Spectrum sensing algorithms and software-defined radio implementation for cognitive radio system

The scarcity of spectral resources in wireless communications, due to a fixed frequency allocation policy, is a strong limitation to the increasing demand for higher data rates. However, measurements showed that a large part of frequency channels are underutilized or almost unoccupied. The cognitive radio paradigm arises as a tempting solution to the spectral congestion problem. A cognitive radio must be able to identify transmission opportunities in unused channels and to avoid generating harmful interference with the licensed primary users. Its key enabling technology is the spectrum sensing unit, whose ultimate goal consists in providing an indication whether a primary transmission is taking place in the observed channel. Such indication is determined as the result of a binary hypothesis testing experiment wherein null hypothesis (alternate hypothesis) corresponds to the absence (presence) of the primary signal. The first parts of this thesis describes the spectrum sensing problem and presents some of the best performing detection techniques. Energy Detection and multi-antenna Eigenvalue-Based Detection algorithms are considered. Important aspects are taken into account, like the impact of noise estimation or the effect of primary user traffic. The performance of each detector is assessed in terms of false alarm probability and detection probability. In most experimental research, cognitive radio techniques are deployed in software-defined radio systems, radio transceivers that allow operating parameters (like modulation type, bandwidth, output power, etc.) to be set or altered by software.In the second part of the thesis, we introduce the software-defined radio concept. Then, we focus on the implementation of Energy Detection and Eigenvalue-Based Detection algorithms: first, the used software platform, GNU Radio, is described, secondly, the implementation of a parallel energy detector and a multi-antenna eigenbased detector is illustrated and details on the used methodologies are given. Finally, we present the deployed experimental cognitive testbeds and the used radio peripherals. The obtained algorithmic results along with the software-defined radio implementation may offer a set of tools able to create a realistic cognitive radio system with real-time spectrum sensing capabilities

Experimental exploration over a quantum control landscape through nuclear magnetic resonance

The growing successes in performing quantum control experiments motivated the development of control landscape analysis as a basis to explain these findings.When a quantum system is controlled by an electromagnetic field, the observable as a functional of the control field forms a landscape. Theoretical analyses have revealed many properties of control landscapes, especially regarding their slopes, curvatures, and topologies. A full experimental assessment of the landscape predictions is important for future consideration of controlling quantum phenomena. Nuclear magnetic resonance (NMR) is exploited here as an ideal laboratory setting for quantitative testing of the landscape principles. The experiments are performed on a simple two-level proton system in a H$_2$O-D$_2$O sample. We report a variety of NMR experiments roving over the control landscape based on estimation of the gradient and Hessian, including ascent or descent of the landscape, level set exploration, and an assessment of the theoretical predictions on the structure of the Hessian. The experimental results are fully consistent with the theoretical predictions. The procedures employed in this study provide the basis for future multispin control landscape exploration where additional features are predicted to exist

Multi-antenna energy detector under unknown primary user traffic

In cognitive radio (CR) networks, the knowledge of primary user (PU) traffic plays a crucial role in designing the sensing slot duration and synchronization with PU traffic. However, the secondary user (SU) sensing unit usually does not have the knowledge of the exact time slot structure in the primary network. Moreover, it is also possible that the communication among PUs are not based on synchronous schemes at all. In this paper, the effect of unknown primary user (PU) traffic on the performance of multi-antenna spectrum sensing is evaluated under a flat fading channel. In contrast to the commonly used continuous time Markov model of the existing literature, a realistic and simple PU traffic model is proposed which is based only on the discrete time distribution of PU free and busy periods. Furthermore, in order to assess the effect of PU traffic on the detection performance, analytical expressions for the probability density functions of the decision statistic are derived considering Energy Detection (ED) test as spectrum sensing method. It is shown that the time varying PU traffic severely affects the spectrum sensing performance. Most importantly, our results show that the performance gain due to multiple antennas in the sensing unit is significantly reduced by the effect of PU traffic when the mean lengths of free and busy periods are of the same order of magnitude of the sensing slot

Detecting Lag-One Autocorrelation in Interrupted Time Series Experiments with Small Datasets

The power and type I error rates of eight indices for lag-one autocorrelation detection were assessed for interrupted time series experiments (ITSEs) with small numbers of data points. Performance of Huitema and McKean’s (2000) zHM statistic was modified and compared with the zHM, five information criteria and the Durbin-Watson statistic

Implementation of 5G beamforming techniques on cylindrical arrays

In this paper we study the performance of a Uniform Cylindrical Array for a 5G base station working in the mmW region. Conventional and Capon beamforming design are considered. A comparison against a base station equipped with three Uniform Planar Arrays, one per sector, is presented. Average per-user achievable rate results are provided with different system configuration in terms of network loading and number of antennas, showing that Uniform Cylindrical Array could represent an interesting solution for 5GmmW networks

Performance Analysis of Multi-Antenna Hybrid Detectors and Optimization with Noise Variance Estimation

In this paper, a performance analysis of multi-antenna spectrum sensing techniques is carried out. Both well known algorithms, such as Energy Detector (ED) and eigenvalue based detectors, and an eigenvector based algorithm, are considered. With the idea of auxiliary noise variance estimation, the performance analysis is extended to the hybrid approaches of the considered detectors. Moreover, optimization for Hybrid ED under constant estimation plus detection time is performed. Performance results are evaluated in terms of Receiver Operating Characteristic (ROC) curves and performance curves, i.e., detection probability as a function of the Signal-to-Noise Ratio (SNR). It is concluded that the eigenvector based detector and its hybrid approach are able to approach the optimal Neyman-Pearson performance

Searching for quantum optimal controls under severe constraints

The success of quantum optimal control for both experimental and theoretical objectives is connected to the topology of the corresponding control landscapes, which are free from local traps if three conditions are met: (1) the quantum system is controllable, (2) the Jacobian of the map from the control field to the evolution operator is of full rank, and (3) there are no constraints on the control field. This paper investigates how the violation of assumption (3) affects gradient searches for globally optimal control fields. The satisfaction of assumptions (1) and (2) ensures that the control landscape lacks fundamental traps, but certain control constraints can still introduce artificial traps. Proper management of these constraints is an issue of great practical importance for numerical simulations as well as optimization in the laboratory. Using optimal control simulations, we show that constraints on quantities such as the number of control variables, the control duration, and the field strength are potentially severe enough to prevent successful optimization of the objective. For each such constraint, we show that exceeding quantifiable limits can prevent gradient searches from reaching a globally optimal solution. These results demonstrate that careful choice of relevant control parameters helps to eliminate artificial traps and facilitate successful optimization.Comment: 16 pages, 7 figure

Analysis of circular and cylindrical array arrangements for mmwave 5G beamforming techniques

In this paper, we study the performance of a 5G base station working in the mmWave range equipped with a cylindrical array. Conventional and Capon beamforming techniques are taken into account. We consider both isotropic and directive antenna elements and we evaluate the trade-off between antennas per ring and number of rings with fixed number of total antennas. Results are provided in terms of average achievable per-user rate with different system configurations, such as of network loading. We show that in the presented scenario, where users are randomly deployed in a hexagonal plane, the best performance occurs when the cylindrical array degenerates in a circular array

5G beamforming implementation and trade-off investigation of cylindrical array arrangements

In this paper, we study the performance of a 5G network working at mmW range for the uplink. We consider a single base station scenario equipped with a cylindrical array and a circular array (which can be seen as a single ring cylindrical array), isotropic and directive antenna elements are taken into account and we evaluate the trade-off between antennas per ring and number of rings with fixed number of total antennas. Users are modeled as a spatial Binomial point process in a hexagonal cell. As beamforming techniques, Conventional and Capon algorithms have been considered. As main KPI to evaluate system performance, we consider average achievable per-user rate with different system configurations, such as network loading. The key result of the trade-off investigation is that, when the radius of the cell is much larger than the height of the base station, the best performance occurs when the cylindrical array degenerates in a circular array both when users lay at ground level and with random heights

Searching for quantum optimal controls in the presence of singular critical points

Quantum optimal control has enjoyed wide success for a variety of theoretical and experimental objectives. These favorable results have been attributed to advantageous properties of the corresponding control landscapes, which are free from local optima if three conditions are met: (1) the quantum system is controllable, (2) the Jacobian of the map from the control field to the evolution operator is full rank, and (3) the control field is not constrained. This paper explores how gradient searches for globally optimal control fields are affected by deviations from assumption (2). In some quantum control problems, so-called singular critical points, at which the Jacobian is rank-deficient, may exist on the landscape. Using optimal control simulations, we show that search failure is only observed when a singular critical point is also a second-order trap, which occurs if the control problem meets additional conditions involving the system Hamiltonian and/or the control objective. All known second-order traps occur at constant control fields, and we also show that they only affect searches that originate very close to them. As a result, even when such traps exist on the control landscape, they are unlikely to affect well-designed gradient optimizations under realistic searching conditions.Comment: 14 pages, 2 figure