Oussama Bazzi

Global Ergodic Capacity Closed-Form Expression of Coexisting DVB-LTE-Like Systems

In this paper, we analyze the problem of deploying small cellular cells into a large broadcast cell in the framework of the convergence between the Long Term Evolution (LTE) and the Digital Broadcasting Video (DVB) technologies. In this work, a non- cooperative deployment of these technologies is considered in the sense that cellular and broadcast networks interfere on each other. In literature, there is no work dealing with the ergodic capacity of full cross-interfering links in a DVB-LTE convergence scenario. Our contribution lies in two folds: i) the global ergodic capacity is derived in closed-form with Rayleigh fading channel on each link. This derivation allows us to evaluate the global data rate of the DVB and LTE in a spectral overlap scenario. ii) The analytical forms allow the evaluation of the influence of system parameters on the global and broadcast data rate, e. g. mobile and broadcast power, distance between the broadcast receiver and the LTE base station.

Bayesian and deterministic CRBs for semi-blind channel estimation in SIMO single carrier cyclic prefix systems

Traditionally, the performance of different semi-blind channel estimation algorithms has been assessed and compared to a certain lower bound. One of these famous lower bounds that has been extensively used in the literature is the Cramer Rao Bound (CRB). Depending on how we treat the symbols and the channel, different versions of CRB have been derived. There are two possible cases on how to treat the symbols and/or the channel namely, deterministic unknowns or random. Moreover, the symbols are either jointly estimated with the channel or eliminated. In other words, we have six different cases to be handled. In this paper we present the CRBs that exist in the literature and fit to some of these cases and derive the others in the context of SIMO single carrier cyclic prefix systems (SC-CP). On the top of that we present a unified framework that permits to derive all versions of CRBs in a concrete manner. All the derived CRBs are validated numerically by conducting limited Monte-Carlo simulations.

Bayesian semi-blind FIR channel estimation algorithms in SIMO systems

When the transmission scenario includes a training sequence or pilots, semi-blind channel estimation techniques have shown a tendency to fully exploit the information available from the received signal if they are correctly implemented. This feature leads semi-blind channel estimation performance to exceed that of the schemes based on the blind part or the training sequence only. Moreover, in some situations they can estimate the channel when the other techniques fail. Semi-blind channel estimation techniques were developed and usually evaluated for a given channel realization, i.e. with a deterministic channel model. On the other hand, in wireless communications the channel is typically modeled as Rayleigh fading, i.e. with a Gaussian (prior) distribution expressing variances of and correlations between channel coefficients. In recent years, such prior information on the channel has started to get exploited in pilot-based channel estimation, since often the pure pilot-based (deterministic) channel estimate is of limited quality due to limited pilots. In this paper we provide a performance comparison between ML/MAP algorithms that use Bayesian and deterministic approaches in semi-blind channel estimation.

Teaching microprocessors, microcontrollers, and digital signal processing courses using only one target processor: The newborn dsPIC30F™ from Microchip™

As the technology of electrical and computer engineering (E&CE) grows, undergraduate programs are under constant pressure to keep content up‐to‐date within a 4‐year context of a fixed number of credits hours allowed for graduation. Teaching Microprocessors, Microcontrollers and Digital Signal Processing using only one target processor (dsPIC30F™) can save many credit hours and efforts. The newborn dsPIC30F from Microchip is a microcontroller with digital signal processing power and a new Harvard architecture. In addition, the same processor can be easily used in lab experiments, final year projects and research works.

On the performance evaluation of Eigenvalue-based spectrum sensing detector for MIMO systems

The agility of any cognitive radio system largely depends on the performance of the spectrum sensing technique used. While the Energy Detector (ED) is considered to be a very simple technique in practice, it suffers from noise and measurement uncertainty. To overcome this uncertainty, the Eigenvalue Based Detector (EBD) is currently proposed as a promising technique for spectrum sensing. In this paper, we propose to analyze the performance of such a detector in a finite context. More specifically, we derive the analytical form of the cumulative density function (CDF) and the probability density function (PDF) of the 3xN MIMO like signal based on Wishart matrix. Then, we evaluate the performance of the EBD detector with 2 and 3 antennas in terms of CDF, probability of false alarm, and probability of detection.

Ergodic capacity optimization in coexisting DVB-LTE-like systems

In this paper, the ergodic capacity maximization problem in case of coexistence between digital video broadcasting (DVB) and long term evolution (LTE) systems is studied. A full interference scenario, i.e. where the DVB and LTE systems spectrally overlap, is assumed. The objective function, defined as the summation of the LTE and DVB system capacities, is shown to be constituted by a convex and concave parts and only depends on the ratio of transmitted powers. Hence, we first apply the convex concave procedure (CCCP) to the maximization problem, under QoS constraints, in order to obtain the optimal functioning point. The optimal solution is shown to be the minimum of the global capacity but leads to a strict fairness situation between the LTE and DVB systems. We hence propose a second simple algorithm strictly maximizing the global capacity under QoS constraints. The algorithm leads to a global data rate higher than the one obtained with CCCP but favor largely one system over the other. This study can be useful for operators interested in dense network deployment scenarios to decide the operating point of resources allocated in a very aggressive frequency reuse pattern.

Adaptive data collection approach based on sets similarity function for saving energy in periodic sensor networks

Disaster monitoring becomes a requirement for collecting and analysing data in order to offer a better disaster management situation. Periodic sensor networks PSNs are usually used in disaster monitoring and are characterised by the acquisition of sensor data from remote sensor nodes before being forwarded to the sink in a periodic basis. The major challenges in PSN are energy saving and collected data reduction in order to increase the sensor network lifetime and to ensure a long-time monitoring for disasters. In this paper, we propose an adaptive sampling approach for energy-efficient periodic data collection in sensor networks. Our proposed approach provides each sensor node the ability to identify redundancy between collected data over time, by using similarity functions, and allowing for sampling adaptive rate. Experiments on real sensors data show that our approach can be effectively used to conserve energy in the sensor network and to increase its lifetime, while still keeping a high quality of the collected data.

Effect of RF impairments on spectrum sensing techniques

Spectrum sensing is the key element in the implementation of a cognitive radio equipment allowing the utilization of vacant bandwidth unused by the primary users such as broadcasting white spaces. To implement suitable spectrum sensing techniques, RF front end is mandatory at the secondary devices. However, these front-ends are usually low cost devices implying then some RF impairments which may affect the properties and characteristics of the received signal hence the performance of the spectrum sensing. In this paper, we analyze the effect of three main imperfections on the spectrum sensing capabilities of a CR receiver: the carrier frequency offset, the IQ mismatch and the phase noise. We show that the energy detector is not sensitive to any of these errors while the cyclostationnarity detector is only sensitive to the phase noise while its performance is independent of the carrier frequency offset and IQ mismatch values.

Wavelet denoising in cooperative and NonCooperative spectrum sensing

Cognitive Radio has become an effective solution for the scarcity and the inefficient use of the spectrum. The performance of the cognitive radio (CR) system depends however on how well it can maximize the usage of the free bands without causing interference to primary users. The ability to detect the primary user in CR systems relies on Spectrum Sensing (SS). In this paper we propose a method to improve the performance of Energy Detection SS using Wavelet Denoising. Cooperative and non-cooperative sensing scenarios are considered. Results show that sensing accuracy can be highly improved in the cooperative scenario when the leaves of the tree of wavelet packet transform are used as a basis for denoising. Different mother wavelets are also tested. Simulation results are analyzed and are compared to traditional results.

Fetal ECG extraction from abdominal composite recordings - A preliminary study

Extracting fetal electrocardiogram (ECG) from the abdominal composite signals acquired from the maternal abdomen remains an unsolved problem in biomedical signal processing. The aim of the present study is to recover the fetal ECG directly from the composite signals without the need of recording the maternal ECG reference signal. Thus, a technique that combines independent component Analysis (ICA) and adaptive filtering and that takes into account the propagation delays of the different electrical activities recorded by multiple electrodes placed at different abdominal locations is described. The presented technique is tested on real multichannel recordings. The results show that fetal ECG can be successfully recovered from the composite abdominal signals without the need of recording any reference signal.