层次分析法结合测量的信道参数,给出可用信道的特征参数,以供认知用户参考。长期对某一固定点进行测量记录后根据历史数据进行复合,作为认知用户机特征参数跳变的根据,以给出合理的建议。