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Air-to-Ground (A2G) communication is considered as a significant enabler technology in next-generation networks. To make this a reality, a comprehensive understanding of the A2G channels is vital. This paper presents an Elevation Angle (EA) based two-ray mean path loss model for the A2G channels. In particular, we present closed-form expressions for the path loss with respect to the elevation angle and compare the results with ray-tracing simulation results. Our results show that mean path loss for the A2G channels can be accurately characterized by the proposed EA based two-ray model. Our study investigates different altitudes of the aerial terminal, different types of terrains, and two polarizations, wherein the proposed EA-based two-ray model matches well with the ray-tracing simulation results. Furthermore, a comparison of the proposed model with the other known path loss models in the literature is conducted. Finally, this work reveals an interesting relationship between the elevation angle and the signal down-fades, that these signal down-fades appear at approximately the same elevation angles regardless of the platform altitude.
N.H. Ranchagoda; K. Sithamparanathan; M. Ding; A. Al-Hourani; K.M. Gomez. Elevation-angle based two-ray path loss model for Air-to-Ground wireless channels. Vehicular Communications 2021, 32, 100393 .
AMA StyleN.H. Ranchagoda, K. Sithamparanathan, M. Ding, A. Al-Hourani, K.M. Gomez. Elevation-angle based two-ray path loss model for Air-to-Ground wireless channels. Vehicular Communications. 2021; 32 ():100393.
Chicago/Turabian StyleN.H. Ranchagoda; K. Sithamparanathan; M. Ding; A. Al-Hourani; K.M. Gomez. 2021. "Elevation-angle based two-ray path loss model for Air-to-Ground wireless channels." Vehicular Communications 32, no. : 100393.
Passive multistatic radars have gained a lot of interest in recent years as they offer many benefits contrary to conventional radars. Here in this research, our aim is detection of target in a passive multistatic radar system. The system contains a single transmitter and multiple spatially distributed receivers comprised of both the surveillance and reference antennas. The system consists of two main parts: 1. Local receiver, and 2. Fusion center. Each local receiver detects the signal, processes it, and passes the information to the fusion center for final detection. To take the advantage of spatial diversity, we apply major fusion techniques consisting of hard fusion and soft fusion for the case of multistatic passive radars. Hard fusion techniques are analyzed for the case of different local radar detectors. In terms of soft fusion, a blind technique called equal gain soft fusion technique with random matrix theory-based local detector is analytically and theoretically analyzed under null hypothesis along with the calculation of detection threshold. Furthermore, six novel random matrix theory-based soft fusion techniques are proposed. All the techniques are blind in nature and hence do not require any knowledge of transmitted signal or channel information. Simulation results illustrate that proposed fusion techniques increase detection performance to a reasonable extent compared to other blind fusion techniques.
Asma Asif; Sithamparanathan Kandeepan. Cooperative Fusion Based Passive Multistatic Radar Detection. Sensors 2021, 21, 3209 .
AMA StyleAsma Asif, Sithamparanathan Kandeepan. Cooperative Fusion Based Passive Multistatic Radar Detection. Sensors. 2021; 21 (9):3209.
Chicago/Turabian StyleAsma Asif; Sithamparanathan Kandeepan. 2021. "Cooperative Fusion Based Passive Multistatic Radar Detection." Sensors 21, no. 9: 3209.
In a distributed cognitive radio (CR) sensor network, transmission and reception on vacant channels require cognitive radio nodes to achieve rendezvous. Because of the lack of adequate assistance from the network environment, such as the central controller and other nodes, assisted rendezvous for distributed CR is inefficient in a dynamic network. As a result, non-assisted blind rendezvous, which is unaware of its counterpart node, has recently led to a lot of interest in the research arena. In this paper, we study a channel rendezvous method based on prime number theory and propose a new multi-radio-based technique for non-assisted rendezvous with the blind and heterogeneous condition. The required time and the optimal number of radios for the guaranteed rendezvous are calculated using probability-based measurement. Analytical expressions for probabilistic guaranteed rendezvous conditions are derived and verified by Monte Carlo simulation. In addition, the maximum time to rendezvous (MTTR) is derived in closed form using statistical and probabilistic analysis. Under different channel conditions, our proposed solution leads to a substantial time reduction for guaranteed rendezvous. For the sake of over-performance of our proposed system, the simulation outcome is compared to a recently proposed heterogeneous and blind rendezvous method. The Matlab simulation results show that our proposed system’s MTTR gains range from
Tahidul Islam; Sithamparanathan Kandeepan; Robin. Evans. Multi-Radio Based Rendezvous Technique for Heterogeneous Cognitive Radio Sensor Network. Sensors 2021, 21, 2997 .
AMA StyleTahidul Islam, Sithamparanathan Kandeepan, Robin. Evans. Multi-Radio Based Rendezvous Technique for Heterogeneous Cognitive Radio Sensor Network. Sensors. 2021; 21 (9):2997.
Chicago/Turabian StyleTahidul Islam; Sithamparanathan Kandeepan; Robin. Evans. 2021. "Multi-Radio Based Rendezvous Technique for Heterogeneous Cognitive Radio Sensor Network." Sensors 21, no. 9: 2997.
Many wireless Internet-of-Things applications require extended battery life ranging from a few months to a few years. Such applications have motivated the recent developments in low power wide area networks, including the rise of Long Range (LoRa) technology. LoRa has a simple modulation scheme designed for extended converge, low battery consumption, and resistance to high interference levels. Thus LoRa is primarily targeted for shared spectrum applications where interference levels are typically higher than controlled spectrum applications where a single operator usually has a dominant control on the quality of service. As a result, it is of paramount importance to carefully design IoT networks while taking into account the impending impacts of interference and propagation environments. This paper presents a novel LoRa network design framework that utilizes a developed open-source emulator to provide a reliable network coverage estimation. The framework is tested in one of the largest open-access IoT network designs in Australia, which enabled the deployment of 294 sensors and 48 gateways. Both the framework and the emulator are implemented using MATLAB scripting, enabling integration with built-in and external radio planning tools. The framework leverages real interference measurements captured using software defined radio that records the spectrotemporal behavior of the existing traffic in the shared band.
Bassel Al Homssi; Kosta Dakic; Simon Maselli; Hans Wolf; Sithamparanathan Kandeepan; Akram Al-Hourani. IoT Network Design Using Open-Source LoRa Coverage Emulator. IEEE Access 2021, 9, 53636 -53646.
AMA StyleBassel Al Homssi, Kosta Dakic, Simon Maselli, Hans Wolf, Sithamparanathan Kandeepan, Akram Al-Hourani. IoT Network Design Using Open-Source LoRa Coverage Emulator. IEEE Access. 2021; 9 (99):53636-53646.
Chicago/Turabian StyleBassel Al Homssi; Kosta Dakic; Simon Maselli; Hans Wolf; Sithamparanathan Kandeepan; Akram Al-Hourani. 2021. "IoT Network Design Using Open-Source LoRa Coverage Emulator." IEEE Access 9, no. 99: 53636-53646.
Software-Defined Networking (SDN) and Internet of Things (IoT) are the trends of network evolution. SDN mainly focuses on the upper level control and management of networks, while IoT aims to bring devices together to enable sharing and monitoring of real-time behaviours through network connectivity. On the one hand, IoT enables us to gather status of devices and networks and to control them remotely. On the other hand, the rapidly growing number of devices challenges the management at the access and backbone layer and raises security concerns of network attacks, such as Distributed Denial of Service (DDoS). The combination of SDN and IoT leads to a promising approach that could alleviate the management issue. Indeed, the flexibility and programmability of SDN could help in simplifying the network setup. However, there is a need to make a security enhancement in the SDN-based IoT network for mitigating attacks involving IoT devices. In this article, we discuss and analyse state-of-the-art DDoS attacks under SDN-based IoT scenarios. Furthermore, we verify our SDN sEcure COntrol and Data plane (SECOD) algorithm to resist DDoS attacks on the real SDN-based IoT testbed. Our results demonstrate that DDoS attacks in the SDN-based IoT network are easier to detect than in the traditional network due to IoT traffic predictability. We observed that random traffic (UDP or TCP) is more affected during DDoS attacks. Our results also show that the probability of a controller becoming halt is 10%, while the probability of a switch getting unresponsive is 40%.
Song Wang; Karina Gomez; Kandeepan Sithamparanathan; Muhammad Rizwan Asghar; Giovanni Russello; Paul Zanna. Mitigating DDoS Attacks in SDN-Based IoT Networks Leveraging Secure Control and Data Plane Algorithm. Applied Sciences 2021, 11, 929 .
AMA StyleSong Wang, Karina Gomez, Kandeepan Sithamparanathan, Muhammad Rizwan Asghar, Giovanni Russello, Paul Zanna. Mitigating DDoS Attacks in SDN-Based IoT Networks Leveraging Secure Control and Data Plane Algorithm. Applied Sciences. 2021; 11 (3):929.
Chicago/Turabian StyleSong Wang; Karina Gomez; Kandeepan Sithamparanathan; Muhammad Rizwan Asghar; Giovanni Russello; Paul Zanna. 2021. "Mitigating DDoS Attacks in SDN-Based IoT Networks Leveraging Secure Control and Data Plane Algorithm." Applied Sciences 11, no. 3: 929.
The radio-over-fiber (RoF) technology has been widely studied during the past decades to extend the wireless communication coverage by leveraging the low-loss and broad bandwidth advantages of the optical fiber. With the increasing need for wireless communications, using millimeter-waves (mm-wave) in wireless communications has become the recent trend and many attempts have been made to build high-throughput and robust mm-wave RoF systems during the past a few years. Whilst the RoF technology provides many benefits, it suffers from several fundamental limitations due to the analog optical link, including the fiber chromatic dispersion and nonlinear impairments. Various approaches have been proposed to address these limitations. In particular, machine learning (ML) algorithms have attracted intensive research attention as a promising candidate for handling the complicated physical layer impairments in RoF systems, especially the nonlinearity during signal modulation, transmission and detection. In this paper, we review recent advancements in ML techniques for RoF systems, especially those which utilize ML models as physical layer signal processors to mitigate various types of impairments and to improve the system performance. In addition, ML algorithms have also been widely adopted for highly efficient RoF network management and resource allocation, such as the dynamic bandwidth allocation and network fault detection. In this paper, we also review the recent works in these research domains. Finally, several key open questions that need to be addressed in the future and possible solutions of these questions are also discussed.
Jiayuan He; Jeonghun Lee; Sithamparanathan Kandeepan; Ke Wang. Machine Learning Techniques in Radio-over-Fiber Systems and Networks. Photonics 2020, 7, 105 .
AMA StyleJiayuan He, Jeonghun Lee, Sithamparanathan Kandeepan, Ke Wang. Machine Learning Techniques in Radio-over-Fiber Systems and Networks. Photonics. 2020; 7 (4):105.
Chicago/Turabian StyleJiayuan He; Jeonghun Lee; Sithamparanathan Kandeepan; Ke Wang. 2020. "Machine Learning Techniques in Radio-over-Fiber Systems and Networks." Photonics 7, no. 4: 105.
Delivering Internet-of-Things (IoT) connectivity over satellite is a promising solution for applications in remote and sparsely populated areas. These applications range from smart agriculture, logistics, asset tracking to emergency services. Using a shared radio spectrum with terrestrial services will facilitate a cost-effective and rapid deployment of IoT-over-Satellite since it reduces the administrative and financial hurdles of leasing a dedicated segment of the spectrum. Although IoT-over-Satellite communication provides larger service coverage, the vast number of IoT devices also increase the interference in the satellite uplink channel, and it becomes a significant challenge for the reliable performance of the IoT-over-satellite. In this paper, we propose a framework for modeling the performance of IoT-over-Satellite access systems when sharing the radio spectrum with terrestrial networks. We take into consideration several important aspects, namely; satellite orbit, terrestrial IoT devices uplink interference, atmosphere and gas absorption, and the probability of line-of-sight. The performance of the overall system is presented in terms of the uplink signal-to-interference-plus-noise ratio (SINR), and thus the time-availability of the satellite link during a typical pass. We focus on low earth orbit satellites due to their potential use in IoT applications, where we evaluate the framework using actual parameters of satellites located in 300–800 km orbits. Furthermore, the paper presents a numercial model to obtain the most suitable antenna beamwidth that maximizes the link-availability of the satellite link by the simultaneous reduction in the terrestrial interference and the boosting of the underlying IoT signal of interest.
Chiu Chun Chan; Akram Al-Hourani; Jinho Choi; Karina Mabell Gomez; Sithamparanathan Kandeepan. Performance Modeling Framework for IoT-over-Satellite Using Shared Radio Spectrum. Remote Sensing 2020, 12, 1666 .
AMA StyleChiu Chun Chan, Akram Al-Hourani, Jinho Choi, Karina Mabell Gomez, Sithamparanathan Kandeepan. Performance Modeling Framework for IoT-over-Satellite Using Shared Radio Spectrum. Remote Sensing. 2020; 12 (10):1666.
Chicago/Turabian StyleChiu Chun Chan; Akram Al-Hourani; Jinho Choi; Karina Mabell Gomez; Sithamparanathan Kandeepan. 2020. "Performance Modeling Framework for IoT-over-Satellite Using Shared Radio Spectrum." Remote Sensing 12, no. 10: 1666.
The optical wireless communication (OWC) system has been widely studied as a promising candidate for indoor high-speed wireless communications. In particular, the spatial diversity scheme has shown to be effective to improve the performance of OWC systems. However, the delay amongst multiple channels in this scheme may result in severe inter-symbol-interference (ISI) and degradations of the system performance. Recent studies have shown that the symbol decision schemes based on recurrent neural networks (RNNs) can mitigate the impact of delays. However, their performances are limited when the channel delays are long. In this paper, we propose a delay-tolerant indoor OWC system, which utilizes an attention-augmented long-short term memory (ALSTM) RNN decision scheme to handle long channel delays. A 10 Gb/s repetition-coded indoor OWC system with the proposed ALSTM RNN decision scheme is experimentally demonstrated. Compared with traditional OWC systems which add cyclic prefix (CP) /zero-postfix (ZP) to combat the impact of channel delays, the proposed system does not reduce the effective data rate or throughput. Compared with the previous study which adopts the vanilla RNN decision scheme, the proposed ALSTM RNN decision scheme can better learn dependencies amongst received symbols with the help of attention mechanism, especially amongst non-neighboring symbols. Hence, it is more robust against the ISI induced by long channel delays. Experimental results show that compared with the previously studied vanilla RNN, over one-order-of-magnitude bit-error-rate improvement is achieved when the channel delay is more than 4.7-symbol-period.
Jiayuan He; Jeonghun Lee; Tingting Song; Hongtao Li; Sithamparanathan Kandeepan; Ke Wang. Delay-Tolerant Indoor Optical Wireless Communication Systems Based on Attention-Augmented Recurrent Neural Network. Journal of Lightwave Technology 2020, 38, 4632 -4640.
AMA StyleJiayuan He, Jeonghun Lee, Tingting Song, Hongtao Li, Sithamparanathan Kandeepan, Ke Wang. Delay-Tolerant Indoor Optical Wireless Communication Systems Based on Attention-Augmented Recurrent Neural Network. Journal of Lightwave Technology. 2020; 38 (17):4632-4640.
Chicago/Turabian StyleJiayuan He; Jeonghun Lee; Tingting Song; Hongtao Li; Sithamparanathan Kandeepan; Ke Wang. 2020. "Delay-Tolerant Indoor Optical Wireless Communication Systems Based on Attention-Augmented Recurrent Neural Network." Journal of Lightwave Technology 38, no. 17: 4632-4640.
Billions of sensors are expected to be connected to the Internet through the emerging Internet of Things (IoT) technologies. Many of these sensors will primarily be connected using wireless technologies powered using batteries as their sole energy source which makes it paramount to optimize their energy consumption. In this paper, we provide an analytic framework of the energy-consumption profile and its lower bound for an IoT end device formulated based on Shannon capacity. We extend the study to model the average energy-consumption performance based on the random geometric distribution of IoT gateways by utilizing tools from stochastic geometry and real measurements of interference in the ISM-band. Experimental data, interference measurements and Monte-Carlo simulations are presented to validate the plausibility of the proposed analytic framework, where results demonstrate that the current network infrastructures performance is bounded between two extreme geometric models. This study considers interference seen by a gateway regardless of its source.
Bassel Al Homssi; Akram Al-Hourani; Sathyanarayanan Chandrasekharan; Karina Mabell Gomez; Sithamparanathan Kandeepan. On the Bound of Energy Consumption in Cellular IoT Networks. IEEE Transactions on Green Communications and Networking 2019, 4, 355 -364.
AMA StyleBassel Al Homssi, Akram Al-Hourani, Sathyanarayanan Chandrasekharan, Karina Mabell Gomez, Sithamparanathan Kandeepan. On the Bound of Energy Consumption in Cellular IoT Networks. IEEE Transactions on Green Communications and Networking. 2019; 4 (2):355-364.
Chicago/Turabian StyleBassel Al Homssi; Akram Al-Hourani; Sathyanarayanan Chandrasekharan; Karina Mabell Gomez; Sithamparanathan Kandeepan. 2019. "On the Bound of Energy Consumption in Cellular IoT Networks." IEEE Transactions on Green Communications and Networking 4, no. 2: 355-364.
Kagiso Magowe; Andrea Giorgetti; Kandeepan Sithamparanathan. Closed-Form Approximation of Weighted Centroid Localization Performance. IEEE Sensors Letters 2019, 3, 1 -4.
AMA StyleKagiso Magowe, Andrea Giorgetti, Kandeepan Sithamparanathan. Closed-Form Approximation of Weighted Centroid Localization Performance. IEEE Sensors Letters. 2019; 3 (12):1-4.
Chicago/Turabian StyleKagiso Magowe; Andrea Giorgetti; Kandeepan Sithamparanathan. 2019. "Closed-Form Approximation of Weighted Centroid Localization Performance." IEEE Sensors Letters 3, no. 12: 1-4.
The number of small sophisticated wireless sensors which share the electromagnetic spectrum is expected to grow rapidly over the next decade and interference between these sensors is anticipated to become a major challenge. In this paper we study the interference mechanisms in one such sensor, automotive radars, where our results are directly applicable to a range of other sensor situations. In particular, we study the impact of radar waveform design and the associated receiver processing on the statistics of radar–radar interference and its effects on sensing performance. We propose a novel interference mitigation approach based on pseudo-random cyclic orthogonal sequences (PRCOS), which enable sensors to rapidly learn the interference environment and avoid using frequency overlapping waveforms, which in turn results in a significant interference mitigation with analytically tractable statistical characterization. The performance of our new approach is benchmarked against the popular random stepped frequency waveform sequences (RSFWS), where both simulation and analytic results show considerable interference reduction. Furthermore, we perform experimental measurements on commercially available automotive radars to verify the proposed model and framework.
Sruthy Skaria; Akram Al-Hourani; Robin J. Evans; Kandeepan Sithamparanathan; Udaya Parampalli. Interference Mitigation in Automotive Radars Using Pseudo-Random Cyclic Orthogonal Sequences. Sensors 2019, 19, 4459 .
AMA StyleSruthy Skaria, Akram Al-Hourani, Robin J. Evans, Kandeepan Sithamparanathan, Udaya Parampalli. Interference Mitigation in Automotive Radars Using Pseudo-Random Cyclic Orthogonal Sequences. Sensors. 2019; 19 (20):4459.
Chicago/Turabian StyleSruthy Skaria; Akram Al-Hourani; Robin J. Evans; Kandeepan Sithamparanathan; Udaya Parampalli. 2019. "Interference Mitigation in Automotive Radars Using Pseudo-Random Cyclic Orthogonal Sequences." Sensors 19, no. 20: 4459.
Cognitive radio technology has shown tremendous potential through its spectrum access mechanism for reducing spectrum paucity. With the vacant spectrum, two nodes require consensus for common channel in an apposite time. However, in a non-centralised distributed communication system, the task of attaining one common channel for two nodes is not tractable. In this paper we attend to a well known technique for rendezvous in such a cognitive radio network and analytically characterize the performance. The statistical distribution of rendezvous time to obtain common channel is analysed and a closed form expression is derived. Using the distribution we further analyze the mean and maximum rendezvous times and moreover propose an improvement in the considered technique. The theoretical analyses are verified using Monte-Carlo simulations and our results show a very precise match between the two.
Tahidul Islam; Sithamparanathan Kandeepan; Robin J. Evans. Statistical Distribution Analysis of Sender-Jump Receiver-Wait Rendezvous in Cognitive Radio. IEEE Communications Letters 2019, 23, 1310 -1313.
AMA StyleTahidul Islam, Sithamparanathan Kandeepan, Robin J. Evans. Statistical Distribution Analysis of Sender-Jump Receiver-Wait Rendezvous in Cognitive Radio. IEEE Communications Letters. 2019; 23 (8):1310-1313.
Chicago/Turabian StyleTahidul Islam; Sithamparanathan Kandeepan; Robin J. Evans. 2019. "Statistical Distribution Analysis of Sender-Jump Receiver-Wait Rendezvous in Cognitive Radio." IEEE Communications Letters 23, no. 8: 1310-1313.
The optical wireless technology has great potential in realizing high-speed wireless communications in indoor applications, and the silicon photonics platform has been widely investigated to provide photonic integrations using advanced CMOS facilities. In this paper, the silicon integration of key beam steering function in high-speed infrared indoor optical wireless communication systems is proposed and investigated. The beam steering function is realized through edge couplers based silicon integrated optical phased array to achieve both wide operation bandwidth and high power efficiency. A 1×4 integrated phased array is designed and fabricated, and up to 12.5 Gb/s data transmission using the silicon integrated beam steering device through over 1.4 m free-space distance is experimentally demonstrated. Results show that error-free data transmission can be achieved with limited mobility provided to users, and the power penalty of the silicon integrated device is negligible. The outcomes successfully demonstrate the feasibility of using silicon photonic integrations in indoor optical wireless communication systems to realize compact and low-cost solutions.
Ke Wang; Zeshi Yuan; Elaine Wong; Kamal Alameh; Hongtao Li; Kandeepan Sithamparanathan; Efstratios Skafidas. Experimental Demonstration of Indoor Infrared Optical Wireless Communications With a Silicon Photonic Integrated Circuit. Journal of Lightwave Technology 2018, 37, 619 -626.
AMA StyleKe Wang, Zeshi Yuan, Elaine Wong, Kamal Alameh, Hongtao Li, Kandeepan Sithamparanathan, Efstratios Skafidas. Experimental Demonstration of Indoor Infrared Optical Wireless Communications With a Silicon Photonic Integrated Circuit. Journal of Lightwave Technology. 2018; 37 (2):619-626.
Chicago/Turabian StyleKe Wang; Zeshi Yuan; Elaine Wong; Kamal Alameh; Hongtao Li; Kandeepan Sithamparanathan; Efstratios Skafidas. 2018. "Experimental Demonstration of Indoor Infrared Optical Wireless Communications With a Silicon Photonic Integrated Circuit." Journal of Lightwave Technology 37, no. 2: 619-626.
In recent times, aerial base stations(AeBSs) are being investigated to provide wireless coverage to terrestrial radio terminals. The advantages of using aerial platforms to provide wireless coverage are many including larger coverage in remote areas, better line-of-sight conditions etc. Energy is a scarce resource for aerial base stations, hence the wise management of energy is quite beneficial for the aerial network. In this context, we study the means of reducing the total energy consumption by designing and implementing an energy efficient aerial base station as presented in this paper. Sleep mode implementation in base stations (BSs) has proven to be a very good approach for improving the energy efficiency and in this paper we propose a novel strategy for further improving energy efficiency by considering ternary state transceivers for an AeBSs. Using the three state model, we propose a Markovian Decision process (MDP) based algorithm, which intelligently switches between the states of the transceivers based on the offered traffic whilst maintaining a prescribed minimum channel rate per user. We have defined a reward function for the MDP, which helps us to get an optimal policy for selecting a particular mode for the transceivers of the AeBS. Considering an aerial BS with state changeable transceivers, we perform simulations to analyse the performance of the algorithm. Our results show that, around 40% gain in the energy efficiency is achieved while using our proposed MDP algorithm together with the three-state transceiver model compared to the always active mode. We also show the energy-delay tradeoff in order to design an efficient aerial base station.
Nahina Islam; Kandeepan Sithamparanathan; Karina Gomez Chavez; James Scott; Hamid Eltom. Energy efficient and delay aware ternary-state transceivers for aerial base stations. Digital Communications and Networks 2018, 5, 40 -50.
AMA StyleNahina Islam, Kandeepan Sithamparanathan, Karina Gomez Chavez, James Scott, Hamid Eltom. Energy efficient and delay aware ternary-state transceivers for aerial base stations. Digital Communications and Networks. 2018; 5 (1):40-50.
Chicago/Turabian StyleNahina Islam; Kandeepan Sithamparanathan; Karina Gomez Chavez; James Scott; Hamid Eltom. 2018. "Energy efficient and delay aware ternary-state transceivers for aerial base stations." Digital Communications and Networks 5, no. 1: 40-50.
Source localization of primary users (PUs) is a spectrum awareness feature that can be very useful in enhancing the functionality of cognitive radios (CRs). When the cooperating CRs have limited information about the PU, weighted centroid localization (WCL) based on received signal strength (RSS) measurements represents an attractive low-complexity solution. This paper proposes a new analytical framework to accurately calculate the performance of WCL based on the statistical distribution of the ratio of two quadratic forms in normal variables. In particular, we derive an analytical expression for the root mean square error (RMSE) and an exact expression for the cumulative distribution function (CDF) of the two-dimensional location estimate. The proposed framework accounts for the presence of independent and identically distributed (i.i.d.) shadowing as well as correlated shadowing with distance-dependent intensity. The methodology is general enough to include the analysis of the one-dimensional error, which leads also to the evaluation of the bias of the position estimate. Numerical results confirm that the analytical framework is able to predict the performance of WCL capturing all the essential aspects of propagation as well as CR network spatial topology.
Kagiso Magowe; Andrea Giorgetti; Sithamparanathan Kandeepan; Xinghuo Yu. Accurate Analysis of Weighted Centroid Localization. IEEE Transactions on Cognitive Communications and Networking 2018, 5, 153 -164.
AMA StyleKagiso Magowe, Andrea Giorgetti, Sithamparanathan Kandeepan, Xinghuo Yu. Accurate Analysis of Weighted Centroid Localization. IEEE Transactions on Cognitive Communications and Networking. 2018; 5 (1):153-164.
Chicago/Turabian StyleKagiso Magowe; Andrea Giorgetti; Sithamparanathan Kandeepan; Xinghuo Yu. 2018. "Accurate Analysis of Weighted Centroid Localization." IEEE Transactions on Cognitive Communications and Networking 5, no. 1: 153-164.
Spectrum occupancy prediction allows cognitive radio secondary users to exploit temporal spectrum opportunities one step-ahead. Temporal correlations in spectrum sensing measurements can be utilized to predict primary user activity patterns. Where applicable, cooperative spectrum prediction has the potential to improve prediction accuracy compared to single user (local) spectrum prediction. This letter presents the concept and methods for soft fusion-based cooperative spectrum occupancy prediction. The proposed methods were simulated and the results show significant improvement in prediction error over local, and hard fusion-based spectrum prediction.
Hamid Eltom; Sithamparanathan Kandeepan; Ying-Chang Liang; Robin J. Evans. Cooperative Soft Fusion for HMM-Based Spectrum Occupancy Prediction. IEEE Communications Letters 2018, 22, 2144 -2147.
AMA StyleHamid Eltom, Sithamparanathan Kandeepan, Ying-Chang Liang, Robin J. Evans. Cooperative Soft Fusion for HMM-Based Spectrum Occupancy Prediction. IEEE Communications Letters. 2018; 22 (10):2144-2147.
Chicago/Turabian StyleHamid Eltom; Sithamparanathan Kandeepan; Ying-Chang Liang; Robin J. Evans. 2018. "Cooperative Soft Fusion for HMM-Based Spectrum Occupancy Prediction." IEEE Communications Letters 22, no. 10: 2144-2147.
Spectrum scarcity due to inefficient utilisation has ignited a plethora of dynamic spectrum access solutions to accommodate the expanding demand for future wireless networks. Dynamic spectrum access systems allow secondary users to utilise spectrum bands owned by primary users if the resulting interference is kept below a pre-designated threshold. Primary and secondary user spectrum occupancy patterns determine if minimum interference and seamless communications can be guaranteed. Thus, spectrum occupancy prediction is a key component of an optimised dynamic spectrum access system. Spectrum occupancy prediction recently received significant attention in the wireless communications literature. Nevertheless, a single consolidated literature source on statistical spectrum occupancy prediction is not yet available in the open literature. Our main contribution in this paper is to provide a statistical prediction classification framework to categorise and assess current spectrum occupancy models. An overview of statistical sequential prediction is presented first. This statistical background is used to analyse current techniques for spectrum occupancy prediction. This review also extends spectrum occupancy prediction to include cooperative prediction. Finally, theoretical and implementation challenges are discussed.
Hamid Eltom; Sithamparanathan Kandeepan; Robin J. Evans; Ying Chang Liang; Branko Ristic. Statistical spectrum occupancy prediction for dynamic spectrum access: a classification. EURASIP Journal on Wireless Communications and Networking 2018, 2018, 29 .
AMA StyleHamid Eltom, Sithamparanathan Kandeepan, Robin J. Evans, Ying Chang Liang, Branko Ristic. Statistical spectrum occupancy prediction for dynamic spectrum access: a classification. EURASIP Journal on Wireless Communications and Networking. 2018; 2018 (1):29.
Chicago/Turabian StyleHamid Eltom; Sithamparanathan Kandeepan; Robin J. Evans; Ying Chang Liang; Branko Ristic. 2018. "Statistical spectrum occupancy prediction for dynamic spectrum access: a classification." EURASIP Journal on Wireless Communications and Networking 2018, no. 1: 29.
Aerial networks based on Low Altitude Platforms (LAP) provides an excellent method to rapidly deploy flexible communications infrastructure during large-scale emergency and public events. In such situations, it is of utmost importance to extend the lifetime of the battery operated hand-held devices serving on the ground. In this paper, we propose a novel clustering technique to improve the energy efficiency of the terrestrial nodes served by the aerial base-station under uncertain channel conditions on the ground. The proposed technique is analysed by means of simulations and the results are compared with well-known clustering algorithms. The results show that the proposed clustering mechanism significantly improves the energy efficiency of the terrestrial nodes under certain conditions.
Sathyanarayanan Chandrasekharan; Sithamparanathan Kandeepan; Robin J. Evans. EE-CAN: Energy efficient clustering in aerial networks. 2017 11th International Conference on Signal Processing and Communication Systems (ICSPCS) 2017, 1 -6.
AMA StyleSathyanarayanan Chandrasekharan, Sithamparanathan Kandeepan, Robin J. Evans. EE-CAN: Energy efficient clustering in aerial networks. 2017 11th International Conference on Signal Processing and Communication Systems (ICSPCS). 2017; ():1-6.
Chicago/Turabian StyleSathyanarayanan Chandrasekharan; Sithamparanathan Kandeepan; Robin J. Evans. 2017. "EE-CAN: Energy efficient clustering in aerial networks." 2017 11th International Conference on Signal Processing and Communication Systems (ICSPCS) , no. : 1-6.
In this paper we present a simulation based study for the co-channel interference in automobile radars. When multiple automobile radar units (vehicles) use the same frequency channel for profiling the environment (detecting the targets/vehicles) it is of utmost importance how the co-channel interference would affect the radar operation. The interference becomes an issue especially during mass deployment. We present a simulation model for the radar interference study and analyse the target signal to interference power ratio (SIR). The statistical distribution of the SIR and the corresponding outage probability are analysed. The simulator takes into account three random phenomena, the random positions of the vehicles, the random number of vehicles, and the random shadowing of the radar signals. The conditional distribution for the SIR and the probability of outage are presented for various environments.
Nishantha D. J. Hettiarachchi; Sithamparanathan Kandeepan; Robin J. Evans. Automobile radar co-channel interference modeling, simulation and outage analysis. 2017 5th International Conference on Information and Communication Technology (ICoIC7) 2017, 1 -6.
AMA StyleNishantha D. J. Hettiarachchi, Sithamparanathan Kandeepan, Robin J. Evans. Automobile radar co-channel interference modeling, simulation and outage analysis. 2017 5th International Conference on Information and Communication Technology (ICoIC7). 2017; ():1-6.
Chicago/Turabian StyleNishantha D. J. Hettiarachchi; Sithamparanathan Kandeepan; Robin J. Evans. 2017. "Automobile radar co-channel interference modeling, simulation and outage analysis." 2017 5th International Conference on Information and Communication Technology (ICoIC7) , no. : 1-6.
Alagan Anpalagan; Adnan Shahid; Waleed Ejaz; Muhammad Ali Imran; Kandeepan Sithamparanathan; Yuhua Xu. Guest Editorial. IET Communications 2016, 10, 1855 -1857.
AMA StyleAlagan Anpalagan, Adnan Shahid, Waleed Ejaz, Muhammad Ali Imran, Kandeepan Sithamparanathan, Yuhua Xu. Guest Editorial. IET Communications. 2016; 10 (15):1855-1857.
Chicago/Turabian StyleAlagan Anpalagan; Adnan Shahid; Waleed Ejaz; Muhammad Ali Imran; Kandeepan Sithamparanathan; Yuhua Xu. 2016. "Guest Editorial." IET Communications 10, no. 15: 1855-1857.