Papers by Aamir Z. Shaikh
International Journal of ADVANCED AND APPLIED SCIENCES
Device-to-device (D2D) communication plays a crucial role in achieving successful implementation ... more Device-to-device (D2D) communication plays a crucial role in achieving successful implementation of 5G+ and 6G wireless networks. The selection of the communication mode is a vital parameter that enables the activation of a communication link through D2D relays. Consequently, this selection can be considered the fundamental functionality responsible for activating the communication mode of transmission within any device-to-device communication network. This research paper proposes a communication mode selection scheme based on a hexagonal cellular structure. The scheme holds significant potential for application in various wireless transmission schemes. Additionally, the paper investigates the issue of bandwidth sharing in device-to-device networks. In future wireless systems, device-centric approaches will be widely adopted, necessitating a key focus on spectrum sharing. The proposed scheme not only facilitates wireless users in sharing their available spectrum with others but also...
Journal of Informatics and Mathematical Sciences, Aug 9, 2017
A novel architecture is proposed, presented andanalyzed for Internet of Things (IoT) driven smart... more A novel architecture is proposed, presented andanalyzed for Internet of Things (IoT) driven smart agriculture setup. This smart setup integrates Cognitive Radio technology to result in a ubiquitous connected system.The proposed system will optimize the use of natural resource i.e. water. Typically, the flow of water for irrigation of crop fields is not uniform due to many reasons including non-uniform terrain, availability of resources at different sites and etc. This non-uniformity produces lesser product from the available farms. This results in economically challenging for third world countries with limited resources. The proposed system uses two data types to model the different conditions of crop filed. Based on these assumptions, the proposed system is analyzed. The simulation results for the proposed scenario are also presented.
Survey on Fuzzy Logic Enabled Cognitive Radios
Lecture Notes in Computer Science, 2018
Fuzzy Logic is an excellent method to incorporate for making decisions at various levels of cogni... more Fuzzy Logic is an excellent method to incorporate for making decisions at various levels of cognitive radio under uncertain, incomplete and nonlinear environments. This is one of the most important methods to employ. It is due to the inherent characteristics of wireless channels that produce mostly inaccurate and incomplete information. Thus, the coexisting radios in a particular RF band have to make many decisions using incomplete information especially under cognitive radio access regime. This paper elaborates the concept of fuzzy logic and also investigates a review of the fuzzy logic in the domain of spectrum sensing, power control, resource management for cognitive radio applications. The survey presents the key applications as well as the benefits offered by this technology in comparison to the hard decision making logic i.e.1 and 0 for future wireless communications.
We derive probability of detection Pd and false alarm Pf for spectrum sensing cognitive devices, ... more We derive probability of detection Pd and false alarm Pf for spectrum sensing cognitive devices, employing correlated multiple antenna elements using linear test statistic. Detection performance of such sensors is severely degraded due to the correlation among antennas, in addition to that fading channel conditions may further deteriorate the performance. We propose a simple hard decision fusion strategy at the secondary Base Station to improve the performance by exploiting collaborative gain. Region of Convergence (ROC) is also evaluated under OR based fusion strategy. Numerical results certify the proposed proposal. Keywords correlated multiple antenna energy detector, linear statistic,
Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 2018
Spectrum sensing helps cognitive wireless users to gather RF information regarding presence or ab... more Spectrum sensing helps cognitive wireless users to gather RF information regarding presence or absence of spectral holes. These spectral holes are not permanent in nature. These are exploited by cognitive users in secondary fashion in such a way that they do not create harmful interference for primary users (PU). Thus, on sudden arrival of a PU, secondary user must vacate those bands for PU because they are high priority users in comparison to cognitive users. The receiver circuit of cognitive radio estimates the received signal and noise parameters and computes a test statistic. This statistic is compared with a pre-set threshold. However, under realistic scenarios, wireless communication channels behave as time-varying entities. Hence, received signal as well as noise varies significantly. The variation in estimated receiver parameters results in deteriorated detection performance for fixed-threshold sensors. In this paper, it is assumed that there are Gaussian estimation errors in received signal. Under this case, an adaptive threshold based testing rule is applied to explore the performance of spectrum sensing radios under adaptive threshold rule. The results clearly recommend the use of proposed algorithm for received signal with Gaussian channel estimation errors. The results show that the proposed method significantly improves the detection performance of the considered cognitive radio i.e. for a false alarm rate of 0.1, the detection probability of the proposed system improves more than 3 times in comparison to the classic cognitive radio under Gaussian Channel estimation errors. The proposed technique can be utilized for future intelligent radios for 5G wireless networks.
Fuzzy Logic Enabled Stress Detection Using Physiological Signals
Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 2021
Mehran University Research Journal of Engineering and Technology, 2018
A novel hybrid design based electronic voting system is proposed, implemented and analyzed. The p... more A novel hybrid design based electronic voting system is proposed, implemented and analyzed. The proposed system uses two voter verification techniques to give better results in comparison to single identification based systems. Finger print and facial recognition based methods are used for voter identification. Cross verification of a voter during an election process provides better accuracy than single parameter identification method. The facial recognition system uses Viola-Jones algorithm along with rectangular Haar feature selection method for detection and extraction of features to develop a biometric template and for feature extraction during the voting process. Cascaded machine learning based classifiers are used for comparing the features for identity verification using GPCA (Generalized Principle Component Analysis) and K-NN (K-Nearest Neighbor). It is accomplished through comparing the Eigen-vectors of the extracted features with the biometric template pre-stored in the election regulatory body database. The results of the proposed system show that the proposed cascaded design based system performs better than the systems using other classifiers or separate schemes i.e. facial or finger print based schemes. The proposed system will be highly useful for real time applications due to the reason that it has 91% accuracy under nominal light in terms of facial recognition.
International Journal of Advanced Computer Science and Applications, 2020
Marriage of Internet of Everything (IoE) and Cognitive Radio driven technologies seems near under... more Marriage of Internet of Everything (IoE) and Cognitive Radio driven technologies seems near under the umbrella of 6G and 6G+ communication standard. The expected new services that will be introduced in 6G communication will require high data rates for transmission. The learning based algorithms will play a key role towards successful implementation of these novel technologies and evolving next generation wireless standards for providing ubiquitous connectivity. This paper investigates performance of two artificial neural network (ANN) based algorithms for Karachi. These include Nonlinear autoregressive exogenous Algorithm (NARX) and cascade feed forward back propagation neural network (CFFBNN) scheme. A dataset for Karachi is also developed for 1805 MHZ. The results of the two algorithms are compared that show Mean Square Error (MSE) for CFFBNN is 6.8877e-5 at epoch 16 and MSE for NARX is 3.1506e-11 at epoch 26. Hence, exploiting computational performance, NARX performs much superior than the classis CFFBNN algorithm.
Mehran University Research Journal of Engineering and Technology, 2017
Two of the popular refrigeration cycles, VC (Vapor Compression), and VA (Vapor Absorption) are us... more Two of the popular refrigeration cycles, VC (Vapor Compression), and VA (Vapor Absorption) are used extensively for refrigeration purposes. In this paper, a system is proposed that works using both cycles powered by an IC (Internal Combustion) engine, where mechanical energy is used to run the VC cycle while exhaust gasses are used to operate the VA cycle. The VC cycle works on R12 refrigerant while LiBr-H 2 O combination is selected for operation of VA cycle. Firstly, the refrigeration system is modeled, followed by a parametric study to investigate the impacts of various operating parameters on the system performance. The results exhibit that for maximum chilling and overall performance, the condenser and evaporator pressures in the VC cycle are obtained as 710 and 340 kPa, respectively, whereas generator and absorber temperatures in VA cycle are 85 and 20 o C, respectively.
International Journal of Advanced Computer Science and Applications, 2016
A novel cooperative spectrum sensing algorithm is implemented and analyzed using Raspberry Pi. In... more A novel cooperative spectrum sensing algorithm is implemented and analyzed using Raspberry Pi. In the proposed setup, Nokia cell phone is used as a spectrum sensing device while Raspberry Pi functions as a FC device to collect sensing results from local sensing devices. The investigation results of the proposed setup show significant improvement in detection performance as compared to local spectrum sensing techniques. Furthermore, results show a successful communication between sensing nodes and FC.
International Journal of Advanced Computer Science and Applications, 2013
Collaborative spectrum sensing for detection of white spaces helps in realizing reliable and effi... more Collaborative spectrum sensing for detection of white spaces helps in realizing reliable and efficient spectrum sensing algorithms, which results in efficient usage of primary spectrum in secondary fashion. Collaboration among cognitive radios improves probability of detecting a spectral hole as well as sensing time. Available literature, in this domain, uses Gudmundson's exponential correlation model for correlated lognormal shadowing under both urban and suburban environments. However, empirical measurements verify that the suburban environment can better be modeled through double exponential correlation model under suburban environments in comparison to Gudmundson's exponential correlation model. Collaboration among independent sensors provides diversity gains. Asymptotic detection probability for collaborating users under suburban environments using double exponential correlation model has been derived. Also, the Region of Convergence performance of collaborative detection is presented which agrees well with analytical derivations.
Performance Analysis of Correlated Multiple Antenna Spectrum Sensing Cognitive Radio
International Journal of Computer Applications, 2012
International Journal of Advanced Computer Science and Applications, 2020
Wireless services appearing in the next generation wireless standard i.e. 6G include Internet of ... more Wireless services appearing in the next generation wireless standard i.e. 6G include Internet of Everything (IoE), Holographic communications, smart transportation and smart cities require exponential rise in the bandwidth in addition to other requirements. The current static spectrum allocation policy does not allow any new entrant to exploit already grid-locked Radio Frequency (RF) spectrum. Hence, quest for larger bandwidth can be fulfilled through other technologies. These include exploiting sub-Terahertz band, Visible Light Communication and Cognitive Radio scheme or exploiting of RF bands in opportunistic fashion. Cognitive Radio is one of those engines to exploit the RF spectrum in secondary style. Cognitive Radio can use artificial intelligence driven algorithms to complete the task. Several intelligent algorithms can be used for better forecasting of spectral holes. Convolutional Neural Network (CNN) is a Deep Learning algorithm that can be used to predict the presence of a spectral hole that can be opportunistically exploited for efficient utilization of RF spectrum in secondary fashion. This paper investigates the performance of CNN for metropolitan Karachi city of Pakistan so that the users can be provided with uninterrupted access to the network even under busy hours. Dataset for the proposed setup is collected for 1805 MHz frequency band through NI 2901 Universal Software Radio Peripheral (USRP) devices. The root mean square error (RMSE) for the predicted results using CNN appears to be 81.02 at epoch of 200 and mini-batch loss of 3281.8. Based on the predicted results, it was concluded that CNN can be useful for investigating the possible opportunistic usage of RF spectrum; however, further investigation is required with different datasets.
International Journal of Advanced Computer Science and Applications
Marriage of Internet of Everything (IoE) and Cognitive Radio driven technologies seems near under... more Marriage of Internet of Everything (IoE) and Cognitive Radio driven technologies seems near under the umbrella of 6G and 6G+ communication standard. The expected new services that will be introduced in 6G communication will require high data rates for transmission. The learning based algorithms will play a key role towards successful implementation of these novel technologies and evolving next generation wireless standards for providing ubiquitous connectivity. This paper investigates performance of two artificial neural network (ANN) based algorithms for Karachi. These include Nonlinear autoregressive exogenous Algorithm (NARX) and cascade feed forward back propagation neural network (CFFBNN) scheme. A dataset for Karachi is also developed for 1805 MHZ. The results of the two algorithms are compared that show Mean Square Error (MSE) for CFFBNN is 6.8877e-5 at epoch 16 and MSE for NARX is 3.1506e-11 at epoch 26. Hence, exploiting computational performance, NARX performs much superior than the classis CFFBNN algorithm.
Cognitive Radio Enabled Telemedicine System
Wireless Personal Communications, 2015
ABSTRACT
We derive probability of detection P d and false alarm P f for spectrum sensing cognitive devices... more We derive probability of detection P d and false alarm P f for spectrum sensing cognitive devices, employing correlated multiple antenna elements using linear test statistic. Detection performance of such sensors is severely degraded due to the correlation among antennas, in addition to that fading channel conditions may further deteriorate the performance. We propose a simple hard decision fusion strategy at the secondary Base Station to improve the performance by exploiting collaborative gain. Region of Convergence (ROC) is also evaluated under OR based fusion strategy. Numerical results certify the proposed proposal.
Collaborative spectrum sensing for detection of white spaces helps in realizing reliable and effi... more Collaborative spectrum sensing for detection of white spaces helps in realizing reliable and efficient spectrum sensing algorithms, which results in efficient usage of primary spectrum in secondary fashion. Collaboration among cognitive radios improves probability of detecting a spectral hole as well as sensing time. Available literature, in this domain, uses Gudmundson's exponential correlation model for correlated lognormal shadowing under both urban and suburban environments. However, empirical measurements verify that the suburban environment can better be modeled through double exponential correlation model under suburban environments in comparison to Gudmundson's exponential correlation model. Collaboration among independent sensors provides diversity gains. Asymptotic detection probability for collaborating users under suburban environments using double exponential correlation model has been derived. Also, the Region of Convergence performance of collaborative detection is presented which agrees well with analytical derivations.
Joint and marginal probabilities for time of arrival and angle of arrival using ellipsoidal model
2013 3rd IEEE International Conference on Computer, Control and Communication (IC4), 2013
ABSTRACT
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Papers by Aamir Z. Shaikh