11 research outputs found
Nondata-Aided Rician Parameters Estimation With Redundant GMM for Adaptive Modulation in Industrial Fading Channel
Wireless networks have been widely utilized in industries, where wireless links are challenged by the severe nonstationary Rician fading channel, which requires online link quality estimation to support high-quality wireless services. However, most traditional Rician estimation approaches are designed for channel measurements and work only with nonmodulated symbols. Then, the online Rician estimation usually requires a priori aiding pilots or known modulation order to cancel the modulation interference. This article proposes a nondata-Aided method with redundant Gaussian mixture model (GMM). The convergence paradigm of GMM with redundant subcomponents has been analyzed, guided by which the redundant subcomponents can be iteratively discriminated to approach the global optimization. By further adopting the constellation constraint, the probability to identify the redundant subcomponent is significantly increased. As a result, accurate estimation of the Rician parameters can be achieved without additional overhead. Experiments illustrate not only the feasibility but also the near-optimal accuracy
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Adaptive Coded Modulation Classification and Spectrum Sensing for Cognitive Radio Systems. Adaptive Coded Modulation Techniques for Cognitive Radio Using Kalman Filter and Interacting Multiple Model Methods
The current and future trends of modern wireless communication systems place heavy demands on fast data transmissions in order to satisfy end users’ requirements anytime, anywhere. Such demands are obvious in recent applications such as smart phones, long term evolution (LTE), 4 & 5 Generations (4G & 5G), and worldwide interoperability for microwave access (WiMAX) platforms, where robust coding and modulations are essential especially in streaming on-line video material, social media and gaming. This eventually resulted in extreme exhaustion imposed on the frequency spectrum as a rare natural resource due to stagnation in current spectrum management policies. Since its advent in the late 1990s, cognitive radio (CR) has been conceived as an enabling technology aiming at the efficient utilisation of frequency spectrum that can lead to potential direct spectrum access (DSA) management. This is mainly attributed to its internal capabilities inherited from the concept of software defined radio (SDR) to sniff its surroundings, learn and adapt its operational parameters accordingly. CR systems (CRs) may commonly comprise one or all of the following core engines that characterise their architectures; namely, adaptive coded modulation (ACM), automatic modulation classification (AMC) and spectrum sensing (SS).
Motivated by the above challenges, this programme of research is primarily aimed at the design and development of new paradigms to help improve the adaptability of CRs and thereby achieve the desirable signal processing tasks at the physical layer of the above core engines. Approximate modelling of Rayleigh and finite state Markov channels (FSMC) with a new concept borrowed from econometric studies have been approached. Then insightful channel estimation by using Kalman filter (KF) augmented with interacting multiple model (IMM) has been examined for the purpose of robust adaptability, which is applied for the first time in wireless communication systems. Such new IMM-KF combination has been facilitated in the feedback channel between wireless transmitter and receiver to adjust the transmitted power, by using a water-filling (WF) technique, and constellation pattern and rate in the ACM algorithm. The AMC has also benefited from such IMM-KF integration to boost the performance against conventional parametric estimation methods such as maximum likelihood estimate (MLE) for channel interrogation and the estimated parameters of both inserted into the ML classification algorithm. Expectation-maximisation (EM) has been applied to examine unknown transmitted modulation sequences and channel parameters in tandem. Finally, the non-parametric multitaper method (MTM) has been thoroughly examined for spectrum estimation (SE) and SS, by relying on Neyman-Pearson (NP) detection principle for hypothesis test, to allow licensed primary users (PUs) to coexist with opportunistic unlicensed secondary users (SUs) in the same frequency bands of interest without harmful effects. The performance of the above newly suggested paradigms have been simulated and assessed under various transmission settings and revealed substantial improvements
A Stochastic Geometry approach towards Green Communications in 5G
In this dissertation, we investigate two main research directions towards net- work efficiency and green communications in heterogeneous cellular networks (HetNets) as a promising network structure for the fifth generation of mobile systems. In order to analyze the networks, we use a powerful mathematical tool, named stochastic geometry. In our research, first we study the performance of MIMO technology in single-tier and two-tier HetNets. In this work, we apply a more realistic network model in which the correlation between tiers is taken into account. Comparing the obtained results with the commonly used model shows performance enhancement and greater efficiencies in cellular networks. As the second part of our research, we apply two Cell Zooming (CZ) techniques to HetNets. With focus on green communications, we present a K−tier HetNet in which BSs are only powered by energy har- vesting. Despite the uncertain nature of energy arrivals, combining two CZ techniques, namely telescopic and ON/OFF scenarios, enables us to achieve higher network performance in terms of the coverage and blocking probabilities while reducing the total power consumption and increasing the energy and spectral efficiencies
D 3. 3 Final performance results and consolidated view on the most promising multi -node/multi -antenna transmission technologies
This document provides the most recent updates on the technical contributions and research
challenges focused in WP3. Each Technology Component (TeC) has been evaluated
under possible uniform assessment framework of WP3 which is based on the simulation guidelines
of WP6. The performance assessment is supported by the simulation results which are in their
mature and stable state. An update on the Most Promising Technology Approaches (MPTAs)
and their associated TeCs is the main focus of this document. Based on the input of all the TeCs in WP3, a consolidated view of WP3 on the role of multinode/multi-antenna transmission
technologies in 5G systems has also been provided. This consolidated view is further
supported in this document by the presentation of the impact of MPTAs on METIS scenarios
and the addressed METIS goals.Aziz, D.; Baracca, P.; De Carvalho, E.; Fantini, R.; Rajatheva, N.; Popovski, P.; Sørensen, JH.... (2015). D 3. 3 Final performance results and consolidated view on the most promising multi -node/multi -antenna transmission technologies. http://hdl.handle.net/10251/7675
Non-Data Aided Rician Parameters Estimation in Temporal Fading Channel With 3 DoFs Gaussian Mixture Model
Rician distribution has been widely utilized to describe wireless fading channel. In the non-stationary temporal fading channel like industrial scenarios, both the specular and scattered components of the multi-path fading channel will be time varying. As a result, the online estimation of Rician parameters is necessary to provide stable wireless service. The traditional estimation approaches of Rician parameters are designed for channel measurement usage and therefore have to work in the data-aided mode for online estimation with modulated I/Q samples. To solve this problem, some non-data-aided algorithms have been proposed in recent years, but only valid in specific scenarios. In this paper, we formulate the estimation of Rician parameters from modulated I/Q samples as a two-dimensional Gaussian mixture model to provide a general non-data-aided Rician parameter estimation method. By involving a priori information of modulation scheme and the motivation of optimized gradient searching, the independent parameters in the maximum likelihood estimation can be significantly decreased to three, which leads to fast convergence of the modified expectation-maximization algorithm with high accuracy. The combination of these modifications has been finally formulated as a Rician mixture model. The numerical results and field measurements illustrate the feasibility of this methodology
1-D broadside-radiating leaky-wave antenna based on a numerically synthesized impedance surface
A newly-developed deterministic numerical technique for the automated design of metasurface antennas is applied here for the first time to the design of a 1-D printed Leaky-Wave Antenna (LWA) for broadside radiation. The surface impedance synthesis process does not require any a priori knowledge on the impedance pattern, and starts from a mask constraint on the desired far-field and practical bounds on the unit cell impedance values. The designed reactance surface for broadside radiation exhibits a non conventional patterning; this highlights the merit of using an automated design process for a design well known to be challenging for analytical methods. The antenna is physically implemented with an array of metal strips with varying gap widths and simulation results show very good agreement with the predicted performance
Beam scanning by liquid-crystal biasing in a modified SIW structure
A fixed-frequency beam-scanning 1D antenna based on Liquid Crystals (LCs) is designed for application in 2D scanning with lateral alignment. The 2D array environment imposes full decoupling of adjacent 1D antennas, which often conflicts with the LC requirement of DC biasing: the proposed design accommodates both. The LC medium is placed inside a Substrate Integrated Waveguide (SIW) modified to work as a Groove Gap Waveguide, with radiating slots etched on the upper broad wall, that radiates as a Leaky-Wave Antenna (LWA). This allows effective application of the DC bias voltage needed for tuning the LCs. At the same time, the RF field remains laterally confined, enabling the possibility to lay several antennas in parallel and achieve 2D beam scanning. The design is validated by simulation employing the actual properties of a commercial LC medium