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On the performance of AoA estimation algorithms in cognitive radio networks
Abstract
Bandwidth efficiency is very important parameter, because it relates to frequency spectrum, which is naturally, limited resource. The cognitive radio has been proposed as the future technology to meet the ever increasing demand of the radio spectrum by allocating the spectrum dynamically to allow unlicensed access on non-interfering basis. Conventional sensing methods usually relate to sensing the spectrum in three dimensions viz. frequency, time and space. However, there are other dimensions 'Angle' and 'Code' that need to be explored further for spectrum opportunity. This paper investigates the performance of Angle of Arrival (AoA) estimation algorithms like Bartlett's, Capon, MUSIC, Root-MUSIC and ESPRIT in cognitive radio networks. The results show that the performance of the algorithms improves with increasing number of array elements, increasing number of snapshots and increasing signal-to-noise ratio. This new approach of AoA estimation of licensed user, improves frequency reuse capability and increases channel capacity by multiplexing multiple users (licensed and unlicensed) into the same channel at the same time in the same geographical area by forming the beam of unlicensed user in the direction other than the licensed users' AoA direction.
... many studies [3][4][5][6][7][8][9][10][11][12][13][14][15] to present the properties of different multipath environments such as outdoor and indoor propagation channels. ...
... where r 2 s D x 2 C y 2 ; N R D 1 e R 2 =2 2 G , and N E D 1 e aR are the normalization constant because we restrict r s to OE0; R and a is a constant. If we do not consider the effects of ES and RP, substituting Equation (10) or (11) into Equation (7) obtains the joint PDFs of AOA/TOA in closed-form expressions, respectively. ...
To test an adaptive array algorithm in cellular communications, we developed a geometry-based statistical channel model for radio propagation environments, which provides the statistics of the angle of arrival and time of arrival of the multipath components. This channel model assumes that each multipath component of the propagating signal undergoes only one bounce traveling from the transmitter to the receiver and that scattering objects are located according to Gaussian and exponential spatial distributions, and a new scatterer distribution is proposed as a trade-off between the outdoor and the indoor propagation environments. Using the channel model, we analyze the effects of directional antennas at the base station on the Doppler spectrum of a mobile station due to its motion and the performance of its MIMO systems. Copyright © 2014 John Wiley & Sons, Ltd.
... A famous and extensively studied technique for DoA estimation is the Multiple Signal Classification (MUSIC) [4][5][6]. It is a super resolution DoA estimation but for non-coherent signals [7]. To use it with coherent signals, many techniques were developed to its capabilities with such signals. ...
Direction of arrival estimation is a popular technique used for localization and tracking. Many techniques were developed to detect it even in a multipath environment. In this paper we introduce an assessment for four techniques that are based on the MUSIC algorithm. They are the Toeplitz, modified virtual SVD (MV-SVD), Virtual array extension (VSS) and the Modified VSS (MVSS). Two assessment metrics are employed for evaluating these techniques under several conditions such as various SNR vales and numbers of samples. These metrics are RMSE and the success rate.
... Despite of detection stage, many works focus on positioning stage. For example,[9]investigates the performance of AoA estimation algorithms in CR networks. On the other hand,[10][16]have studied spatial dimension detection. ...
State-of-the-art sensing methods mostly detect the spectrum holes by exploring the feature in frequency, time, and geography dimensions. In this paper, we analyze the sensing problem from angle/space domain by using the angle of arrival (AoA) estimation technology. We show a property that the spatial spectrum of noise has the feature of central symmetry, which the arriving signal does not have in general. Hence, the existence of the central symmetry feature depends on the presence or absence of the primary user signal. Motivated by this, we introduce a novel spatial spectrum sensing framework and propose a blind central-symmetry-based feature detection (CSFD) method correspondingly. Different from conventional spectrum sensing, the designed sensing framework reduces the complexity of spatial spectrum sensing and is available for spectrum access. Taking advantage of the inherent central symmetry feature of noise spatial spectrum, the proposed CSFD can achieve higher probability of detection even at low signal-to-noise ratios (SNRs) and offer AoA information. Theoretical performance analysis of the proposed CSFD method is also provided. Simulation results are presented to verify the efficiency of the proposed algorithm.
Many spectrum sensing algorithms have as a purpose determining if the primary users (PUs) are present or absent, by using statistical signal characteristics. However, for a better management of a cognitive network, additional information about PUs, such as their position, is required. Motivated by these requirements, this paper investigate the performance of MUSIC and Capon algorithms in Cognitive Radio networks context and show that the MUSIC algorithm is highly accurate and stable while also providing a high angular resolution compared to the Capon algorithm.
Spectrum sensing is an essential process in cognitive radio networks. The majority of existing sensing approaches aim to detect the existence of a signal on a busy channel without differentiating whether a signal originates from a primary user or not. In this paper, we address this issue and propose to employ an Angle of Arrival (AoA) based sensing approach to effectively distinct a primary user's signal from a secondary user' signal. Multiple Signal Classification (MUSIC), a classical AoA algorithm, is selected due to easy implementation and high resolution. Unlike the previous works on AoA based sensing, we thoroughly investigate its sensing performance based on a practical model which captures typical characteristics in cognitive radio networks. Two performance metrics named false alarm probability and miss detection probability are theoretically analyzed. Closed-form analytical expressions are derived for both metrics. Extensive simulations are carried out under various scenarios to evaluate AoA based sensing approach.
Device-to-Device (D2D) communications underlaying cellular network exploits physical proximity of the devices and aims at enhancing resource utilization, coverage, data rates and Quality of Service (QOS). Further, it enables the network operators to offload conventional network routed traffic to direct peer- to-peer links and could also support new application fields, such as Machine-to-Machine (M2M) and Vehicle-to-Vehicle (V2V), communication. In order to enable D2D communication, allocating resources (Physical resource blocks: PRBs) to D2D links by reusing cellular resources is a vital procedure. There are several resource allocation (RA) schemes that facilitate resource reuse of cellular PRBs for D2D communication. In most of these schemes, the crucial information for deciding upon PRB reuse is positions of D2D pairs and cellular users, so that mutual interference can be reduced. Further, there are certain schemes that rely on angular information of users to carry out resource allocation for D2D users. Thus, accuracy of position information plays an important role for employing these RA schemes in real world. This paper discusses RA schemes that are based on position/angular information and evaluates the robustness of location based RA schemes against positioning errors in real world deployment.
The cognitive radio technology is the new paradigm to fulfill ever increasing need of bandwidth ultimately the radio spectrum by accommodating the radio spectrum dynamically to secondary users/unlicensed users without causing the interference. In cognitive radio, the spectrum opportunities have been checked for Space, Time and frequency dimensions but ‘Angle’ dimension has not been explored till now. In this paper we have investigated accuracy of various ‘Angle-of-Arrival (AoA)’ estimation algorithms: ESPRIT, MUSIC, Bartlett, and Capon for opportunistic secondary users’ network under AWGN and time varying fading channels. The improvement in performance of these algorithms has been observed as array elements, signal-to-noise ratio and samples increases. An ‘adaptive thresholding’ technique has been proposed to improve the performance of AoA algorithms. Thus by estimating an ‘Angle-of- Arrival’ of licensed users, the unlicensed users can be accommodated in the same geographical area into the same channel in the same frequency band at the same time by directing unlicensed users’ beam in different direction than the direction of licensed users. Thereby improving spectrum utilization.
Around the world static allocation of spectrum scheme is commonly used which is allocated to specific technology based services, such as mobile, fixed, broadcast, fixed satellite and mobile satellite services on exclusive basis. These wireless communication systems are representatives of 2G and 3G systems with all evolution phases towards 4G systems. The complexity of wireless networks requires a careful design, especially related to bandwidth and energy efficiency. Bandwidth efficiency is very important parameter, because it relates to frequency spectrum, which is naturally scarce resource. Many new wireless applications cannot be rolled out because of unavailability of free spectrum.The cognitive radio has been proposed as the future technology to meet the ever increasing demand of the radio spectrum by allocating the spectrum dynamically without causing interference to the licensed users. The digital dividend of 700MHz band opens the door for cognitive radio making broadband wireless access cheaper. But in cognitive radio, spectrum sensing is the fundamental problem. In this paper we describe the hybrid detection method which exploits the advantages of energy detection and covariance absolute value methods. The simulation shows that the proposed hybrid detection method exploiting TV white space outperformed energy detection and covariance absolute value method under Rayleigh time varying fading channel and is more insensitive to the type of input data.
Smart antenna refers to any type of antenna arrays combined with signal processor components which can adjust its own beam pattern in order to emphasize on the signal of interest and minimizing the interference signal. The accurate estimation of direction of interest which is also known as direction of arrival (DOA) of the incident signals is very significant to produce beam from antenna. There are several algorithms those have the ability in calculating the DOA of the incidents signals. In this paper an adaptive antenna is applied by using the most frequent used algorithm, estimation of signal parameters via rotational invariance technique (ESPRIT) to obtain the direction of arrival (DOA) of any incident signals. The exact number of samples and elements used is the most important parameter in the algorithms in order to sustain the accuracy of the direction of arrival of the incident signals. The optimization was done by running the program in cellular mobile environments. The data from the optimization was evaluated using SPSS in evaluating the performance of the algorithm.
Network Coding for Cognitive Radio Relay NetworksCognitive Radio Networks ArchitectureTerminal Architecture of CRNQoS Provisional Diversity Radio Access NetworksScaling Laws of Ad-hoc and Cognitive Radio NetworksReferences
In the entire world the wireless communication systems are represented by 2G and 3G systems with all stages of evolution towards 4G systems. The complexity of wireless networks requires a careful design, especially related to bandwidth and energy efficiency. Bandwidth efficiency is very important parameter, because it relates to frequency spectrum, which is a natural limited resource. The cognitive radio has been proposed as the future technology to meet the ever increasing demand of the radio spectrum by allocating the spectrum dynamically to allow unlicensed access on noninterfering basis. The digital dividend of 700MHz band (mainly used by TV broadcast services) opens the door for cognitive radio applications due to its excellent propagation characteristics compared to GSM 1800 MHz, 2.1 GHz or 2.5 GHz bands. In cognitive radio, spectrum sensing is the fundamental problem. In this paper we are analyzing the performance of spectrum sensing algorithms; energy detection and covariance absolute value utilizing TV white space for IEEE 802.11 af standard.
Concept of wireless communication systems which use smart antennas is based on digital signal processing algorithms. Thus, the smart antennas systems become capable to locate and track signals by both: users and interferers and dynamically adapts the antenna pattern to enhance the reception in Signal-Of-Interest direction and minimizing interference in Signal-Of-Not-Interest direction. Hence, Space Division Multiple Access system, which uses smart antennas, is being used more often in wireless communications, because it shows improvement in channel capacity and co-channel interference. However, performance of smart antenna system greatly depends on efficiency of digital signal processing algorithms. The algorithm uses the Direction of Arrival (DOA) algorithms to estimate the number of incidents plane waves on the antenna array and their angle of incidence. This paper investigates performance of the DOA algorithms such as MUSIC, ESPRIT and ROOT MUSIC on the uniform linear array in the presence of white noise. The simulation results show that MUSIC algorithm is the best. The resolution of the DOA techniques improves as number of snapshots, number of array elements and signal-to-noise ratio increases.
Since the spectrum is the scarce resource, spectrum sensing is an important part of Green Engineering. The cognitive radio has been proposed as the future technology to meet the ever increasing demand of the radio spectrum by allocating the spectrum dynamically to allow unlicensed access on non-interfering basis. In cognitive radio, spectrum sensing is the fundamental problem. Energy detection method is the simplest method but suffers from noise uncertainty problem. Covariance based detection exploits space-time signal correlation, but its performance is very sensitive to the signal correlation. Hybrid detection method exploits the advantages of these two methods by utilizing energy detection in low correlation and covariance based detection in high correlation. We analyze the performance of hybrid detection method exploiting TV White Space under Rayleigh and Rician fading channel for different Signal-to-Noise Ratio values by setting probabilities of false alarm and measuring probability of detection. Simulation shows that the hybrid detection method outperformed energy detection and covariance based detection method and is more insensitive to the type of input data. The hybrid detection method shows the better performance compared to energy detection and covariance method under time-varying fading conditions.
In cognitive radio networks, the first cognitive task preceding any form of dynamic spectrum management is the spectrum sensing and identification of spectrum holes in wireless environment. In cognitive radio, spectrum sensing is fundamental crucial task. Energy detection method is a basic method, which requires knowledge of noise power but suffers from noise uncertainty problem. Covariance based detection exploits space-time signal correlation that does not require the knowledge of noise and signal power. The covariances of signal and noise are generally different which can be used in detection of licensed user. However, there are not many studies that show the feasibility of the detectors and analyze their performance under fading channels. In this paper, we analyzed the detector performance exploiting TV White Space under Rayleigh and Rician fading channel by setting probabilities of false alarm and measuring probability of detection. We further analyze the effect of smoothing factor and overall correlation coefficient on the performance of covariance based detector. Covariance based detector outperformed the energy detector with noise uncertainty even under the time-varying fading channels.
This study presents the experimental verification of multiple signal classification (MUSIC), estimation of signal parameters via rotational invariance techniques (ESPRIT) and space-alternating generalized expectation-maximization (SAGE) algorithms in estimating the direction-of-arrival (DoA) of a narrowband source. MUSIC and ESPRIT are subspace-based methods while SAGE is a maximum-likelihood technique. A BPSK signal was transmitted off-the-air and was received under varied system parameters. The three algorithms were then applied on the recorded data. The performance of the three algorithms was compared based on their capability to estimate the signal's general DoA. The results showed that SAGE has an average deviation in signal localization of 3.5deg, followed by MUSIC 3.8deg and ESPRIT 9.7deg. Further tests show that SAGE can closely estimate the signal DoA with lower data samples than MUSIC and ESPRIT. For subspace-based methods, a 4-element antenna array gives better estimates than a 2-element array
Directional of arrival (DOA) estimation technology play an important role in enhancing the performance of adaptive arrays for mobile wireless communications. A number of DOA estimation algorithms have been developed during the year. In this paper we present the performance analysis and comparison for Capon and MUSIC DOA estimation algorithms with a uniform circular array. Our focuses were to unveil the relationship between the mean square estimation error (MSE) and system resolution with phase mismatch. Monte Carlo simulation study results have been presented to illustrate the dependence of MSE with the quality of array calibration. The dependence of MSAE on array element number was also studied.
In this article we simulate four famous algorithms in DOA and then compare the algorithms based on their finding and estimating of the accuracy level angels from two different users, having demonstrated the result of simulation of the four algorithms in comparison tables, it is observed that ROOT-MUSIC algorithm have high level of accuracy in estimation of close angles(28, 30 degrees). MUSIC, Spatially Smoothed and ML algorithms have the next steps in accuracy respectively.
This paper presents a tool for the modelling, analysis and simulation of direction-of-arrival (DOA) estimation and adaptive beamforming needed in the design of smart antenna arrays for wireless mobile communications. In this paper performance of adaptive beamforming algorithm has been studied for two different DOA estimation algorithms namely MUSIC & MVDR. MUSIC estimates the number of incident signals on the array and their directions of arrival. It also gives the direction of arrival of desired signal. The Minimum Variance Distortion less Response (MVDR) is a very well known algorithm to obtain the optimum weight vector, which maximizes the output signal to noise and interference ratio (SNIR) of multiple antennas. The LMS algorithm, which has been simulated, is a simple yet efficient technique for robust adaptive beamforming. The LMS algorithm recursively computes and updates the weight vector. It has been observed that LMS algorithm gives the response for the two different DOA estimation algorithms MUSIC & MVDR depending upon the DOA estimations.As the signals are randomly generated the response of LMS algorithm differ for some cases of DOA estimations using MUSIC & MVDR otherwise it gives same response for both the algorithms. The algorithms have been simulated in MATLAB 7.4 version. A simulation tool with a graphical user interface, which implements these algorithms, is developed. Results of numerical simulation are useful for the design of smart antennas systems with optimal performance.
Base transceiver stations (BTS) with antenna arrays employing narrow beam patterns pointing to each user rather than omnidirectional or directional antenna covering a large number of users or areas can provide better network performance. It is the fundamental theory of smart antenna systems (SAS) designed for a modern cellular network, which is more challenged nowadays by network capacity and service quality due to the increased Internet traffic volume. In this paper, super-resolution algorithms are applied to the switched beam smart antenna system, and a higher angle resolution and performance are achieved. This paper presents super-resolution algorithms specifically developed for the switched beam smart antenna system. The particular research interest is focused on the performance of a multiple signal classification (MUSIC) algorithm and a RELAX algorithm. The study results show a higher angle resolution and a significant overall system benefit by using these two algorithms. We also discuss the non-uniform geometry arrangement of the array and its application to improve the capacity of direction finding further. Simulation results are presented.
There is a global coordinated move for Digital Switchover (DSO) by discontinuing analogue TV transmission. In India the frequency band 470-806 MHz has been allotted to Fixed, mobile broadcasting services on primary basis and 698-806 MHz more specific 700MHz band mainly used by TV broadcast services. This Digital Dividend offers real opportunities for wireless innovation. We discuss the scope and nature of opportunities for white space created by Digital Dividend (700 MHz band) in India.
700MHz band attracted many researchers and stakeholders for mobile communications by providing a rare opportunity to have cost effective wireless solutions due to its excellent propagation characteristics compared to GSM 1800 MHz, 2.1 GHz or 2.5 GHz bands for 3G/BWA. In India, 698-806 MHz more specific 700MHz band mainly used by TV broadcast services. We discuss the scope and nature of opportunities for white space created by Digital Dividend (700 MHz band) in India especially to rural India by providing wireless broadband for the applications like e-education, e-agriculture, e-animal husbandry and e-health which would help in decreasing primary school drop-out rate, in decreasing farmer suicides rate and in decreasing mortality rate. Further use cases for the exploitation of TV White Space suitable for rural India are discussed based on user's and BS geo-location and user's mobility; which is followed by an overview of recent regulatory activities.
The authors analyze the performance of Root-Music, a variation of
the MUSIC algorithm, for estimating the direction of arrival (DOA) of
plane waves in white noise in the case of a linear equispaced sensor
array. The performance of the method is analyzed by examining the
perturbation in the roots of the polynomial formed in the intermediate
step of Root-Music. In particular, asymptotic results for the mean
squared error in the estimates of the direction of arrival are derived.
Simplified expressions are presented for the one- and two-source case
and compared to those obtained for least-squares ESPRIT. Computer
simulations are also presented, and they are in close agreement with the
theory. An important outcome of this analysis is the fact that the error
in the signal zeros has a largely radial component. This provides an
explanation as to why the Root-Music is superior to the spectral MUSIC
algorithm
Simunic, ―Hybrid Detection Method for Spectrum Sensing in Cognitive Radio,‖ 35 th Jubilee International Convention MIPRO 2012
- T Dhope
T. Dhope, D. Simunic, ―Hybrid Detection Method for Spectrum Sensing in Cognitive Radio,‖ 35 th Jubilee International Convention MIPRO 2012. Opatija, Croatia, May 2012(accepted)