Jacques Palicot

Cyclostatilonarilty-Based Test for Detection of Vacant Frequency Bands

The problem addressed in this paper is the test for presence of any telecommunication signal within a given frequency band, which is of great importance for cognitive radios. Since a telecommunication signal is well modeled as cyclostationary, we transform this problem to the one of testing for presence of the cylostationary property over a range of cyclic frequencies and we propose a constant false alarm rate (CFAR) multicycle detector based on a chi-squared (x2) statistical test of the time varying covariance estimate

A new concept for wireless reconfigurable receivers

In this article we present the Self-Adaptive Universal Receiver (SAUR), a novel wireless reconfigurable receiver architecture. This scheme is based on blind recognition of the system in use, operating on a new radio interface comprising two functional phases. The first phase performs a wideband analysis (WBA) on the received signal to determine its standard. The second phase corresponds to demodulation. Here we only focus on the WBA phase, which consists of an iterative process to find the bandwidth compatible with the associated signal processing techniques. The blind standard recognition performed in the last iteration step of this process uses radial basis function neural networks. This allows a strong analogy between our approach and conventional pattern recognition problems. The efficiency of this type of blind recognition is illustrated with the results of extensive simulations performed in our laboratory using true data of received signals.

Spectral occupation measurements and blind standard recognition sensor for cognitive radio networks

Cognitive radio has been claimed to be a hopeful solution to the existing conflicts between spectrum demand growth and spectrum underutilization. The basic underlying idea of cognitive radio is to allow unlicensed users to access in an opportunistic and non-interfering manner some licensed bands temporarily unoccupied by licensed users. The cognitive radio concept relies on two basic premises: the current spectrum underutilization, which has been demonstrated in some spectrum measurements campaigns, and the ability of unlicensed users to effectively detect and identify the presence of different licensed technologies in order not to cause harmful interference. In this context, this paper reports the joint work on these two areas that is currently being carried out in the framework of the FP7 Network of Excellence in Wireless COMmunications (NEWCOM++). Concretely, this paper presents spectrum occupancy measurements conducted in the frequency range from 75 MHz to 7075 MHz that demonstrate the low degree to which spectrum is currently used in an urban outdoor environment and also describes the blind standard recognition sensor concept, a sensor embedded in a cognitive radio equipment to enable the identification of many commercial wireless standards without the need to connect to any network. The joint research in both areas is a key step in promoting and validating the idea of dynamic spectrum usage.

A classification of methods for efficient power amplification of signals

This paper presents a classification of methods that have been proposed to address nonlinear power amplification of highly fluctuating signals in telecommunications. The classification proposed uses a tree-like representation wherein each branch refers to a group of methods that all have a common characteristic. By virtue of this representation, each node corresponds to a test used to discriminate between different methods. From top to bottom, these tests are “What is the target of the method?,” Is the method downward-compatible?,” “Is the bit error rate degraded?,” “Is there a useful data rate loss?,” and “Does the method require changes in the amplification function?” By collating all these requirements, an original classification is proposed that is open enough to allow new methods to be added. It only concerns methods located either only at the transmitter or at both transmitter and receiver. The context of this study generally concerns multicarrier signals (especially orthogonal frequency division modulation) but can be applied to any multiplex of modulated signals.

Partial Reconfiguration of FPGAs for Dynamical Reconfiguration of a Software Radio Platform

In the context of a cognitive radio terminal we propose to use partial reconfiguration of FPGAs in order to obtain a enhanced wide band software radio platform. That means the reconfiguration should be performed dynamically (during the run time). Only partial reconfiguration of FPGAs could currently meet this requirement both in terms of power computing efficiency and reconfiguration speed. In this paper we show how it is possible to perform this type of behavior within an heterogeneous platform. We consider in detail three different situations illustrated with the three following examples: the dynamical reconfiguration of a convolutional coder, a constellation mapper, and a FIR filter.

The prediction analysis of cellular radio access network traffic: From entropy theory to networking practice

Although the research on traffic prediction is an established field, most existing works have been carried out on traditional wired broadband networks and rarely shed light on cellular radio access networks (CRANs). However, with the explosively growing demand for radio access, there is an urgent need to design a traffic-aware energy-efficient network architecture. In order to realize such a design, it becomes increasingly important to model the traffic predictability theoretically and discuss the traffic-aware networking practice technically. In light of that perspective, we first exploit entropy theory to analyze the traffic predictability in CRANs and demonstrate the practical prediction performance with the state-of-the-art methods. We then propose a blueprint for a traffic-based software-defined cellular radio access network (SDCRAN) architecture and address the potential applications of predicted traffic knowledge into this envisioned architecture.

Multi-armed bandit based policies for cognitive radio's decision making issues

We suggest in this paper that many problems related to Cognitive Radios (CR) decision making inside CR equipments can be formalized as Multi-Armed Bandit problems and that solving such problems by using Upper Confidence Bound (UCB) algorithms can lead to high-performance CR devices. An application of these algorithms to an academic Cognitive Radio problem is reported.

TACT: A Transfer Actor-Critic Learning Framework for Energy Saving in Cellular Radio Access Networks

Recent works have validated the possibility of improving energy efficiency in radio access networks (RANs), achieved by dynamically turning on/off some base stations (BSs). In this paper, we extend the research over BS switching operations, which should match up with traffic load variations. Instead of depending on the dynamic traffic loads which are still quite challenging to precisely forecast, we firstly formulate the traffic variations as a Markov decision process. Afterwards, in order to foresightedly minimize the energy consumption of RANs, we design a reinforcement learning framework based BS switching operation scheme. Furthermore, to speed up the ongoing learning process, a transfer actor-critic algorithm (TACT), which utilizes the transferred learning expertise in historical periods or neighboring regions, is proposed and provably converges. In the end, we evaluate our proposed scheme by extensive simulations under various practical configurations and show that the proposed TACT algorithm contributes to a performance jump start and demonstrates the feasibility of significant energy efficiency improvement at the expense of tolerable delay performance.

Upper Confidence Bound Based Decision Making Strategies and Dynamic Spectrum Access

In this paper, we consider the problem of exploiting spectrum resources for a secondary user (SU) of a wireless communication network. We suggest that Upper Confidence Bound (UCB) algorithms could be useful to design decision making strategies for SUs to exploit intelligently the spectrum resources based on their past observations. The algorithms use an index that provides an optimistic estimation of the availability of the resources to the SU. The suggestion is supported by some experimental results carried out on a specific dynamic spectrum access (DSA) framework.

A frequency-domain decision feedback equalizer for multipath echo cancellation

A block decision feedback equalizer (DFE) implemented in the frequency domain is derived. The new algorithm is directly applicable to multipath echo cancellation in digital transmission systems. The new equalizer consists of two distinct parts, namely a filtering part of low complexity implementable on a single VLSI chip, and an efficient filter updating part which can be implemented in todays technology DSPs. In both parts, block formulations in the frequency domain are developed, with different block sizes for each case. The resulting equalizer enjoys the computational advantages of frequency domain implementations (studied extensively for linear equalization schemes) offering at the same time the well-known superior performance of DFE.